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DOE OSTI2023

An Overview of the Risk Assessment Information System

This technical memorandum (TM) presents an overview of the Risk Assessment Information System (RAIS), a collection of web-based tools designed to assist with the environmental risk assessment process. The objective of the RAIS is to be a single resource for the risk assessment process, providing guidance when planning and performing the steps: data assessment, exposure assessment, toxicity assessment, and risk characterization. The RAIS evolved as a result of the initial remediation efforts at various United States (U.S.) Department of Energy (DOE) facilities. The goal was to increase the efficiency and transparency of the human health and ecological assessments being performed by DOE’s Office of Environmental Management, Oak Ridge Operations (ORO) office by providing a repository for toxicity information, physicochemical data, risk assessment procedures, standardized risk calculation methods, and web-based tools. Since the initial launch in 1996, the RAIS has expanded its user base outside of the federal government and now has users from over 100 countries, universities, states, and local governments. What sets the RAIS apart from other risk assessment sites are the publicly available, searchable toxicity and physicochemical databases and the wide range of chemical and radionuclide risk calculation tools. The purpose of this TM is to present the RAIS tools in order of the website menus and explain how they fit in the risk assessment process. In addition, this TM describes differences between the chemical and radionuclide tools of the RAIS. Screening level equations, chronic daily intake equations, and default exposure factors used in the chemical and radionuclide calculators are included in the appendices of this TM. This TM is not intended to be a detailed guide to risk assessment or the RAIS tools. The tools on the RAIS can be used to comply with procedures from multiple agencies, including but not limited to DOE, U.S. Environmental Protection Agency (EPA), U.S. Department of Defense (DoD), and many state governments. Further information on the RAIS tools can be found in the user guides and tutorials available on the webpage.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Explainable Artificial Intelligence Technology for Predictive Maintenance

The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Status Report on Regulatory Criteria Applicable to the Use of Artificial Intelligence (AI) and Machine Learning (ML)

Although the interest in the use of artificial intelligence (AI) and machine learning (ML) in nuclear energy is increasing rapidly, at present their implementation is limited. This rapid increase in interest is not surprising considering that implementing AI and ML technology would allow for continuous monitoring, facilitate the implementation of predictive maintenance with optimized staffing plans, enable automation and autonomy opportunities that could drastically reduce fixed operation and maintenance costs, and provide training for operations and maintenance. Other industries are using AI for construction, and in the nuclear arena AI could provide great benefit in decommissioning activities. The ability of AI and ML to operate in real time vastly increases their potential impact. Before AI can be used in design, operations, or as a regulatory tool, the specifics on the regulations applicable to the use of AI for nuclear power applications need to be established. The difficulty is that the specific use cases will dictate the applicability of regulations. For example, even within the application domain associated with operations, the regulations might vary if the AI is used to create a virtual reference for plant operations or is used for training, optimization of maintenance intervals, prioritization of maintenance activities, etc. Different still is if the AI is to be used for design or setting technical specifications, which will introduce additional requirements. US Nuclear Regulatory Commission (NRC) licensing reviews are based on an applicant’s design meeting its performance assessment based on (1) safety goals and objectives, (2) deterministic and/or probabilistic analysis of accident scenarios, and (3) quantitative assessment of design alternatives against the safety goals and objectives using accepted engineering tools, methodologies, and performance criteria. The current regulatory framework does not explicitly address AI or autonomous control. However, as implementing AI technology will require the use of a digital platform, it must meet the requirements of an instrumentation and control (I&C) system. The regulatory requirements for AI, which will be incorporated into the I&C system, will be very dependent on how it is used (i.e., its functionality, safety classification, etc.). The licensing process is primarily risk-based with the identification of components and systems as nonsafety, important to safety, or safety related. A risk-informed approach allows further gradation of components and systems based on risk metrics such as core damage frequency or large early release fractions. Thus, the use cases and the risk categorization of impacted systems and components will determine the regulatory requirements. Regardless of how AI is used it presents new opportunities for risk-informing operating, maintenance, and regulatory decisions. Trustworthiness, transparency, and the ability to validate and verify the results will be paramount in showing that the systems and plant still meet their performance requirements. This report describes the results of research to identify regulatory implications of AI technologies and their uses. Specifically, this report reviews current regulatory guidance relevant to the application of AI for design (including design changes or new designs including advanced reactors), construction, operations, training, maintenance, research, testing, and as a regulatory tool. AI can be automated at different levels from purely informative purposes to autonomous controls. The focus of this review included determination of constraints on the application of AI technology, identification of any regulatory gaps or uncertainties, and clarification of anticipated technical basis information likely to be important for regulatory acceptance of these technologies. Currently, any use of AI at nuclear power plants is focused on nonsafety-related applications. The NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than create new regulations to address the use of AI and ML. This approach seems to be the best to encourage AI development without adding regulatory uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

