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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗

DOE OSTI2019

ROBOT: A Tool for Automating Ontology Workflows

BACKGROUND:Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats. Similar to more general software development, automation is the key to executing and managing these tasks effectively and to releasing more robust products in standard forms. For ontologies using the Web Ontology Language (OWL), the OWL API Java library is the foundation for a range of software tools, including the Protégé ontology editor. In the Open Biological and Biomedical Ontologies (OBO) community, we recognized the need to package a wide range of low-level OWL API functionality into a library of common higher-level operations and to make those operations available as a command-line tool. RESULTS:ROBOT (a recursive acronym for "ROBOT is an OBO Tool") is an open source library and command-line tool for automating ontology development tasks. The library can be called from any programming language that runs on the Java Virtual Machine (JVM). Most usage is through the command-line tool, which runs on macOS, Linux, and Windows. ROBOT provides ontology processing commands for a variety of tasks, including commands for converting formats, running a reasoner, creating import modules, running reports, and various other tasks. These commands can be combined into larger workflows using a separate task execution system such as GNU Make, and workflows can be automatically executed within continuous integration systems. CONCLUSIONS:ROBOT supports automation of a wide range of ontology development tasks, focusing on OBO conventions. It packages common high-level ontology development functionality into a convenient library, and makes it easy to configure, combine, and execute individual tasks in comprehensive, automated workflows. This helps ontology developers to efficiently create, maintain, and release high-quality ontologies, so that they can spend more time focusing on development tasks. It also helps guarantee that released ontologies are free of certain types of logical errors and conform to standard quality control checks, increasing the overall robustness and efficiency of the ontology development lifecycle.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2016

Evaluation of Novel Wet Chemistry Separation and Purification Methods to Facilitate Automation of Astatine-211 Isolation

This research is a collaborative effort between the research groups of the PIs, Dr. D. Scott Wilbur in the Department of Radiation Oncology at the University of Washington (UW) and Matthew O’Hara at the Pacific Northwest National Laboratory (PNNL). In this report only those studies conducted at UW and the budget information from UW will be reported. A separate progress and financial report will be provided by PNNL. This final report outlines the experiments (Tasks) conducted and results obtained at UW from July 1, 2013 thru June 30, 2016 (2-year project with 1 year no-cost extension). The report divides the information on the experiments and results obtained into the 5 specific objectives of the research efforts and the Tasks within those objectives. This format is used so that it is easy to see what has been accomplished in each area. A brief summary of the major findings from the studies is provided below. Summary of Major Findings from Research/Training Activities at UW: Anion and cation exchange columns did not provide adequate 211 At capture and/or extraction results under conditions studied to warrant further evaluation; PEG-Merrifield resins containing mPEG350, mPEG750, mPEG2000 and mPEG5000 were synthesized and evaluated; All of the mPEG resins with different sized mPEG moieties conjugated gave similar 211 At capture (>95%) from 8M HCl solutions and release with conc. NH 4 OH (~50-80%), but very low quantities were released when NaOH was used as an eluent; Capture and release of 211 At when loading [ 211 At]astatate appeared to be similar to that of [ 211 At]astatide on PEG columns, but further studies need to be conducted to confirm that; Capture of 211 At on PEG columns was lower (e.g. 80-90%) from solutions of 8M HNO 3 , but higher capture rates (e.g. 99%) can be obtained when 10M HNO 3 is mixed with an equal quantity of 8M HCl; Addition of reductants to the 211 At solutions did not appear to change the percent capture, but may have an effect on the % extracted; There was some indication that the PEG-Merrifield resins could be saturated (perhaps with Bi) resulting in lower capture percentages, but more studies need to be done to confirm that; A target dissolution chamber, designed and built at PNNL, works well with syringe pumps so it can be used in an automated system; Preliminary semi-automated 211 At isolation studies have been conducted with full-scale target dissolution and 211 At isolation using a PEG column on the Hamilton automated system gave low overall recoveries, but HNO 3 was used (rather than HCl) for loading the 211 At and flow rates were not optimized; Results obtained using PEG columns are high enough to warrant further development on a fully automated system; Results obtained also indicate that additional studies are warranted to evaluate other types of columns for 211 At separation from bismuth, which allow use of HNO 3 /HCl mixtures for loading and NaOH for eluting 211 At. Such a column could greatly simplify the overall isolation process and make it easier to automate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

Automation and Robotics for Space-Based Systems, 1991

A NASA Langley workshop on Automation and Robotics for Space-Based Systems was held on December 10, 1991. This conference proceedings document presents the overhead slides from each speaker at this event. The purpose of this in-house workshop was to assess the state-of-the-art of automation and robotics for space operations from a LaRC perspective and to identify areas of opportunity for future research. The workshop was sponsored by the Guidance, Navigation, and Control Technical Committee, chaired by Mr. Raymond C. Montgomery. Nineteen talks were given, reflecting a high level of interest in the field of automation at NASA Langley. Over half of the presentations came from the Automation Technology Branch, covering telerobotic control, EVA and IVA robotics, hand controllers for teleoperation, sensors, neural networks, and automated structural assembly, all applied to space missions. Other talks covered RMS active damping augmentation, space crane work, modeling, simulation, and control of large, flexible space manipulators, and virtual passive controller designs for space robots.

