Defects go green: using defects in nanomaterials for renewable energy and environmental sustainability

Induction of point defects in nanomaterials can bestow upon them entirely new physics or augment their pre-existing physical properties, thereby expanding their potential use in green energy technology. Predicting structure-property relationships for defects a priori is challenging, and developing methods for precise control of defect type, density, or structural distribution during synthesis is an even more formidable task. Hence, tuning the defect structure to tailor nanomaterials for enhanced device performance remains an underutilized tool in materials design. We review here the state of nanomaterial design through the lens of computational prediction of defect properties for green energy technology, and synthesis methods to control defect formation for optimal performance. We illustrate the efficacy of defect-focused approaches for refining nanomaterial physics by describing several specific applications where these techniques hold potential. Most notably, we focus on quantum dots for reabsorption-free solar windows and net-zero emission buildings, oxide cathodes for high energy density lithium-ion batteries and electric vehicles, and transition metal dichalcogenides for electrocatalytic green hydrogen production and carbon-free fuels.

1 Introduction

The industrial revolution—largely propelled by burning hydrocarbon-containing materials to provide electricity, heating, and power engines (e.g., in motor vehicles)—facilitated over 200 years of sustained human development (Chu and Majumdar, 2012). However, an unfortunate byproduct of burning fossil fuels are large-scale greenhouse gas emissions, which contribute to climate change and ecological deterioration (Chu and Majumdar, 2012; Alstone et al., 2015; Clark et al., 2016; Hallegatte et al., 2016; Schleussner et al., 2016). To ameliorate environmental damage associated with climate change, public policy endeavors must focus on curbing greenhouse gas emissions, while also supporting sustained global development through the expansion of access to inexpensive and reliable energy. Technological innovation will therefore play a pivotal role in achieving a sustainable future. Nanomaterials in particular are poised to contribute to the development of renewable energy production and storage (Chen et al., 2012).

Point defects are single or multiple atom disruptions in the long-range periodicity of crystallographic materials. These atomic impurities often form in nanomaterials, dramatically alter their physical properties (e.g., induce magnetism or metal-insulator transitions) (Lopez-Bezanilla et al., 2015a; Lopez-Bezanilla et al., 2015b; Ganesh et al., 2020; Bennett et al., 2022), and offer a potentially rewarding route for tuning their functionality for enhanced device performance in a broad array of applications. However, predicting the relationship between crystal growth conditions, defect formation, and their corresponding physics is challenging, and has served as a bottleneck to the commercialization of many ubiquitous technologies such as In_xGa_1-xN heterostructure blue light-emitting diodes (LEDs) (Nakamura, 1998). Hence, defect engineering represents an encouraging, but underexplored paradigm to tailor nanostructures for a diverse array of green technology such as solar energy (Giustino and Snaith, 2016) or batteries (Zhao et al., 2020).

Defect engineering efforts will require innovations that link theoretical predictions of defect properties with experimental methods for controlling defect formation in nanomaterials. First principles calculation methods such as density functional theory (DFT) have become a powerful tool in predicting defect physical properties, and guiding experimental efforts to detect and control defect formation during synthesis or post-processing (Freysoldt et al., 2014; Dreyer et al., 2018). Recent advances in scanning transmission electron microscopy (STEM) enable direct measurement and quantification of defects in nanomaterials (Ziatdinov et al., 2017; Madsen et al., 2018; Zhao et al., 2018; Maksov et al., 2019; Ziatdinov et al., 2019; Lee et al., 2020; Guo et al., 2021; Trentino et al., 2021; Yang et al., 2021; Lee et al., 2022; Wu et al., 2022). These ab initio and experimental approaches can be combined with other supplemental experimental techniques such as spectroscopy and scanning tunneling microscopy (STM) to directly resolve nanomaterial defect physics (Ziatdinov et al., 2019). In this context, we review computational and experimental approaches for elucidating defect synthesis-structure-property relationships with the specific aim of unleashing the full potential of defects for green technology. Additionally, we delve into several examples of green technologies where defect engineering has shown promise. These systems of interest include optical defects in quantum dots for Stokes-shift engineered luminescent solar concentrators and net zero-energy buildings, cation-disordered oxides for lithium-ion battery cathodes with improved energy storage capabilities, and defects in transition metal dichalcogenide electrocatalysts for green hydrogen production.

2 Defect formation in nanomaterials: theory and chemistry

2.1 Types of defects

Crystallographic materials exhibit periodicity wherein atoms are arranged in a consistent repeating pattern. The term point defect is generally used to indicate a single or few atom “break” in periodicity such as a missing or misplaced native lattice atom (intrinsic defect), or a foreign atom not normally present in the lattice (extrinsic defect, Figure 1) (Tuller and Bishop, 2011; Freysoldt et al., 2014; Dreyer et al., 2018; Fuhr et al., 2023). Intrinsic defects are generally classified as either vacancies (missing anion or cation), anti-site defects (atomic species in the lattice swap positions such as a cation occupying a lattice site expected to be an anion), or interstitials (cation or anion occupies an interstitial space in the lattice). Extrinsic defects can occupy substitutional or interstitial lattice sites as dopants, or form as adatoms on the surface. The specific lattice site and charge of point defects are commonly described using Kroger-Vink notation (Kröger et al., 1956). Defect atomic identity is indicated by the first letter, and for most defect types (intrinsic or extrinsic), the subscript designates the lattice site where the defect occurs. The exceptions to this rule are vacancies and interstitials for which “V” is used to indicate a vacancy and the subscript “i” is used to indicate interstitial. The superscript indicates the electronic charge at the defect lattice point: “x” signifies no charge, “/” denotes a negative charge, and “•” represents a positive charge. For example, a sulfur anion vacancy with a +2 charge in MoS₂ would be denoted as V_S^•• (a sulfur atom is missing from a sulfur lattice site leaving a +2 charge, Figure 1A), a sulfur interstitial in MoS₂ with a −2 charge would be indicated as S_i^// (Figure 1B) and a O²⁻ dopant on a Te²⁻ site in WTe₂ (net charge of 0) as O_Te^x (Figure 1C) (Kröger et al., 1956).

FIGURE 1

FIGURE 1. (A–C) DFT generated STEM digital twins for defects in monolayer TMDs. Reproduced with permission from Fuhr et al. (2023).

Kroger-Vink theory—in its original conception—describes defect formation under thermodynamic equilibrium by charge-compensated formal reaction pathways. If we consider a simple binary ionic material (MA where M is a 2+ metal cation and A is a chalcogen or oxygen 2− anion), these reaction pathways could include Schottky defects (V_A^•• + V_M^//), Frenkel pairs (V_A^•• + M_i^//, or V_M^•• + M_i^//), antisite defect pairs (M_A^•••• + A_M^////), or non-stoichiometric defects wherein a charged defect is compensated by the oxidation or reduction of another atom (e.g., V_A^•• + 2M_M^/). Regions of lattice disorder, (Cen et al., 2023), distortion (Ding et al., 2018), or non-stoichiometry (Fuhr et al., 2020a) are not always well described by Kroger-Vink reaction pathways, but the notation is still commonly used. Using the notation we described earlier for ionic material MA, metal or anion deficient synthesis conditions could yield M_1-xA or MA_1-x structures with ordered metal vacancies. For this illustrative example the material would not have defects in the traditional sense. Yet, the Kroger-Vink metal vacancy notation is still often used (e.g., as observed with iron sulfides, ceria, or strontium titanate) (Zhuang et al., 2014; Li et al., 2017a; Luo et al., 2021).

2.2 Predicting defect stability

Despite its clarity, consistent bookkeeping of all charge-compensating Kroger-Vink reactions is unrealistic for nanomaterials at-scale (Freysoldt et al., 2014). This problem is even further exacerbated in off-equilibrium processes such as ion implantation. However, the creation of defects alters local chemical bonding (e.g., breaking bonds to form vacancies) in nanomaterials and generally invokes an enthalpic energy penalty. Density functional theory (DFT) or similar electronic structure approaches can therefore be used to calculate formation enthalpies and predict the type and relative concentrations of defects (Freysoldt et al., 2014; Dreyer et al., 2018). This approach assumes a grand canonical material system wherein individual defects interact with an electron reservoir (described by the Fermi level), and their energy can be calculated as a function of the energy of the electron reservoir and relative concentration of each atomic species. The DFT route can shed light onto the likelihood of various defects to form under thermal equilibrium conditions, their relative concentration, local geometry, and corresponding structure-property relationships.