International Radiation Monitoring Information System (IRMIS) – a versatile EPR tool for all member states [Slides]

IRMIS provides Competent Authorities, IEC, and other relevant International Organizations with a data sharing tool that helps to report and share information, evaluate radiation monitoring data to assess if the public is safe, identify protective actions, keep the public informed by Member State Competent Authority, and maintain transparency of data handling and processing.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Project: Corbomite - Product: ConsoleWorks REACT

TDi Technologies presents ConsoleWorks REACT, an advanced platform designed to tackle the complexities of cyber and operational risk assessment. This comprehensive solution goes beyond asset-focused approaches by considering the impact of both assets and people have on the security and operation of critical infrastructure, specifically targeting preventing gird mis-operation by evaluating real-time human interaction or commands with critical assets. The hypothesis suggests that by integrating the assessment of user commands into the overall risk assessment process, organizations can make more informed decisions, prioritize resources effectively, and respond promptly to potential threats. This hypothesis forms the basis for the development of a proactive and holistic risk management approach that is more comprehensive and context aware than traditional models which only look at assets, patch levels, configuration and threat intel by collecting that information off the network vs directly from the asset, human, and human interaction all in real-time. ConsoleWorks' unique man-in-the-middle architecture is a key feature that sets it apart in the cybersecurity landscape. This architecture enables the real-time observation, enforcement, and commands or interaction risk transparency of user interaction with critical infrastructure to be risk mitigated and audited as they are aggregated with device and human risk factors for a more comprehensive risk threat score across a device or group of devices. This architecture allows ConsoleWorks to act as a secure intermediary between users and critical assets, monitoring all interactions and ensuring that only authorized commands are sent to the asset to be executed. This not only enhances security but also provides a comprehensive audit trail of all user activities, contributing to compliance efforts and facilitating incident investigation and risk management. By integrating this unique architecture with our comprehensive risk assessment methodology, ConsoleWorks REACT provides a powerful solution for managing cyber and operational risks, enabling organizations to maintain a robust security posture and effectively mitigate potential threats. To that end, the primary objective of this project was to research and develop a robust solution that enables the energy industry to mitigate the risks associated with human actions that can compromise the security or operations of assets critical to energy delivery, generation, transmission and operation. ConsoleWorks REACT plays a pivotal role in achieving this goal by leveraging its unique capabilities to monitor and track all user activity. Through its Zero Trust approach, which emphasizes continuous verification, the platform ensures secure access to assets and serves as the centralized human response and notification platform for addressing cyber and operational issues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

DeepDataProfiler: A Platform and Methodology for the Analysis and Interpretation of Neural Networks

The DeepDataProfiler is a methodology and framework for providing interpretability to trained neural networks. Its approach is to decompose a network into a weighted graph of neurons and synapses and link the components of the graph to human identifiable concepts. By identifying concepts important to the network and tracking the decision process employed by the network, the network becomes more transparent and less like a black box. Spurious decisions and poor generalization strategies can be identified and a measure of trustworthiness can be established.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Triton Initiative: FY22 Communications, Outreach, and Engagement End-of-Year Report

The Department of Energy (DOE) Water Power Technologies Office (WPTO) Triton Initiative supports the advancement of the marine energy (ME) industry through environmental monitoring research and technology development. This report presents the results and analysis of the Triton Initiative’s communications, outreach, and engagement (TCOE) efforts in fiscal year 2022. The primary TCOE goals were to: (1) educate and raise awareness of ME and the role of Triton's environmental monitoring research in supporting the industry; (2) build trust with audiences through transparent communications and outreach; and (3) evaluate and refine TCOE tactics based on feedback and metrics. To support these goals, the TCOE team used multiple platforms and approaches. Notable achievements include: (1) 12 newsletter issues sent to 185 subscribers with an average open rate of 56.4%. (2) 10 Triton Stories, resulting in 2,871 collective views contributing to 46% of all Triton website views. (3) 78 Triton-specific social media posts, which generated a total of 81,896 impressions, 1,037 post-clicks, and 7,814 video views. (4) 6,320 Triton website views with increased search engine optimization ranking in several categories. (5) 3 Triton researchers interviewed as guests on two different podcasts, Water Women and Big Deep: An Ocean Podcast. (6) A Triton special issue of the Journal of Marine Science and Engineering (JMSE) featuring 10 peer reviewed publications. All articles ranked in the top 25%, and two in the top 5%, for digital attention of all research outputs scored by Altmetric. (7) A seven-part webinar series called Triton Talks to share and discuss research and results from the research published in the JMSE special issue. Triton leveraged unique opportunities, particularly the JMSE special issue, to disseminate research results to end users, educate stakeholders, and gain valuable feedback. These concerted communication efforts increased exposure across platforms ultimately resulting in greater reach and access across audiences. Based on audience analyses of webinar attendees and newsletter subscribers, the TCOE team was able to successfully engage with general audiences, research partners, and ME stakeholders, including subject matter experts from government agencies, research organizations, and the regulatory community. The TCOE task established channels to gather input and create opportunities for two-way communication with people engaged with Triton’s outreach efforts. The feedback received will enable the TCOE team to support its goals for ongoing evaluation of outreach and engagement tools while continuing to build trust in the ME community and educate diverse audiences about the impactful research conducted by the Triton Initiative. This report is a Triton Initiative Fiscal Year 2022 Quarter 4 Milestone Deliverable due to the DOE WPTO Sponsor on 9/30/2022. An updated version to include data through 9/30/2022 will be delivered in October 2022.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