Automation↗

NASA NTRS1996

Mission simulation as an approach to develop requirements for automation in Advanced Life Support Systems

This paper examines mission simulation as an approach to develop requirements for automation and robotics for Advanced Life Support Systems (ALSS). The focus is on requirements and applications for command and control, control and monitoring, situation assessment and response, diagnosis and recovery, adaptive planning and scheduling, and other automation applications in addition to mechanized equipment and robotics applications to reduce the excessive human labor requirements to operate and maintain an ALSS. Based on principles of systems engineering, an approach is proposed to assess requirements for automation and robotics using mission simulation tools. First, the story of a simulated mission is defined in terms of processes with attendant types of resources needed, including options for use of automation and robotic systems. Next, systems dynamics models are used in simulation to reveal the implications for selected resource allocation schemes in terms of resources required to complete operational tasks. The simulations not only help establish ALSS design criteria, but also may offer guidance to ALSS research efforts by identifying gaps in knowledge about procedures and/or biophysical processes. Simulations of a planned one-year mission with 4 crewmembers in a Human Rated Test Facility are presented as an approach to evaluation of mission feasibility and definition of automation and robotics requirements.

NASA Discipline Number 61-10↗

NASA NTRSDate not supplied

Display and Automation Considerations for the Airborne Collision Avoidance System Xu

In this paper we examine several display and automation considerations of a collision avoidance system that is currently under development: the Airborne Collision Avoidance System (ACAS) Xu. This study builds on previous work conducted as part of NASA’s Unmanned Aircraft Systems (UAS) Integration into the National Airspace System (NAS) project. ACAS Xu represents the next-generation successor to the Traffic Alert and Collision Avoidance System (TCAS II), wherein the Xu variant is intended for UAS applications. Whereas TCAS II exclusively issues RAs in the vertical dimension, a major distinction between ACAS Xu and previous collision avoidance (CA) systems is the introduction of horizontal and “blended” RAs (i.e., RAs with both horizontal and vertical components). This present work was conducted as an engineering analysis involving two parts. In Part 1, a two-by-two, within-subjects study was performed that manipulated how RAs were presented to a pilot situated at a UAS ground control station. Five participants experienced four experimental trials in which text and aural alerting characteristics were manipulated. In Part 2, another five participants experienced four trials in which the levels of automation were manipulated with regard to the CA and return-to-course (RTC) tasks. The results for Part 1 found no effect of display or alerting configuration on pilot performance. However, it was discovered that pilot response time to RAs greatly depended on the RA type. In particular, pilots were quicker to respond to vertical RAs (M = 4.52 seconds) than horizontal (M = 7.42 seconds) and blended (M = 9.68 seconds) RAs in which both dimensions were issued simultaneously. For Part 2 of the study, pilots found both auto-CA and auto-RTC functions equally useful. Most pilots were comfortable with the automation, however responses were mixed. Three of five participants indicated high levels of comfort with the auto-CA function, while two rated their comfort as low. Pilots’ comfort for the auto-RTC functionality was slightly higher: four out of five pilots gave high ratings, while one pilot gave a low rating. Overall, pilots ordinally ranked their preference for automated functions as auto-CA together with auto-RTC (when an aural alert announces a change between CA and RTC states), auto-CA, and auto-CA and RTC (without the aural state-change announcement). Recommendations for improving the display of automation are also discussed.

collision avoidance↗

NASA NTRSDate not supplied

Display and Automation Considerations for the Airborne Collision Avoidance System Xu

