There is growing interest to leverage optical sensors and data science for nuclear materials analysis in many applications including radioisotope production, safeguards, forensics, security, and the nuclear fuel cycle. Characterizing nuclear materials by traditional methods is challenging due to extreme environments (radiological, temperature, chemical, etc.), specimen availability, and regulations. Optical spectroscopy techniques exhibit several characteristics that make them well-suited for standoff measurements and online monitoring applications. These advantages include rapid/real-time analysis, compatibility with chemical- and radiation-resistant materials, and sensitivity to many species and material properties. Optical techniques can be combined with data science methodologies and experimental design to efficiently account for sample complexity, various instrumental techniques, and the generation of large datasets. The deployment of these methods for the analysis of nuclear materials can improve safety, reduce operational costs, and minimize the consumption of valuable materials.
This Research Topic is dedicated to highlighting the latest advancements in optical sensor and data science development for cutting-edge fundamental and applied research. This collection intends to bring together forward-thinking experts from diverse disciplines to highlight recent advancements and identify future objectives. Rapid technological advancements in terms of instrumental techniques and data processing are being leveraged to provide the nuclear field with robust, rapid, and in situ measurements.
Topics within the scope of this collection include the identification of unique signatures, the development of new protocols and standards, the development of standoff measurements, the design of feedback tools for machine learning driven applications, the improvement of analysis time, the establishment of process control, and the engineering of deployable sensors for hazardous nuclear environments. Articles describing innovative studies, applications, perspectives, and concepts to advance the development and characterization of advanced nuclear materials with optical sensors and data science are welcome.
Topic themes of particular interest to this Research Topic include, but are not limited to, the following:
• Standoff, in situ analysis, and characterization of nuclear materials
• Production and optimization
• Online monitoring
• Sampling and experimental design
• Ensemble learning and sensor fusion
• Advanced data processing strategies
• Optical sensors as a feedback tool
• Forensics and nonproliferation applications
• Standards, guides, and best practices
• Unique signatures
All manuscript types are welcome in this Research Topic.
There is growing interest to leverage optical sensors and data science for nuclear materials analysis in many applications including radioisotope production, safeguards, forensics, security, and the nuclear fuel cycle. Characterizing nuclear materials by traditional methods is challenging due to extreme environments (radiological, temperature, chemical, etc.), specimen availability, and regulations. Optical spectroscopy techniques exhibit several characteristics that make them well-suited for standoff measurements and online monitoring applications. These advantages include rapid/real-time analysis, compatibility with chemical- and radiation-resistant materials, and sensitivity to many species and material properties. Optical techniques can be combined with data science methodologies and experimental design to efficiently account for sample complexity, various instrumental techniques, and the generation of large datasets. The deployment of these methods for the analysis of nuclear materials can improve safety, reduce operational costs, and minimize the consumption of valuable materials.
This Research Topic is dedicated to highlighting the latest advancements in optical sensor and data science development for cutting-edge fundamental and applied research. This collection intends to bring together forward-thinking experts from diverse disciplines to highlight recent advancements and identify future objectives. Rapid technological advancements in terms of instrumental techniques and data processing are being leveraged to provide the nuclear field with robust, rapid, and in situ measurements.
Topics within the scope of this collection include the identification of unique signatures, the development of new protocols and standards, the development of standoff measurements, the design of feedback tools for machine learning driven applications, the improvement of analysis time, the establishment of process control, and the engineering of deployable sensors for hazardous nuclear environments. Articles describing innovative studies, applications, perspectives, and concepts to advance the development and characterization of advanced nuclear materials with optical sensors and data science are welcome.
Topic themes of particular interest to this Research Topic include, but are not limited to, the following:
• Standoff, in situ analysis, and characterization of nuclear materials
• Production and optimization
• Online monitoring
• Sampling and experimental design
• Ensemble learning and sensor fusion
• Advanced data processing strategies
• Optical sensors as a feedback tool
• Forensics and nonproliferation applications
• Standards, guides, and best practices
• Unique signatures
All manuscript types are welcome in this Research Topic.