SoK: A Framework for and Analysis of Software Bill of Materials Tools

Modern software development has gradually become more complex, leveraging available open-source software and third party components. This practice has raised questions about the provenance, licensing, versioning and compliance of reused code and its dependencies. Furthermore, it is par ticularly important to review such code fragments and third party components for known-vulnerabilities before they are included in a software product. A Software Bill of Materials (SBoM) is a mechanism to achieve such an analysis, provid ing transparency and visibility into a software product to both the software developer and its respective consumer. An SBoM lists information and details about all the elements constituting a piece of software and can, therefore, be used to evaluate associated security risk. While the concept of SBoMs is growing in popularity, it is still fairly new to many organizations, causing them to potentially struggle with pro ducing and processing SBoMs and limiting their widespread adoption. In this work, we delve into the area of SBoMs and present the state-of-the-art SBoM tools, creating a framework for analysis and categorizing them based on a diverse set of features and functionalities. We are the first to provide a detailed analysis of 83 open-source SBoM tools along with a perspective on how a potential SBoM user can select a tool based on their specific requirements. Our work aims to help promote understanding of this domain, thereby encouraging and furthering its overall adoption. We additionally seek to pave a path for future work in this area by providing recommendations to tool developers and users, researchers, and standardizing organizations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Microdroplet Electrospray Localized Laser Printing and Sintering of Nanoparticles for Passivating, Carrier-Selective Contacts (Final Technical Report)

In this project, the team used a nanoparticle electrospray laser deposition (NELD) process developed at the University of Central Florida (UCF) to address current limitations of passivating, carrier-selective contact technologies for crystalline silicon (c-Si) photovoltaic (PV) cells. The NELD process was used to print low bulk line resistivity Ag contacts directly onto transparent conductive oxides (TCOs), like indium tin oxide (ITO), for hydrogenated amorphous silicon (a-Si:H) based c-Si heterojunction (SHJ) cells without any subsequent contact firing step needed.

14 SOLAR ENERGY↗
DOE OSTI2023

LA100 Equity Strategies. Chapter 3: Community-Guided Energy Equity Strategies

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided strategies that aim to operationalize recognition and procedural justice. Chapters 1 and 2 target the problem space - the causal factors, impact areas, and values affecting LA's energy justice landscape. This chapter threads those themes through to begin focusing on the solution space. We examine community-identified problems and solutions through the lens of recognition and procedural justice, presenting analysis and strategies that form the basis for more equitable outcomes in LA's energy transition. In our listening sessions, underserved Angelenos highlighted the need to transition away from the status quo one participant described as "transactional extraction of information to check the box. To say yes, we engaged." She asked the LA Department of Water and Power (LADWP) to approach her community with respect and transparency, stating, "We consider you all to be experts in your community, and we'd like to authentically engage with you in the decision-making process. So, I do think there needs to be some intentional actions for that rapport building and that trust building." The community-informed analysis and strategies described in this chapter, which are foundational to the LA100 Equity Strategies project, rise to the challenge of engaging authentically to build rapport, establish relationships of respect, and meaningfully involve Angelenos in the decision-making process. LADWP is already making concerted efforts to redress a disproportionate distribution of investments in physical infrastructure and energy efficient technologies in Los Angeles. This chapter concentrates on the challenge to further rectify past and ongoing inequities in the social, cultural, and institutional scaffolding of Los Angeles. We examine community-guided strategies to tackle this challenge, informed by community input on how all Angelenos can equitably access green jobs and affordable, safe, and resilient energy services, technologies, and programs. These actionable strategies can help move energy equity programs from plans to applied practices, supporting LADWP in launching a just and equitable clean energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Measurement, reporting and Verification (MRV) of non-CO 2 greenhouse gases: International Best Practices and Suggestions for China