In this presentation we examine several display and automation considerations of a collision avoidance system that is currently under development: the Airborne Collision Avoidance System (ACAS) Xu. This study builds on previous work conducted as part of NASA’s Unmanned Aircraft Systems (UAS) Integration into the National Airspace System (NAS) project. ACAS Xu represents the next-generation successor to the Traffic Alert and Collision Avoidance System (TCAS II), wherein the Xu variant is intended for UAS applications. Whereas TCAS II exclusively issues RAs in the vertical dimension, a major distinction between ACAS Xu and previous collision avoidance (CA) systems is the introduction of horizontal and “blended” RAs (i.e., RAs with both horizontal and vertical components). This present work was conducted as an engineering analysis involving two parts. In Part 1, a two-by-two, within-subjects study was performed that manipulated how RAs were presented to a pilot situated at a UAS ground control station. Five participants experienced four experimental trials in which text and aural alerting characteristics were manipulated. In Part 2, another five participants experienced four trials in which the levels of automation were manipulated with regard to the CA and return-to-course (RTC) tasks. The results for Part 1 found no effect of display or alerting configuration on pilot performance. However, it was discovered that pilot response time to RAs greatly depended on the RA type. In particular, pilots were quicker to respond to vertical RAs (M = 4.52 seconds) than horizontal (M = 7.42 seconds) and blended (M = 9.68 seconds) RAs in which both dimensions were issued simultaneously. For Part 2 of the study, pilots found both auto-CA and auto-RTC functions equally useful. Most pilots were comfortable with the automation, however responses were mixed. Three of five participants indicated high levels of comfort with the auto-CA function, while two rated their comfort as low. Pilots’ comfort for the auto-RTC functionality was slightly higher: four out of five pilots gave high ratings, while one pilot gave a low rating. Overall, pilots ordinally ranked their preference for automated functions as auto-CA together with auto-RTC (when an aural alert announces a change between CA and RTC states), auto-CA, and auto-CA and RTC (without the aural state-change announcement). Recommendations for improving the display of automation are also discussed.

collision avoidance↗

NASA NTRSDate not supplied

Thinking outside the box: The human role in increasingly automated aviation systems

Rapid advances in artificial intelligence are enabling automated systems to operate in an increasingly autonomous manner in domains that previously required the involvement of human operators. Examples are rail transport systems, self-driving cars, and warehouse delivery systems. From time to time, such automation encounters operational conditions that fall outside a “competency box” within which the system has been designed to operate. Human operators add resilience because they can see and act outside the competency box of scenarios and environments for which the system was designed. The system’s competencies can be expanded over time with modifications to software, sensors, etc.; however, it is unclear at what point the competency box becomes large enough to safely eliminate the role of the human operator. One area where advanced automation may be applied is Urban Air Mobility (UAM). Current UAM concepts envision fleets of highly automated air vehicles providing on-demand transport for people and goods. A phased development of UAM has been proposed, beginning with on-board pilots and transitioning to a future state where automated vehicles operate with minimal human involvement. Proponents of UAM note that this final state reduces cost as well as eliminating pilot error, identified as a contributing factor in many aircraft accidents. However, eliminating human involvement also risks eliminating their positive contributions to system resilience. Here we examine Concepts of Operation proposed for future UAM systems and explore how humans can best be incorporated to maintain resilience while minimizing cost and risk. A human-autonomy teaming approach is suggested.

Advanced Air Mobility↗

NASA NTRSDate not supplied

Initial Performance Evaluation of Flight Path Management Onboard Automation

Significant developments in automation are necessary to achieve safe and efficient operations in advanced aerial mobility related concepts. Urban Air Mobility (UAM) is rapidly growing, emerging field that poses a challenging use case with a tighter scale of operations compared to the traditional commercial transport paradigm. A large part of the challenge is the uncharted territory; as of this paper, no set of operational standards or guidelines for UAM operations have been established and automated en route operations for UAM level 4 (UML-4) have not been studied. Flight Path Management (FPM) automation provides a set of capabilities that are critical toward enabling airborne vehicles to achieve mission success while maintaining operational safety. An initial performance evaluation of FPM automation was conducted using a UAM-adapted version of the Autonomous Operations Planner (AOP), an onboard trajectory management capability developed over years of research targeting commercial transport operations, as its reference implementation. This paper describes the evaluation, including the approach and methodology for simulating FPM automation in UML-4, key results, future work, and conclusions.