The usual approach for calculating defect formation energy via DFT or related methods is to separately optimize the geometry of a pristine supercell or surface, and compare its energy to the same structure with defect “X” at charge state “q” using Eq. 1:

${\mathrm{E}}_{\mathrm{f}}\left[{\mathrm{X}}^{\mathrm{q}}\right]={\mathrm{E}}_{\text{tot}}\left[{\mathrm{X}}^{\mathrm{q}}\right]-{\mathrm{E}}_{\text{tot}}\left[\text{pristine}\right]-{\displaystyle {\sum }_{\mathrm{i}}}{\mathrm{n}}_{\mathrm{i}}{\mathrm{\mu }}_{\mathrm{i}}+q{\mathrm{E}}_{\mathrm{F}}+{\mathrm{E}}_{\text{corr}}(1)$

where E_tot[X^q] is the total energy of a supercell or surface with the specified defect in charge state q, E_tot[pristine] is the total energy of the defect-free supercell or surface, μ_i represents the chemical potential for atomic species i either added (positive n_i where n notes the number of atoms added by exchange from a chemical reservoir) or subtracted (negative n_i where n notes the number of atoms removed by exchange to a chemical reservoir). The Fermi-level (E_F) describes the energy of the electron reservoir that exchanges electrons with the lattice resulting in a positive or negative charge (q) for electrons removed or gained by the material, respectively. E_F is conventionally described in relation to the valence-band (VB) where E_F = 0 reflects a Fermi-level exactly at the valence band maximum, and the upper bound for E_F is the conduction band (CB) of the material. A correction term E_corr is often added to account for the finite-size of the supercells and k-point meshes on elastic or electrostatic interactions and are described in greater detail elsewhere (Makov and Payne, 1995; Lany and Zunger, 2008; Freysoldt et al., 2009; Komsa et al., 2012; Freysoldt et al., 2014; Dreyer et al., 2018).

The low concentration of defects in materials requires that DFT approaches use large supercells (e.g., 50–200 atoms). Computational expense for DFT based approaches scale with size and the number of electrons in the material, which makes predicting defect stability and structure-property relationships challenging. For example, it is well-known that pure DFT functionals such as the Perdew Burke Ernzerhof (PBE) do not accurately predict semiconductor band gaps (Le Bahers et al., 2014). One route to improve the accuracy of DFT is to include some degree of Hartree Fock direct exchange using a hybrid functional (e.g., HSE06), but this comes at significantly greater computational expense. Hence, predicting optical transitions for defects is much more complicated than for defect-free materials due to the simultaneous requirement of computationally expensive functionals and large supercells. In addition, DFT treatment of surfaces (with or without defects) is often required to predict structure-property relationships at the nanoscale, and similarly scales poorly with hybrid functional or other beyond pure DFT methods. While we do not focus here on specific electronic structure approaches for dealing with large supercells, these are important considerations for predicting defect formation and corresponding physics and are reviewed elsewhere (Makkar and Ghosh, 2021; Broberg et al., 2023).

DFT-calculated formation enthalpy is typically determined at 0 K, and the usually positive value is often interpreted to indicate that entropy and temperature are needed to overcome the enthalpic energy barrier—resulting in a negative Gibbs free energy and enabling defects to spontaneously form. Among the various types of entropy, configurational and vibrational are the most frequently discussed. In the context of understanding defects, configurational entropy pertains to atomic rearrangements resulting from local disruptions of periodicity, while vibrational entropy encompasses modified phonon interactions and changes in chemical bonding. Configurational entropy can be calculated by combining cluster expansion approaches with Monte Carlo, while packages such as Phonopy can be used to determine vibrational entropy using either the Hessian matrix from density functional perturbation theory (DFPT) calculations or the finite displacement method (Freysoldt et al., 2014; Sutton and Levchenko, 2020; Kaczkowski et al., 2021). These additional contributions are typically ignored in most studies due to the high computational cost of performing both enthalpic and entropic calculations. DFT-calculated formation enthalpy is generally considered sufficient to predict structure-property relationships and general trends in the type and relative concentration of defects that will form in nanomaterials under different oxidizing/reductive environments and relative precursor concentration (e.g., metal deficient synthesis vs. chalcogen deficient synthesis). However, interest in high-throughput DFT and beyond 0 K approaches is growing, and are essential to predict more precise relationships between synthesis conditions and defect creation (Balachandran et al., 2017; Choudhary et al., 2023; Mosquera-Lois et al., 2023).

2.3 Synthesis and control of defect formation

The theoretical principles underpinning defect formation predictions have several general implications for nanomaterial synthesis. The type and concentration of defects that form in nanomaterials is strongly influenced by the relative concentration of each atomic species during synthesis or post-processing, as well as whether the experiments are conducted in a more reductive (high E_F) or oxidative (low E_F) environment (Liu et al., 2014a; Du et al., 2021). The set of defects with the lowest formation energies under the specific experimental conditions will prevail. For instance, ignoring kinetic considerations, cation-poor and oxidative growth conditions could favor the creation of negatively charged metal vacancies. Furthermore, the repercussions of local geometric and electrostatic distortions vary by chemical bonding motif. Although the first principles assessment of chemical bonding in the material is not flawless, it remains instructive. For example, closed packed structures less frequently exhibit Frenkel defects due to the additional energy required to squeeze an interstitial ion into the lattice (geometric penalty). On the other hand, materials with metallic or covalent bonds tend to form antisite defects or partial cation disorder due to the lower electrostatic penalty compared to ionically bonded materials (YOO and TULLER, 1987; Tuller and Bishop, 2010; Tuller and Bishop, 2011; Hu et al., 2017).

As discussed earlier, the formation enthalpy of defects is generally positive (unfavorable). Entropic stabilization or external energy is therefore required to overcome the enthalpic penalty to create defects in most materials. These observations are suggestive that growth/post-processing temperature—or the inclusion of external energy sources such as plasmas or light—can be used to control defect formation. Hence, most defect engineering strategies revolve around managing the relative concentrations of each species, establishing an oxidative or reductive environment, and/or controlling external energy factors such as temperature during nanomaterial synthesis or post-processing. For extrinsic defects such as dopants, solubility (maximum concentration attainable by a dopant) and diffusivity (rate at which atomic species spreads across the material at a finite temperature) also need to be taken in consideration (Freysoldt et al., 2014).

The predominant method for managing defect distribution in-situ during nanomaterial synthesis typically entails regulating temperature and atomic species concentration. The synthesis of V_O-rich SnO_2-x nanosheets, achieved through a hot-injection reaction between SnSe nanosheets and organic residue, serves as an illustrative method for creating anion vacancies via temperature control (Zhong et al., 2019). Multinary nanomaterials—such as Cu_xIn_2-xSe_yS_2-y (CISeS) nanocrystals—frequently have their defect distribution tuned by adjusting precursor ratios. In this case, Cu-deficient nanocrystals tend to form V_Cu^/ whereas Cu_In^// are more commonly observed in near-stoichiometric or Cu-rich nanocrystals (Ueng and Hwang, 1989; Ueng and Hwang, 1990; Kim et al., 2012; Jara et al., 2016; Fuhr et al., 2017; Yun et al., 2018; Houck et al., 2019; Fuhr et al., 2020a; Fuhr et al., 2020b; Du et al., 2020; Frick et al., 2020; Liang et al., 2023). Adjusting synthesis temperature and precursor ratios has been shown to enhance the density of vacancies during chemical vapor deposition (CVD) or chemical vapor transport (CVT) synthesis of transition metal dichalcogenides (TMDs, Figure 2) (Enyashin et al., 2013; Lin et al., 2016; Li et al., 2017b; Liang et al., 2021). CVD synthesis occurs at a lower temperature than CVT, and uses more volatile precursors and shorter growth times (Shi et al., 2015). The density of sulfur vacancies can be controlled by the sulfur rate (rate at which sulfur-containing compounds are introduced to the reaction environment) (Gutiérrez et al., 2013; Peimyoo et al., 2013; van der Zande et al., 2013). Both CVD and CVT have also been used to dope nanostructures (Chen et al., 2013; Dumcenco et al., 2013; Zhang et al., 2014a; Feng et al., 2014; Suh et al., 2014; Tongay et al., 2014; Li et al., 2015; Gao et al., 2016; Lin et al., 2016; Deng et al., 2021; Liang et al., 2021). However, the high temperature and long growth times generally leads to greater control of the spatial distribution and density of defects with CVT, which has been demonstrated with Mo_xW_1-xS_y, Mo_xW_1-xS_ySe_2-y, and MoS_xSe_2-x monolayers. Enhanced control of dopant distribution has also been observed in colloidal quantum dots by using hot-injection and diffusion methods to dope Mn in CdSe, ZnSe, and PbSe quantum dots (Mikulec et al., 2000; Norris et al., 2001; Ji et al., 2003; Jian et al., 2003; Vlaskin et al., 2013; Rice et al., 2016; Singh et al., 2019). The high energy of interstitial defects typically precludes their formation in QDs, and dopants are usually assumed to be substitutional unlike nanostructured oxides where both substitutional and interstitial defects are well-known to form (Norris et al., 2001; Robertson et al., 2011; Zhang et al., 2014b).

FIGURE 2

FIGURE 2. Schematic depiction of CVD vs. CVT process for creating defects in TMDs (A–C), light and plasma induced defects in graphene oxide (D), and electron beam induced defects on TMDs (E). Figures reproduced with permission from Deng et al. (2021) for (A–C), Kondratowicz et al. (2018) for (D), and Wu et al. (2022) for (E).

Despite the major advances, controlling the density and distribution of defects in nanomaterials in-situ remains difficult and post-processing methods are often required. Post-synthesis annealing and altering the cooling rate after calcination have been used to create antisite defects and cation site disorder in LiNi_xMn_2-xO₄ and LiNi_0.45Mn_1.45Cr_0.1O₄ phases (Liu et al., 2012; Zheng et al., 2012; Liu et al., 2014b). High-temperature annealing of oxide films in an oxygen deficient environment has been well established to induce oxygen loss and create V_O even in inert environments (Kell et al., 2022). This effect can be further enhanced by inclusion of a reductant such as hydrogen (Merdrignac et al., 1992; Jeong et al., 2003; Chen et al., 2011; Shi et al., 2014; Bonu et al., 2015; Chen et al., 2015; Xiong et al., 2018; Kim et al., 2020; Xiong et al., 2022). Thermal annealing in a pre-determined atmosphere has been extended to non-oxide systems to control the distribution of other anion vacancies such as V_N in C₃N₄ (Niu et al., 2014), or chalcogenide vacancies in MoTe₂, VSe₂, or PdSe₂ (Zhu et al., 2017; Chen et al., 2019; Chua et al., 2020; Zhang et al., 2020). Similar to in-situ methods, control of the heating rate and duration is central to controlling defect density and distribution. This approach can also be extended to nanomaterial doping as exemplified by PdSe₂ wherein the use of an oxidative ozone environment was used to generate oxygen dopants (Liang et al., 2020a). High temperature annealing is not always required to create an oxidative or reductive environment, and solution phase routes can be advantageous for large-scale manufacturing due to their lower energy input requirements, decreased use of harmful chemicals, and overall improved safety. NaBH₄ is a frequently employed solution-phase reducing agent capable of extracting lattice oxygen atoms in materials (e.g., K₄Nb₆O₁₇ ultrathin nanosheets or TiO₂ nanoparticles) to create V_O (Bi et al., 2014; Fang et al., 2014; Mao et al., 2014). Chemical reduction with NaBH₄ can create V_O in ZnO nanorods or SnO₂ nanoparticles at temperatures as low as 30°C–190°C, which is far lower than that required for vacuum annealing (500°C–800°C) (Ansari et al., 2013; Lv et al., 2013; Bonu et al., 2014; Wang et al., 2015a; Wang et al., 2018a; Sahu et al., 2019; Zeng et al., 2020; Xiong et al., 2022). Similar success in controlling the density of V_O has been demonstrated using other solution-phase reductants, including ethylene glycol or glycerol for oxygen vacancy formation in BiOCl or Bi₂WO₆ (Jiang et al., 2013; Ye et al., 2015; Chen et al., 2023).

Temperature and oxidative/reductive environments are not the only post-growth methods capable of generating ample external energy to surmount enthalpic barriers for defect generation. Bi-O bonds in BiOCl nanosheets are long and have a low bond energy, which can be broken with UV photons to create surface oxygen vacancies (Ye et al., 2011; Ye et al., 2012; Jiang et al., 2013; Wu et al., 2018). Photons can also employed to convert chalcogen vacancies to oxygen dopants, as demonstrated in the case of WSe₂ (Lu et al., 2015). Ion-beam bombardment is a common route for substitutional dopant creation—such as Sb-implantation of SnO₂ nanowires (Zhu et al., 2005; Kim et al., 2020). Perhaps counterintuitively, they can also be used to expel lattice atoms and cause atomic rearrangement on the surface without any substitutional doping, as demonstrated with the creation of O_i^// and Sn_i^•••• in SnO₂ nanostructures by high-energy (45–75 MeV) bombardment of Ni⁺ and He²⁺ ions, or vacancy formation in MoSe₂ monolayers via He⁺ ion beam nanoforging (Jeong et al., 2003; Rani et al., 2008; Shi et al., 2014; Iberi et al., 2016; Kwon et al., 2016). Electron beams can create electrons with sufficient kinetic energy to cause knock-on effects. This phenomena can be understood as high-energy electrons from the electron beam transferring enough energy to dislodge atoms from the nanomaterial and create atomic defects (Lingerfelt et al., 2019; Lingerfelt et al., 2020; Lingerfelt et al., 2021). This effect has been demonstrated with nanomaterials such as graphene and TMDs (e.g., MoTe₂, MoS₂, WS₂, and WSE₂) (Algara-Siller et al., 2013; Komsa et al., 2013; Zan et al., 2013; Ziatdinov et al., 2017; Wang et al., 2018b; Elibol et al., 2018; Moody et al., 2018; Nguyen et al., 2018; Maksov et al., 2019; Dyck et al., 2020; Roccapriore et al., 2022). The latter case is particularly well-known due to the high mobility of chalcogen atoms and their relative ease of diffusion out of the structure due to beam-matter interactions. However, these effects are not limited to carbon or chalcogen materials and have been demonstrated in oxides as well (Egdell et al., 1987; Belloni, 2006; Komuro and Matsumoto, 2011). Plasma etching is also a powerful method to create anion vacancies in TMDs, and chalcogen vacancy creation has been demonstrated using Ar plasmas in MoS_2, WSe₂, PdSe₂, and PtSe₂ (Wu et al., 2017; Oyedele et al., 2019; Shawkat et al., 2020; Tsai et al., 2022). Exposure to plasmas can create vacancies in these and other structures, and the defect type and concentration can be controlled by adjusting the plasma gas type (Kondratowicz et al., 2018), irradiation time, or intensity (e.g., generating O-Mo bonds using oxygen plasma) (Islam et al., 2014; Kang et al., 2014; Nan et al., 2014).

3 Energy harvesting: luminescent solar concentrators and net-zero emission buildings

The juxtaposition of global urbanization and the need to lower greenhouse gas emissions require net zero emission buildings wherein annual power consumption is fully counterbalanced by on-site renewable generated energy. Installing conventional photovoltaic (PV) units on a large scale is challenging within dense urban layouts. Energy demands for large buildings frequently exceed those of individual housing units, and PV cells are constrained to rooftop space that is inadequate to meet energy demands (Meinardi et al., 2017). To address these issues, interest has grown in using luminescent solar concentrators (LSCs) as potential building-integrated semi-transparent PV windows (Debije and Verbunt, 2012; Meinardi et al., 2017; Papakonstantinou et al., 2021). LSCs are constructed by doping or coating a glassy or polymeric waveguide with chromophores (Figure 3A) (Debije and Verbunt, 2012; Meinardi et al., 2017). The chromophores absorb broadband solar radiation and re-emit at a specific wavelength, which is guided by internal reflection within the waveguide to the edges or window frame where it is converted into electricity by PV cells (Yablonovitch, 1980; Currie et al., 2008; Sark et al., 2008; Banal et al., 2014). The specific wavelength of re-emission varies by the chromophore material, but near-infrared emission is generally targeted because it is semi-transparent, aesthetically pleasing, and more likely to attain public acceptance (Saifullah et al., 2016).

FIGURE 3

FIGURE 3. (A) Schematic depiction of LSCs, and their potential usage as building-integrated photovoltaic units. Reproduced with permission from Meinardi et al. (2017). (B) CISeS absorption and emission spectra (red and black lines) compared with the solar spectrum (grey shading) and Si solar cell peak EQE (green line). Reproduced with permission from Meinardi et al. (2015).