flight path management↗

NASA NTRSDate not supplied

Initial Performance Evaluation of Flight Path Management Onboard Automation

flight path management↗

DOE OSTI2022

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 3

This project is a collaborative research effort between PKMJ Technical Services LLC, Idaho National Laboratory, and Public Service Enterprise Group (PSEG) Nuclear, LLC. The collaboration, led by PKMJ Technical Services LLC, is part of the industry Funding Opportunity Announcement (FOA) award under Advanced Nuclear Technology Development FOA #DE-FOA-0001817. The pilot demonstration focuses on the Circulating Water System (CWS), an important non-safety-related system that impacts the power generation capability of the plant site. Achieving riskinformed condition-based Predictive Maintenance (PdM) on the CWS will result in significant economic benefits, and the developed methodologies can also be applied to other plant systems. This approach supports an industry goal of ensuring that nuclear power generation remains a viable, economically competitive option in the energy market. Operation and Maintenance (O&M) costs include labor-intensive Preventive Maintenance (PM) programs that involve manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies as well as time-based replacement of assets, irrespective of condition. This project offers an alternative by focusing on riskinformed condition-based maintenance to reduce O&M costs while still maintaining plant health and safety. This report summarizes the progress made toward achieving a risk-informed condition-based maintenance approach. The research and development (R&D) activities presented in this report are associated with development of a nuclear digital platform application, integration of fault signature models, and automated work management processes. The fault signatures and Machine Learning (ML) models are key components in predictive analytics and are heavily leveraged to improve the insights received by existing plant process data sources. Availability of the analysis results within a centralized digital platform enhances efficiency by enabling automation of activities otherwise performed manually. Personnel are presented with enhanced information that can be used to evaluate plant status and risks. Utilizing the enhancements to data analytics supports automated responses, (i.e. issuance of work orders) to address developing equipment faults and thus preventing forced, unplanned shutdowns of components or systems. The R&D activities described within this report lay the foundation for developing and demonstrating a digital automated platform to centralize the implementation of condition monitoring and response to equipment faults. The digital automated platform is cloud-based and designed to enable improved efficiency of plant processes. The digital platform includes content related to maintenance optimization, fault signature analysis, and plant records, which can all be used to support efficiencies when located within a centralized digital platform. These efficiencies could be further enhanced when deployed through industry-wide deployment of the technology to improve insights and processes based upon economies of scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Use of Automation in Low Level Waste Storage and Management - 19227

The Australian Nuclear Science and Technology Organisation (ANSTO) generates Low Level Waste (LLW) and Intermediate Level Waste (ILW) from various site operations such as the operation of a research Reactor and the manufacture of Molybdenum 99. The Low Level Solid Waste (LLSW) generated is stored at ANSTO before and after conditioning. The current process flow involves the storage of LLSW waste before conditioning on racks, handled using forklifts. When the unconditioned waste is ready for conditioning, it is transferred to another facility, where volume reduction and packaging is carried out. Once conditioned, the waste is placed in further storage, pending dispatch to the proposed Australian National Radioactive Waste Management Facility (NRWMF). A new purpose built facility has been constructed, adjacent to the LLSW processing facility, for the storage and management of LLSW in both unconditioned and conditioned forms. This new facility will streamline the waste management process and significantly enhance the safety and efficiency of the process. In line with international best practises, the new facility utilises automation solutions to minimise the build footprint, and minimise the use of forklifts and other mobile plant. Most importantly, it applies the principle of ALARA (As Low as Reasonably Achievable) to minimise operator activities in areas where radioactive material is stored and eliminates double handling of the waste. The automation for unconditioned waste utilises an Automated Storage and Retrieval System (ASRS), a vertical stacker crane within high density racking, to provide easy storage and retrieval for processing and/or routine inspections. This system allows operators to control it from outside of the storage area whilst utilising integrated software that allows for the required tracking of the unconditioned waste. From the ASRS storage area, unconditioned waste will have a smooth transition to the processing facility which is located adjacent to the ASRS system. Once conditioned, the waste is catalogued and returned to a designated storage area within the new facility using an automated building gantry crane with a target delivery system to eliminate the need for operators in the main storage bay. The waste will be held here in preparation for dispatch to the future repository. The utilisation of the ASRS for the purpose of storing LLSW is an innovative use of automation that will eliminate operators from active areas, reduce dose rates received and integrate with the waste tracking software. Furthermore, the system has significant advantages with operational efficiencies increased, reduced double handling of nuclear waste and maximum use of building footprint. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

A human automation interaction concept for a small modular reactor control room - 101

Many advanced nuclear power plant (NPP) designs incorporate higher degrees of automation than the existing fleet of NPPs. Automation is being introduced or proposed in NPPs through a wide variety of systems and technologies, such as advanced displays, computer-based procedures, advanced alarm systems, and computerized operator support systems. Research consistently finds that there is a fundamental tradeoff between system performance with increased automation and reduced human performance. Idaho National Laboratory (INL) researchers and NuScale Power human factors and operations staff are working on a collaborative project to address the human performance challenges of increased automation and to determine the principles that lead to optimal performance in highly automated systems. This paper will describe this concept in detail and will describe an experimental test of the concept. The benefits and challenges of the approach will be discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Effects of adaptive automation on operator-system performance - 103