An ideal LSC chromophore should hold three major optical properties: a large absorption cross-section for capturing sunlight, a high emission efficiency (defined by quantum yield, or $\mathbf{\Phi }=\frac{{\mathbf{N}}_{\mathbf{\text{photons}}\text{emitted}}}{{\mathbf{N}}_{\mathbf{\text{photons}}\text{absorbed}}}$) particularly in the near-infrared region, and a large Stokes shift (Klimov et al., 2016; Gungor et al., 2022). While this review centers on chromophore materials design, other device aspects are important to consider and are discussed elsewhere (Yablonovitch, 1980; Currie et al., 2008; Sark et al., 2008; Banal et al., 2014; Saifullah et al., 2016). Regarding the first two properties, exemplary chromophores should absorb sunlight in both the visible and near-infrared (near-IR) spectral ranges, and re-emit at near 100% quantum yield (QY) allowing for collection by the PV edges. The emitted photons would preferably fall within the near-IR range to achieve both a semi-transparent aesthetic, and also to boost device performance by matching the peak external quantum efficiency (EQE) of the PV device (Figure 3B) (Sark et al., 2008; Meinardi et al., 2015). The chromophore should also have a large Stokes shift, or exhibit peak emission markedly red-shifted from the absorption onset energy. The large Stokes shift is crucial to mitigate reabsorption losses, which are caused by substantial spectral overlap between absorption and emission. Reabsorption losses scale with device dimensions, and chromophores with small Stokes shifts will have poor performance if manufactured at conventional window sizes (Klimov et al., 2016; Gungor et al., 2022).

Several dyes such as 4-dicyanomethyl-6-dimethylaminostiryl-4H-pyran (DCM), CRS040 Yellow, or Lumogen Red have been explored as potential chromophores for LSCs (Batchelder et al., 1979; Sark et al., 2008; Desmet et al., 2012). Though well-studied, molecular dyes struggle to combine all three LSC chromophore optical requirements in the same material: strong broadband optical absorption, high QY, and large Stokes shift with near-IR emission. Quantum dots (QDs) have been proposed as alternative chromophores because of their well-known size-tunable broadband absorption, and the ability to achieve high QY in the near-IR spectral ranges (Pietryga et al., 2016). However, most conventional QDs such as CdSe have a small Stokes shift (tens of meV), which make them unsuitable for LSCs due to prominent reabsorption losses (Pietryga et al., 2016). Several routes have been explored to induce large Stokes shifts in QDs without losing their other potential advantages as LSC chromophores. Most of these approaches involve either doping the QDs with substitutional defects, or designing multinary QD alloys (e.g., ternary or quaternary) that typically form intrinsic defects.

Binary QDs (e.g., CdSe) can be doped directly during crystal growth, or via cation exchange (Mikulec et al., 2000; Norris et al., 2001; Ji et al., 2003; Jian et al., 2003; Meulenberg et al., 2004; Stouwdam and Janssen, 2009; Corrado et al., 2010; Gul et al., 2011; Srivastava et al., 2011; Viswanatha et al., 2011; Vlaskin et al., 2013; Rice et al., 2016; Pinchetti et al., 2018; Singh et al., 2019; Najafi et al., 2021). In the first case, QDs are grown by a conventional strategy such as hot injection wherein precursors are injected into a solvent at high temperature to induce rapid nucleation and growth for size control. During the conventional synthesis route, a dopant is introduced and kinetically competes with host cations during crystal growth. A challenge with this route is that impurity atom binding is unfavorable due to physical attribute mismatching (e.g., differences in charge or ionicity). Cation exchange, on the other hand, involves first synthesizing the QD with conventional methods, and then immersing them in a cation exchange solution with potential dopants. An advantage of such an approach is that the anion sublattice is retained, and crystal composition can be altered without dramatic changes in QD size or shape. This physical process is governed by rapid diffusion driven by the differences in the chemical potential of the QD and impurity solution. While cation exchange often provides for better compositional control than kinetic doping, cation combinations are more limited.

Substitutional transition metal impurities induce red-shifted emission without significantly altering the absorption onset, concurrently increasing the Stokes shift to mitigate reabsorption losses in LSCs. Substitutional Mn²⁺ dopants are the most extensively studied in II-VI QDs—emitting photons via an internal ⁴T₁ → ⁶A₁ d-d transition following excitation by energy transfer from the QD host. The energy of photon emission is fixed at approximately ∼590 nm or 2.1 eV (Figure 4A) (Norris et al., 2001; Erwin et al., 2005; Beaulac et al., 2009), while QD absorption is tunable by nanocrystal size. The absorption onset can therefore be shifted to bluer spectral energies until there is virtually zero overlap between absorption and emission, which results in reabsorption-free LSCs (Erickson et al., 2014). However, the fixed wavelength resulting from the internal emission process for Mn²⁺ dopants yields two key drawbacks. Solar absorption is confined to a narrow spectral region due to the potential of reabsorption when the QD band gap is smaller than 2.2 eV (∼560 nm). Furthermore, the emission exhibits a pronounced yellow-orange hue instead of the preferred semi-transparent shading (Pietryga et al., 2016).

FIGURE 4

FIGURE 4. Absorption and emission spectra for Mn-doped QDs (A), and a comparison between Cu-doped and undoped QDs in (B,C). Reproduced with permission from Erickson et al. (2014) for (A) and Viswanatha et al. (2011) for (B,C). For Mn-doped QDs the absorption and emission mechanism is depicted schematically in an additional panel to the right of (A), and for Cu-doped QDs it is depicted in the inset of (C).

The emission mechanism for Ag⁺ and Cu²⁺ dopants is markedly different from Mn²⁺ dopants. Radiative recombination occurs via relaxation of a conduction band (CB) electron from the QD host and a hole localized at the dopant energy level (Figures 4B, C) (Lingerfelt et al., 2019, Lingerfelt et al., 2020, Lingerfelt et al., 2021, Wang et al., 2018a, Elibol et al., 2018, Komsa et al., 2013, Algara-Siller et al., 2013, Roccapriore et al., 2022). While the emission transition for both Ag⁺ and Cu⁺ dopants appears to be similar, the hole localization process differs for each structure due to their distinct electron configurations. Cu²⁺ dopants have a 3d⁹ electron configuration, which results in a pre-existing hole in its ground state that can directly recombine with the excited-state CB electron from the host QD (Viswanatha et al., 2011; Knowles et al., 2015; Nelson and Gamelin, 2018; Fuhr et al., 2019; Hughes et al., 2019; Harchol et al., 2022). On the other hand, Ag⁺ has a 3d¹⁰ electron configuration, which must capture a photogenerated hole from the VB (Pinchetti et al., 2018; Najafi et al., 2021). For both cases, the emission wavelength is consequently governed by the energy difference between the hole localized at the Ag⁺ or Cu²⁺ dopant and the CB electron. The Stokes shift is determined by the energy difference between the hole localized at the dopant site and the valence band (VB). The CB electron energy is size-tunable, which allows for larger QDs with redder absorption and near-IR emission to be synthesized without dramatically increasing reabsorption.

The band gap for copper and silver doped QDs is still somewhat large, which limits spectral absorption coverage for LSCs and has driven research interest in Cu_xIn_2-xSe_2-yS_y (CISeS) QDs. CISeS QDs have size tunable absorption all the way to the near-IR range, a large Stokes shift (300–500 meV), a near colorless emission wavelength that well-matches the peak EQE of the LSC PV cells (Figure 3B), and have recently achieved greater than 95% QY (Ueng and Hwang, 1989; Ueng and Hwang, 1990; Kim et al., 2012; Knowles et al., 2015; Jara et al., 2016; Fuhr et al., 2017; Xia et al., 2017; Bergren et al., 2018; Nelson and Gamelin, 2018; Yun et al., 2018; Houck et al., 2019; Hughes et al., 2019; Makarov et al., 2019; Fuhr et al., 2020a; Fuhr et al., 2020b; Du et al., 2020; Frick et al., 2020; Velarde et al., 2020; Hinterding et al., 2021; Xia et al., 2021; Harchol et al., 2022; Liang et al., 2023). The origin of CISeS Stokes shifted emission has commonly been ascribed to defects, but with several other proposed mechanisms depending on the type of defect that forms, and the band-edge transition itself (described later in the review). It has been suggested that near-stoichiometric (and especially Cu-rich) CISeS QDs have antisite (Cu_In^//) defects, and that Cu-deficient QDs have V_Cu^/ charge compensated by oxidation of a lattice Cu⁺ atom to Cu²⁺ (Cu_Cu^•) (Fuhr et al., 2020a; Fuhr et al., 2020b). Considering that Cu_In^// defects are in the +1 oxidation state (3d¹⁰ configuration) and Cu²⁺ defects in the 3d⁹ configuration, hole localization is thought to occur via a similar process as Ag⁺ dopants for Cu_In^// (near-stoichiometric or Cu-rich QDs) and Cu²⁺ dopants for Cu_Cu^• (Cu-deficient QDs).

Both defects involve recombination from a delocalized CB electron, sharing many of the same advantages as Ag⁺ and Cu²⁺-doped structures. However, precise control of synthesis conditions becomes crucial due to variations in emission channels between each defect type. Specifically, the hole localization process for Cu_In^// defects involves intragap absorption, which is absent for Cu_Cu^• defects (Figure 5). A potential conclusion from this observation would be that the sharper absorption edge for Cu-deficient structures arising from the removal of Cu_In^// defects should lead to superior LSC performance via reduced spectral overlap between absorption and emission, and correspondingly improved reabsorption losses. This prediction is partially correct, but misses quantum yield considerations. Moderately Cu-deficient structures exhibit sharper absorption, reduced spectral overlap, and even higher QY due to deactivation of hole trapping pathways (Jara et al., 2016; Fuhr et al., 2020a; Fuhr et al., 2020b). However, if QDs become too Cu-deficient eventually other defects (e.g., In_Cu^••) can form in larger densities and reduce QY via electron trapping (Jara et al., 2016; Fuhr et al., 2020a; Fuhr et al., 2020b). These findings are suggestive that the defect chemistry of CISeS QDs is highly sensitive to synthesis conditions, and that likely the complex distribution of defects and LSC performance will strongly vary with other experimental parameters such as temperature or pH.

FIGURE 5

FIGURE 5. Antisite defects in CIS QDs have been predicted to form in near-stoichiometric structures (left panel) and copper vacancies charge compensated by lattice copper oxidation in Cu-deficient structures (right panel). CIS has two absorption pathways if antisite defects are present (h$\mathrm{\upsilon }$_x and h${\mathrm{\upsilon }}_{\mathbf{\text{Cu}},\mathbf{\alpha }}$ for band-edge absorption and Cu¹⁺ absorption, respectively). CIS with V_Cu + Cu_Cu^• only exhibit the h$\mathrm{\upsilon }$_x pathway. Antisite defects undergo excited state reorganization, which further red-shifts emission due to the Cu_In^// → Cu_In^/ Jahn-Teller distorted photoconversion process (similar to the singlet-triplet splitting model). “Near-stoichiometric” CIS therefore has absorption/emission dominated by the antisite defect pathway (similar to Ag⁺-doped QDs), and Cu-deficient CIS by the V_Cu induced Cu_Cu^• pathway (similar to Cu²⁺-doped QDs). Reproduced with permission from Fuhr et al. (2020a).

The precise emission mechanism is still under debate for CISeS QDs, and other models that do not require defects such as the self-trapped exciton or inverted band-edge hole model have been discussed (Knowles et al., 2015; Shabaev et al., 2015; Nagamine et al., 2018; Nelson and Gamelin, 2018; Hughes et al., 2019; Anand et al., 2020; Harchol et al., 2022). For the purposes of this general review on defects in nanomaterials we do not attempt to determine the model that most accurately depicts the exact CISeS emission mechanism. We instead focus on two key points: 1) many of these proposed models are not mutually exclusive, and 2) defects likely affect the emission process, LSC performance, and their formation is sensitive to chemical processing conditions. The predicted Stokes shift for the band-edge hole inversion model is expected to be smaller than the defect-induced emission, and are difficult to resolve experimentally due to partial overlap with strong Cu-defect emission unless defect-free QDs can be synthesized (Batchelder et al., 1979, Desmet et al., 2012, Meinardi et al., 2015). The self-trapped exciton model involves the same hole localization and excited-state reorganization mechanism described for antisite defects and Ag⁺ dopants, but is argued to instead occur via band-edge states to cause the large Stokes shift without the need for defects (Batchelder et al., 1979, Desmet et al., 2012, Meinardi et al., 2015).

These distinctions may prove valuable in future LSC efforts, particularly in resolving routes to reduce spectral linewidths to further diminish reabsorpiton losses. However, it is important to note that regardless of the precise emission mechanism, defects likely strongly impact spectral properties for CISeS QDs and are important to control for LSC performance. There is extensive evidence that the spectral properties of CISeS QDs are highly sensitive to chemical processing in ways that binary QDs are not. Single particle spectroscopy studies have shown radiative lifetimes and photoluminescence (PL) linewidths that can vary by several hundreds of ns or several hundreds of meV, respectively (Zang et al., 2017; Hinterding et al., 2021; Xia et al., 2021). Ensemble absorption and emission spectroscopy has resolved both two channel absorption and two channel emssion (Jara et al., 2016; Fuhr et al., 2020a; Fuhr et al., 2020b; Xia et al., 2021), and the magneto-optical charateristics vary significantly across studies with different QD batches. (Rice et al., 2014; Knowles et al., 2015; Fuhr et al., 2020a; Anand et al., 2020; Fuhr et al., 2020b). These large variations are atypical for QDs, and defect-free structures are atypical for covalently bonded multinary structures—especially those with large variations in stoichiometry (Alvarez-Garcia et al., 2000; Hahn et al., 2001; Paier et al., 2009; Ye et al., 2019; Vijay et al., 2021; Han et al., 2022; Quadir et al., 2022). Given these characteristics and the well-known tendency to form defects in the bulk CISeS phase (Ueng and Hwang, 1989; Ueng and Hwang, 1990; Alvarez-Garcia et al., 2000; Hahn et al., 2001), it is highly likely that defects are impacting the spectral properties in some way, and that regardless of the precise emission mechanism understanding synthesis-defect formation relationships for CISeS QDs could improve LSC performance.

4 Energy storage: batteries and electric vehicles

Fossil fuel powered vehicles are a major contributor to CO₂ emissions and climate change. As such, electric vehicles (EVs) have attracted widespread interest, and their proliferation persists. In this context, lithium-ion batteries (LIBs) power a diverse array of consumer electronics that have become indispensable to modern-society, and their integration into commercial EVs has enabled an alternative to the combustion engine. In conjunction with a greener grid (e.g., utilizing recent innovations in solar and wind technology) EVs powered by LIBs will be critical in lowering CO₂ emissions and reducing the deleterious impacts of climate change (Chu and Majumdar, 2012; Clark et al., 2016). A typical LIB has a solid-state anode and cathode separated by a liquid or gel electrolyte that shuttles ions between the two electrodes during charging and discharging (Manthiram, 2020). For EVs, ideal electrode materials should yield a high energy density, superior rate capability, and long cycle life for consumer acceptability—allowing for extended driving ranges, fast charging, and low maintenance costs.

The achievable energy density of an electrode material is proportional to its capacitance and voltage. Capacitance represents the amount of charge each electrode material can store, and the voltage represents the energy difference between the anode and cathode redox potentials. Hence, an optimal anode would exhibit stable, redox-inactive lower energy levels and a high lying energy band—relative to vacuum or the standard Hydrogen electrode—where redox reactions occur. The opposite is true for the cathode, which should have its highest redox active energy band at the lowest feasible energy (within the limitations of electrolyte stability). Stanley Whittingham demonstrated the first rechargeable LIB at Exxon Corporation using a TiS₂ cathode, which could not be commercialized due to the safety hazards of using Li metal as an anode, and the limited energy density arising from the 2.5 V discharge voltage (Whittingham, 1976). Oxide p-bands lie at lower energies than sulfides (2p vs. 3p electrons), and allow the access of lower lying redox energy states such as the Co^3+/4+ redox couple in LiCoO₂ (Goodenough, 1971; Mizushima et al., 1981). Oxide cathodes, specifically LiCoO₂, extended the voltage range of LIBs to 4V and allowed for the usage of graphite as an anode material by incorporating Li into its as-synthesized lattice structure. These advancements improved the energy density and safety of LIBs, were central to the eventual commercial success of LIBs, and awarded the Nobel prize in chemistry.

The success of LiCoO₂ in commercializing LIBs is laudable, but many challenges persist. LiCoO₂ has a layered cathode structure with a cubic close-packed oxide sublattice and Li⁺ and Co³⁺ ions ordered on alternate (111) planes (Mizushima et al., 1981). The good cation ordering stems from the significant size difference between Li⁺ and Co³⁺ and aids electronic and ionic conduction. Li⁺ ionic conduction occurs via low energy barrier face-sharing tetrahedral voids between octahedra (o-t-o pathway). Shared octahedra along the cobalt plane enable Co-Co interactions for enhanced electronic conductivity. Specifically, Co³⁺ is oxidized to low-spin Co⁴⁺ during LIB charging, leading to the inclusion of holes in the cobalt t₂g^6–x band, and causing Li_1-xCoO₂ to become metallic during charging (Nishizawa and Yamamura, 1998; Chebiam et al., 2001a). However, the overlap between the top of the O²⁻:2p and Co^3+/4+ bands leads to the release of oxygen if charged more than 50% (Chebiam et al., 2001b; Venkatraman et al., 2003). This limits the practical capacity (∼140 mA h g⁻¹), and in conjunction with the high cost of cobalt has driven the search for new rock salt LiMO₂ (where M = a transition metal) alloys.