Adaptive automation (AA) is the dynamic, real-time change in the degree of automation in response to situational changes. AA systems are being developed in many industries, including for nuclear power plant applications. AA is a promising means of mitigating human performance issues that often arise in highly automated systems. The purpose of this Nuclear Regulatory Commission study was to characterize important AA design features, define the effects of AA on performance, examine the human factors engineering (HFE) guidance available to design and evaluate AA systems, and identify research and development needs. In general, we found that AA improves task performance and situation awareness (SA) while managing workload. Although the research is limited, AA also supports operator recognition of automation failure and recovery. Research on human-system interfaces has identified principles showing promise for supporting SA, including failure detection, and limiting workload. Research further suggests that AA systems are both more effective, and less disruptive and distracting, when they follow rules of interaction similar to those used by human crewmembers. Our general conclusion about the HFE guidance available to designers and reviewers is that it is limited and has not kept pace with automation technology. We discuss several research and development needs that will help support a better understanding of where and how AA should be used and support the development of more comprehensive guidance for AA safety reviews. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Test case selection procedure for simulation-assisted automation testing - 321

Simulation-assisted automation testing is an efficient tool for validating the automation systems for nuclear power plants. This paper presented a systematic procedure for selecting test cases for simulation-assisted automation testing. The procedure is relies on the plant's licensing framework and allows associating the test cases to the functional requirements in order to produce traceable test set for validation. The procedure is demonstrated with a case study concerning the automation tests of Loviisa NPP's automation renewal project. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Quantifying the Mobility and Energy Benefits of Automated Mobility Districts Using Microscopic Traffic Simulation

Connected and automated vehicles (CAVs) are increasingly being discussed as the basis for shared mobility and on-demand services to replace privately owned vehicles. The rapid growth of transportation networking companies (TNCs) and their increasing investment in automated vehicle (AV) technologies attests to this. Combining the concepts of TNCs, with AV and on-demand transit services, the term 'automated mobility district' (AMD) describes a district-scale implementation of CAV technology to realize the full benefits of a shared, fully automated vehicle service within a confined region. This research effort provides a modeling architecture for AMDs along with a preliminary analysis to quantify the mobility and energy benefits of such districts. A customized open-source microscopic mobility simulation toolkit built on the simulation of urban mobility (SUMO) platform is implemented for AMD performance evaluation. Experimental scenarios are tested with different combinations of operational variables to provide insights on energy and mobility gains that can be realized in AMDs.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2026

Advancing specialized biofoundries via automated adaptive laboratory evolution

Adaptive laboratory evolution (ALE) is a powerful strategy for improving microbial phenotypes by harnessing natural selection under defined environmental conditions. Through applying selection regimes, beneficial mutations accumulate, enabling the generation of strains with enhanced properties. However, conventional ALE is labor-intensive and difficult to scale, limiting reproducibility and broader discovery of evolutionary principles. Recent advances in robotics, automation, and computational infrastructure are transforming ALE into a scalable, data-rich experimental paradigm. Automated platforms enable standardized and complex protocols, real-time monitoring, and highly parallel evolution campaigns, improving consistency while generating longitudinal datasets that reveal convergent adaptive mechanisms. Here, we discuss the role of specialized biofoundries in advancing automated ALE and enabling large-scale evolutionary engineering. We review major automated ALE formats and outline key design principles for effective ALE biofoundries, highlighting how automated ALE can support autonomous experimentation and AI-guided strain engineering.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Automated defect analysis in electron microscopic images

Electron microscopy and defect analysis are a cornerstone of materials science, as they offer detailed insights on the microstructure and performance of a wide range of materials and material systems. Building a robust and flexible platform for automated defect recognition and classification in electron microscopy will result in the completion of analysis orders of magnitude faster after images are recorded, or even online during image acquisition. Automated analysis has the potential to be significantly more efficient, accurate, and repeatable than human analysis, and it can scale with the increasingly important methods of automated data generation. Herein, an automated recognition tool is developed based on a computer vison–based approach; it sequentially applies a cascade object detector, convolutional neural network, and local image analysis methods. We demonstrate that the automated tool performs as well as or better than manual human detection in terms of recall and precision and achieves quantitative image/defect analysis metrics close to the human average. The proposed approach works for images of varying contrast, brightness, and magnification. Furthermore, these promising results suggest that this and similar approaches are worth exploring for detecting multiple defect types and have the potential to locate, classify, and measure quantitative features for a range of defect types, materials, and electron microscopic techniques.

47 OTHER INSTRUMENTATION↗