Cation-ordered LiMO₂ structures crystallize in several common motifs such as the γ-LiFeO₂ (tetragonal structure where Li⁺ and Fe³⁺ ions are well-ordered on octahedral sites, Figure 6A), low-temperature spinel-like LiCoO₂ structure (all Li⁺ ions are ordered on the 16c octahedral sites, Figure 6B), or $\mathit{\alpha }$-NaFeO₂ (Li and M are ordered along alternating (111) planes, Figure 6C). Cation-disordered structures can also form, as exemplified by $\mathit{\alpha }$-LiFeO₂ for which Li and M are randomly distributed (Figure 6D). Li⁺ ions are located on octahedral O_h sites in both ordered and disordered structures, but cation disorder prevents the earlier described o-t-o Li-migration mechanism (Figure 6E) (Sebastian and Gopalakrishnan, 2003; Manthiram, 2020; Wang et al., 2022a) Specifically, the randomness of cation distribution on the octahedral sites means that the intermediate tetrahedral site in the o-t-o diffusion mechanism could now be connected to either Li or M octahedra. The electrostatic interactions between the four cations of the face-sharing octahedra and the size of the tetrahedral diffusion site (T_d) determine the barrier to diffusion. If surrounded only by Li cations (0-TM channel, Figure 6F), Li⁺ ions will have smaller required distances to diffuse through, combined with weaker electrostatic repulsion due to the low valency of lithium. This pathway therefore exhibits facile lithium migration. However, if one or more of the cations are transition metals (1-TM or 2-TM channels, Figures 6G, H) the increase in both migration distances and electrostatic repulsion will lead to a higher energy barrier, which reduces Li⁺ conductivity by disabling the formation of a percolation network for long-distance diffusion (Wang et al., 2022a; Zhang et al., 2023). Inability to efficiently transport Li⁺ through the o-t-o pathway initially led to little interest in cation disordered rock salt structures.

FIGURE 6

FIGURE 6. (A–D) Types of rock salt cathode structures. The cation ordered structures are shown in (A–C), and an example of cation disorder is shown in (D). Reproduced with permission from Zhang et al. (2023). (E,F) Diffusion models for ordered (E) structures versus disordered structures (F–H). The disordered 0-TM channel (transition metal-free) is shown in (F), while the channels with higher barriers due to transition metals are shown in (G) and (H), for 1 transition metal and 2 transition metals, respectively. Reproduced with permission from Lee et al. (2014).

Monte Carlo simulations have since shown that 0-TM percolation networks can be created if excess lithium (e.g., 10%) in Li_1+xM_1-xO₂ is incorporated into the structure (Lee et al., 2014), giving high conductivity as well as capacity, which has led to renewed interest in these materials (Dixit et al., 2014; Chen et al., 2021a; Szymanski et al., 2022; Patil et al., 2023; Szymanski et al., 2023). Equivalently, when partial Li-occupancies are present, high Li-ion conductivity is expected (Dathar et al., 2017). Lithium-excess cation disordered rock salt structures can be synthesized in any of the structure-types described earlier: γ-LiFeO₂, layered, spinel-like LiCoO₂, and the layered $\mathit{\alpha }$-NaFeO₂ structure-type. Several of these structures have demonstrated capacities beyond currently commercialized LIB cathode materials (Lee et al., 2014; Urban et al., 2014; Wang et al., 2022a; Zhang et al., 2023). Disordered structures that use nickel or manganese for the redox transition metal are the most well-studied. Many nickel alloy (e.g., with Ti, Nb, or Mo) cathodes have been synthesized with high average voltage and tilt slope (Pralong et al., 2012; Lee et al., 2015; Lee et al., 2017a; Källquist et al., 2019; Ouyang et al., 2020). If charged up to 4.6 V, overlap between e_g orbitals in Ni with hybridized Li-O-Li orbitals prevents the complete oxidation/reduction of Ni due to competition with O oxidation (Pralong et al., 2012; Lee et al., 2015; Lee et al., 2017a; Källquist et al., 2019; Ouyang et al., 2020; Zhang et al., 2023). While there are challenges related to the corresponding release of CO₂ and O₂ during the cycling process (surface densification), these materials have exhibited capacities greater than 220 mAh/g (Lee et al., 2015; Yu et al., 2019; Wang et al., 2022a). Manganese structures are also well studied, and Li₄Mn₂O₅ has been shown to exhibit discharge capacities as high as 287 mAh/g (Pralong et al., 2012). Alloying with other metals such as Ti or Nb in Li_1.2Mn_0.4Ti_0.4O₄ or Li_1.3Nb_0.3Mn_0.4³⁺O₂ can further increase the discharge capacity to 300 mAh/g (Yabuuchi et al., 2016a; Lee et al., 2017a). However, irreversible O redox reactions contribute to a large initial discharge capacity, which eventually fades and limits cycle life (Wang et al., 2015b; Lun et al., 2019). Iron and vanadium systems such as Li-Ti-Fe-O and Li-Nb-V-O also show promise. For example, LIBs with discharge capacities equal to or greater than 200 mAh/g have been demonstrated with Li_1.2Ti_0.4Fe_0.4O₂ and Li_1.25Nb_0.25V_0.5O₂ (Yabuuchi et al., 2016b; Nakajima and Yabuuchi, 2017; Wandt et al., 2018; Wang et al., 2019).

Rock salts are not the only class of disordered cathode materials with the potential to improve LIB performance. Spinel LiMn₂O₄ structures have a cubic-closed pack oxygen sublattice where ordered structures consist of Mn³⁺ and Mn⁴⁺ ions occupying octahedral centers (16d) and Li⁺ tetrahedral (8a) sites (Thackeray et al., 1983; Manthiram, 2020). LiMn₂O₄ has a three-dimensional Li⁺ diffusion pathway that enables fast Li conduction; Li⁺ ions migrate between 8a tetrahedral sites via transitioning through low migration barrier empty 16c octahedral sites. Dissimilar to the Li_1-xCoO₂ metallic transition during the charge-discharge process, LiMn₂O₄ remains a small polaron semiconductor. Regardless, Mn-Mn interactions from mixed valence t_2g and e_g states in Mn^3+/4+ facilitates electron hopping and yields good electronic conductivity and high operating voltages (Gul et al., 2011). Jahn-Teller distortions in Mn³⁺:t_2g³e_g¹ contributes to a cubic to tetragonal phase transition, which presents a challenge for LIB performance because of the large volume change induced by the 2Mn³⁺ → Mn²⁺ + Mn⁴⁺ disproportionation reaction (Manthiram, 2020). This leads to dissolution of Mn in the electrolyte and poor cycle life. One route to somewhat circumvent this issue is to alloy LiMn₂O₄ with Ni to form cation disordered LiMn_1.5Ni_0.5O₄ (LMNO). The Ni dopants partially occupy Mn sites, reduce the Mn³⁺ site prevalence, and contribute to a high 4.7 V Ni²⁺/Ni⁴⁺ redox couple (Kan et al., 2017; Liang et al., 2020b; Cen et al., 2023).

LMNO can be synthesized with or without site disorder depending on the temperature (e.g., post synthesis calcination in air above 700°C leads to the formation of the disordered phase and temperatures at or below 700°C the ordered phase, Figure 7) (Kim et al., 2004). Mn atoms are in the +4 oxidation state in the ordered (P4₃32) phase with Ni and Mn located on the 4b and 12d Wyckoff sites, respectively (Kunduraci and Amatucci, 2006; Lee et al., 2017b; Liu et al., 2017). If synthesized at higher temperatures (e.g., greater than 700°C) LMNO forms in the Fd $\overline{\mathbf{3}}$ m space group. The partial reduction of Mn⁴⁺ to Mn³⁺ occurs alongside oxygen vacancy formation, Mn/Ni site disorder, and varied additional impurity phases (e.g., Li_xNi_1-xO) (Chebiam et al., 2001a; Venkatraman et al., 2003; Kunduraci and Amatucci, 2006; Shin et al., 2012; Casas-Cabanas et al., 2016; Aktekin et al., 2019; Haruna et al., 2021; Cen et al., 2023). The partial reduction of Mn⁴⁺ to Mn³⁺ in the cation disordered phase increases the electronic conductivity (>2.5 orders of magnitude) relative to the ordered phase (Kunduraci and Amatucci, 2006). Charging/discharging disordered LMNO as a LIB cathode results in a two-phase reaction when x in Li_xNi_0.5Mn_1.5O₄ is below 0.5 (between Li_0.5Ni_0.5Mn_1.5O₄ and Ni_0.25Mn_0.74O₄), and a solid-solution reaction when x is between 0.5 and 1 due to the Ni^2+/3+ redox couples (Liang et al., 2020b). The solid-solution reaction involves size changes in the parental lattice during charging/discharging, or insertion/extraction of lithium. On the other hand, the two-phase reaction involves interconversion and destruction of the parent cathode structure, which limits lithiation and delithiation kinetics. Notably, the two-phase reaction occurs across the entire x charging range for the ordered LMNO phase (between LiNi_0.5Mn_1.5O₄/Li_0.5Ni_0.5Mn_1.5O₄ and Li_0.5Ni_0.5Mn_1.5O₄/Ni_0.5Mn_1.5O₄), leads to poorer electrochemical stability, reduced rate capability, and lower cycling stability than the disordered structure (Ariyoshi et al., 2004; Liang et al., 2020c).

FIGURE 7

FIGURE 7. Comparing cation ordered and disordered LMNO structures based on their Wyckoff positions. Reproduced with permission from Cen et al. (2023).

Doping LMNO with other metals can further improve the cycling stability and rate capability. Sodium dopants have been shown to enhance cation disorder, decrease particle size, and improve charge transfer by providing extra pathways for electron hopping (Wang et al., 2014). The 5% Na-doped LMNO structure achieved superior rate performance arising from the reduced voltage polarization. Al can be incorporated into LMNO as either substitutional dopants at the Ni/Mn sites via a thermopolymerization method, or in empty surface 16c octahedral sites using atomic layer deposition (ALD), and can prevent transition metal dissolution (Zhong et al., 2011; Piao et al., 2018). This process improves the rate capability and cycling stability by mitigating electrolyte/electrode side-reactions and enabling fast Li⁺ diffusion. The concentration of Mn³⁺ can be increased with iron dopants, which enhances electronic conductivity, reduces voltage polarization, and correspondingly improves cycling performance and rate capability (Liu and Manthiram, 2009). Cr-doped LMNO structures (e.g., LiNi_0.45Cr_0.1Mn_1.45O₄) have also exhibited improved electronic/ionic conductivity with a wide voltage plateau, and cycle-stable structure (Wang et al., 2018c).

5 Energy conversion: electrocatalytic green hydrogen production

Hydrogen has a high energy density (142 MJ/kg), is abundant, and can potentially be used as a clean CO₂ emission-free fuel (Dincer, 2012; Abdin et al., 2020). However, despite these potential advantages over conventional greenhouse gas emitting fuels, H₂ is not readily available in its free form in nature. The predominant industrial routes for hydrogen production rely on thermochemical fossil fuel-related processes such as steam-methane or hydrocarbon reforming, pyrolysis, or coal gasification (Nikolaidis and Poullikkas, 2017; Abdin et al., 2020; Megía et al., 2021). Each of these industrial-scale processes emit greenhouse gases, which has motivated interest in “green hydrogen” production wherein hydrogen is produced via carbon neutral routes. Water electrolysis offers a potentially viable route to produce hydrogen without carbon emissions (Lu et al., 2021; Tan et al., 2023). Catalyst design represents a pertinent challenge for water electrolysis at industrial scales though. To date, the catalysts with the best performance utilize rare metals such as platinum, palladium, iridium, or rhodium (Chen et al., 2021b). These rare earth metals catalysts are known to be commercially expensive and to have negative mining impacts that limit their utility for economically viable and environmentally sustainable hydrogen production at-scale (Glaister and Mudd, 2010; Lu et al., 2021; Tan et al., 2023).

MX₂ phases (where M is a transition metal and X is an oxygen or chalcogenide) are of great interest for many electronic and optical applications (Manzeli et al., 2017). Transition metal dichalcogenides (TMDs) are the most well-studied branch of these materials, and several phases such as MoS₂ and WS₂ are under consideration for replacing platinum group metals catalysts for the hydrogen evolution reaction (HER) (Hinnemann et al., 2005). These two dimensional structures are similar to graphene except that instead of stacked carbon layers separated by weak van der Waals forces (graphite) the bulk structure has stacked metal chalcogen or oxide layers, which similarly can be exfoliated as either a few-layer stacked structure, or as monolayers (Chhowalla et al., 2013). The basal plane of defect-free 2D TMDs is unfortunately catalytically inert, which impedes their electrocatalytic HER performance (Xu et al., 2015). The basal planes can be activated by either inducing defect formation or altering the TMD phase. The latter of these two approaches is often difficult (Kibs et al., 2012; Kong et al., 2013; Voiry et al., 2013; Jiao et al., 2018; Wei et al., 2019; Li et al., 2021; Tan et al., 2023). Using MoS₂ as an example, the 2H phase is a semiconductor and therefore has a lower electron mobility than the metallic 1T phase—yielding reduced HER performance. While converting the 2H phase to 1T could potentially improve charge transfer kinetics, it also involves harsh chemicals and produces only a metastable phase that eventually converts back to the thermodynamically more stable 2H phase (Lukowski et al., 2013). Routes for exposing more catalytically active edge sites on the 2H MoS₂ phase can improve performance, but these do not alter the electronic conductivity significantly.

Alternatively, controlling the density and distribution of defects in TMDs can increase the density of active sites, while simultaneously improving electron mobility by altering the electronic structure. This route is particularly viable with TMDs, which as discussed in the “Synthesis and Control of Defect Formation” section are well-known to form defects in-situ and have many post-processing routes to further control their distribution and density. The Sabatier principle guides HER catalysis design, and states that heterogeneous catalysts that have intermediate binding strengths with reaction intermediates will yield the best performance. Specifically, a catalyst that binds too strongly with the reaction products will not allow for product dissociation, and the active sites of the catalyst will be permanently blocked. On the other hand, a catalyst that binds too weakly to the reactants will not be able to weaken chemical bonds and lower the reaction barrier to improve product yield or selectivity. The most common tool used to illustrate this Goldilocks principle is the volcano plot, which for HER describes $∆$G_H* (binding strength) versus j (exchange current density, Figure 8) (Parsons, 1958).

FIGURE 8

FIGURE 8. (A–C) Volcano plots comparing hydrogen adsorption free energies to Pt for defect-free TMDs (a, depicted by a vacancy-free representative structure in the figure inset), low density anion vacancy concentration (6.25%, b, depicted by a representative structure with a single vacancy), and higher density anion vacancy concentration (25%, c, depicted by a representative structure with four vacancies). Reproduced with permission from Lee et al. (2018).

Among the many defect engineering techniques outlined earlier, the management of vacancy formation in TMDs through a combination of in-situ and ex-situ approaches are the most well-developed, and consequently, the most widely employed for enhancement of $∆$G_H* in TMD-catalyzed HER. First principles calculations have shown that there is an inverse relationship between vacancy formation energy and $∆$G_H* (Lee et al., 2018; Wang et al., 2022b). Localized electronic states resulting from vacancy creation interact with hydrogen electronic states during chemical bonding to reduce the energy cost of bond-breaking from vacancy formation. This process results in stronger hydrogen adsorption for vacancies with larger formation energies. Smaller HOMO-LUMO gaps (highest occupied molecular orbital and lowest unoccupied molecular orbital, respectively), which may encompass localized defect states in addition to band-edges, are also favored. To illustrate the desirability of a small HOMO-LUMO gap, let’s consider group 5 transition metals. As previously described, the hybridization process requires the transfer of two electrons from the HOMO to the bonding state, which necessitates “left-over” electrons occupy the LUMO (Figure 9). This process helps explain the superior performance of ZrSe₂, ZrTe₂, and TiTe₂, which have $∆$G_H* closer to Pt than other TMDs in the volcano plot in Figure 9. An inherent challenge in establishing defect relationships with TMDs lies in the fact that the identical defect types (e.g., vacancies) can elicit distinct effects within the same class of TMDs in different phases. One such example is VS₂ wherein vacancies improve hydrogen adsorption in the 2H phase, but hamper performance in the 1T phase (Zhang et al., 2017). While the general relationships explored so far between vacancy formation and HER performance are informative, each TMD system still requires careful examination.

FIGURE 9

FIGURE 9. Schematic depiction of TMD/hydrogen band diagrams where (A–C) represents defect-free TMDs with group 4, 5, and 6–10 transition metals, and (D–F) represents the same structures with anion vacancies. Reproduced with permission from Lee et al. (2018).

HER performance enhancement via vacancy creation is sensitive to the concentration of defects, and the relationship between vacancy density and performance varies by specific TMD system (Lee et al., 2018). Ab initio computational screening studies have categorized the effects of vacancy density on TMD HER performance into four types. Type-I TMDs exhibit low $∆$G_H* without vacancies. As the vacancy concentration increases the HER performance will improve until it eventually approaches Pt HER performance (e.g., MoS₂, WSe₂, or ReSe₂). Hence, type-I TMDs are initially poor choices for HER catalysts but can be dramatically improved by increasing the vacancy concentration. Type-II TMDs (e.g., MoSe₂ and MoTe₂) have an intermediate $∆$G_H*, or moderately positive $∆∆$G_H* (defined as $∆$G_H* relative to Pt) without vacancies. As the vacancy formation is induced in these structures, there is an initial improvement from their already relatively strong HER performance (eventually matching Pt). However, if the vacancy concentration becomes too large $∆∆$G_H* will become negative and there will be a performance drop. Type-III TMDs (e.g., ZrSe₂ and ZrTe₂) exhibit similar properties as type-II, but with $∆$G_H* already near that of Pt, which indicates that while similar trends hold as described for type-II, the tolerance for including more vacancies is much smaller. The $∆$G_H* for type-I through type-III can therefore be thought of as: TMDs where large vacancy concentrations (type-I), intermediate vacancy concentrations (type-II), and small vacancy concentrations (type-III) are desirable. Type-IV TMDs differ from the other three by exhibiting the opposite $∆$G_H* relationship. For these TMD structures, $∆$G_H* is already larger than Pt, and vacancies will yield a HER performance reduction.

An alternative scheme of modifying TMDs for optimal HER performance is via edge-engineering (Peng et al., 2016; Cui et al., 2017; Hu et al., 2019). As described earlier, the basal plane of non-defective TMDs are catalytically inert. However, stacking 2D TMDs along the edges can increase the exposure of catalytically active edges, and lead to a larger effective surface-area of very active catalytic sites. Recently it was demonstrated using first principles calculations that different types of non-stoichiometric edges in MoSe₂, many of whom have been recently synthesized under a scanning transmission electron microscope (STEM) (Sang et al., 2018), can have near optimal HER activity over conventional stoichiometric edges. They found a strong linear correlation between Bader charges on H and the Gibbs free energy of hydrogen adsorption (ΔG*_H) at these edges, providing a design principle for discovering better HER catalytic edges. HER activity was found to be not only influenced by the formation of H–Se/Mo chemical bonds as previously thought, but also by geometric reconstructions and charge redistribution. The same group subsequently discovered via high-throughput computational screening about nine thermodynamically stable multi-functional edges in MoS₂, many showing optimal HER performance (Hu et al., 2020). STEM was subsequently used as an atomic drill bit for targeted synthesis of specific edge-patterns in 2D TMDs. (Boebinger et al., 2023). Nevertheless, a scalable approach to engineer edges in 2D materials is still lacking, but has significant potential in achieving high HER in TMDs with earth-abundant elements and without involving any critical materials.

These classifications explain many experimental trends, but as observed through other defect systems, a priori prediction of structure-property relationships for defects is complex and difficult. DFT studies on MoS₂ electrocatalysts indicate that high concentrations of sulfur vacancies preferentially agglomerate instead of randomly dispersing throughout the lattice, which partially negates its classification as a type-I defect system (Zhou et al., 2021). However, experimental studies have shown improved performance at high vacancy concentrations because of the unusual interplay between sulfur vacancy formation and exposure of under-coordinated Mo atoms, which become synergistically active as catalytic sites (Li et al., 2019). This is just one of many demonstrations that vacancy formation in TMDs should not only be considered in isolation to other effects in the atomic or electronic structure. Excess vacancy formation can damage the structural integrity of TMDs such as inducing cracks or holes, and the existence of dangling bonds can adsorb other non-hydrogen species (particularly in air) (He et al., 2018; Yang et al., 2019). At low concentrations the co-creation of other defects (e.g., Frenkel pairs) can improve performance by providing additional adsorption sites, or possibly even alternative adsorption mechanisms such as in MoS₂ where the preferred hydrogen adsorption site shifts to a region between the vacancy and interstitial in the Frenkel pair (Xu et al., 2022). This process improved the performance even relative to Pt-doped MoS₂. It is also well-known that defect creation semiconductors leads to localized intragap states, which can contribute to improved electrical conductivity and enhance hydrogen adsorption, but in ways that will wildly vary by which defects form (Li et al., 2016).

6 Challenges and future prospects

Understanding defect formation mechanisms and elucidating their structure-property relationships in nanomaterials is a highly prospective route to commercialize new green energy device architectures, or improve existing ones. A key challenge to address for the future of defect engineering is the development of better integrated theory-experiment workflows wherein the physical properties of a specific defect can be predicted a priori to experiment and the synthesis (or post-synthesis) methods to control the type, concentration, and distribution of defects are known. While partial implementation of such workflows are feasible today, unlocking their full potential requires significant advances in theory and experimental methods. DFT methods for predicting synthesis-structure-property relationships are ever-improving, but the time-scale for calculations is often only marginally faster than running experiments. Avenues for defective material design are continually expanding with the advent of beyond 0 K computational chemistry methods for predicting defect phase stability and advanced electronic structure calculation methods compatible with large supercells for predicting electronic and optical properties of defects. However, each of these routes is computationally expensive and are generally used to explain experimental results posteriori. This problem is further exacerbated if excited-state modeling is considered for gaining mechanistic understanding of QD optical emission processes for optimizing LSCs, or electrochemical-interface modeling is required to improve cation disordered oxides for LIB cathodes or TMDs as catalysts for HER. Hence, further advances in high-throughput calculation methods are required for electronic structure calculations and computational chemistry to be effectively integrated in theory-experiment workflows.

From an experimental perspective, determining synthesis conditions for controlling defect formation in nanomaterials has traditionally relied on an Edisonian trial-and-error methodology. This approach entails selection of initial synthesis conditions, measurement of basic material structure without accounting for defects (e.g., XRD for crystal structure and/or mass spectroscopy for composition), measurement of nanomaterial physical properties (e.g., emission energy), and potentially device performance. The influence of defects on these properties is oftentimes only considered if anomalous characteristics arise. Synthesis methods are then iteratively adjusted to enhance, modify, or eliminate these characteristics. True experimental control of defect chemistry will likely only be achieved if routes for measuring defect structure are regularly integrated in the initial measurement of structure, and the direct impact of synthesis conditions and post-processing on defect distribution are consistently considered. Further advances in in-situ and operando microscopy and spectroscopy techniques, aimed at achieving atomic-level control over defect formation during synthesis (in-situ) or observing their effects on device performance (operando), is equally crucial.

An additional but related challenge is that state-of-the-art techniques for measuring defect structure, such as STEM are also used to create defects. This challenge is particularly pronounced in materials such as TMDs where it is well-known that STEM serves a dual purpose—evaluating the defect distribution in as-synthesized flakes and using the electron beam directly to create defects. Regardless, the prospects for such workflows has been significantly heightened by a recent surge of computational power improving the efficiency of first principles calculations, the synthesis methods outlined here, and advances in material imaging capabilities. The integration of these ever-evolving methods for modeling, synthesis, and imaging into workflows is likely key for defect engineering to reach its full potential. The resulting improvements in nanomaterial design could enable the development of Stokes shift engineered QDs for building integrated photovoltaic units, high-voltage lithium-ion batteries utilizing cation disordered oxides in electric vehicles, and TMD electrocatalysts for green hydrogen production. If the described technologies are then integrated into contemporary cities, a future marked by net-zero emission buildings, fossil fuel-free transportation, and carbon neutral hydrogen production would mark a major step forward in achieving a sustainable future.

Author contributions

AF: Conceptualization, Investigation, Writing–original draft. BS: Conceptualization, Investigation, Writing–review and editing. PG: Conceptualization, Investigation, Writing–review and editing.

Funding

The authors declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Center for Nanophase Materials Science (CNMS) and the Alvin M. Weinberg Fellowship at Oak Ridge National Laboratory.

The authors declare that this study received funding from Oak Ridge National Laboratory. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.

Acknowledgments

AF acknowledges support from the Alvin M. Weinberg Fellowship at Oak Ridge National Laboratory. This work was carried out at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences, a US Department of Energy Office of Science User Facility.

Licenses and permissions

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Conflict of interest

All authors are employees of Oak Ridge National Laboratory, managed by UT-Battelle LLC, an M&O contractor for the U.S. Department of Energy.

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