Measurement, Reporting, and Verification (MRV) is a systematic approach to tracking and documenting greenhouse gas (GHG) emissions and emission reductions. MRV can be used across all sectors and for all GHGs to track emissions patterns, evaluate programs, and promote transparency. As methane and other short-lived climate pollutants become critical to mitigating near-term climate change impacts, MRV systems become critical in improving emission inventories; facilitating the development of climate change policies and targets, and tracking and demonstrating progress towards sustainable development. This report focuses on current sectoral issues – including the emerging roles for satellites and remote sensing technologies - and international best practices in MRV policies and programs for non-carbon dioxide (CO 2 ) GHGs including methane, nitrous oxide (N 2 O), and hydrofluorocarbons (HFCs) in specific sectors. Based on international best practices and a review of China’s current MRV system, we offer suggestions for a possible path forward for developing and implementing a stronger non-CO 2 MRV system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multi-Probe 24A Pre-Shot report

The Multi-Probe Radiography campaign will field a full day of experiments at the Omega EP laser facility. The day consists of shots alternating between Omega EP’s two short-pulse laser beams. The Backlighter beam will generate proton and deuteron beams from 500-800nm CH/CD film targets, and the Sidelighter beam will accelerate electrons to generate x-rays from 0.5mm x 25-50µm Ø Ta wire targets attached to Compound Parabolic Concentrator (CPC) cones. The ion beams shots will optimize CD foil thickness (maximizing ion energy/yield) for the transparency regime for use as the pitcher in a pitcher catcher neutron-generation platform. Several shots will include a LiF catcher within the NTA and this feeds into future neutron radiography work. X-ray shots will be used to characterize the platform established in FY2020B via measurement of electron spectra with and without the Ta wire, and radiography will be conducted at varying laser energies. This will validate PIC electron acceleration modeling while also demonstrating potential for using the x-ray platform for imaging of thicker objects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans

This guide was developed to improve decision-making in the electricity planning process by strengthening dialogue between electricity system planners and stakeholders throughout the process. This document was created for anyone who is first getting exposed to scenario results from power system planning models, or for those who are beginning to interact with power system modelers. It does not assume any experience with power system modeling, or familiarity with electricity planning concepts. This guide can be helpful to a wide range of people, including but not limited to state utility commissioners and commission staff, state energy offices, and intervenors in the planning process. It is targeted to those who are evaluating or reviewing model results presented by a utility, which typically span utility-scale generation and storage (and associated transmission) assets. This guide is designed to provide enough background and guidance that stakeholders can formulate and ask questions to evaluate model results through a deeper understanding of the key assumptions, data, and methods that drive decision outcomes. The ultimate purpose of this work is to increase transparency in the electricity planning process by enabling stakeholders to better engage and evaluate model results. A follow-on guide will provide a deeper dive into emerging topics, which are expected to become more prominent in the electricity planning process, but whose methods and approaches are still being refined.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Area V: Waste Management and Subsurface Science (FY21-23 Final Report)

The objective of the Waste Management and Subsurface Science Topic Area V project is to evaluate the feasibility and safety of an intermediate-depth borehole for disposal of Israel Atomic Energy Commission (IAEC) nuclear waste. The IAEC nuclear waste is currently stored in above ground and/or in near-surface facilities that provide short-term radiological worker safety but do not provide long-term, full security and safeguards protection for the nuclear material. Disposal of the IAEC nuclear waste several hundred meters below the surface in a sealed borehole would provide long-term security and safeguards due to its depth underground, as well as long-term radiological safety, due to its isolation in a stable geological formation. This project supports the nuclear security and safeguards initiatives of the Science and Technology Working Group of the NNSA/IAEC Memorandum of Understanding (MOU) and addresses the Topic Area V objective and associated goals. The goals for Topic Area V are: (1) Assess the suitability of the vadose zone in the Yamin Plain of the northern Negev Desert, Israel as a host location for intermediate-depth borehole disposal of radioactive waste, (2) Define and refine the necessary characterization needs to better understand the regional climate, structure, and stratigraphy, geomechanics, geochemistry, hydrogeology, and seismicity of the stratigraphic sequence from the surface to the water table in the vicinity of the proposed host location for the disposal borehole(s), and (3) Develop a preliminary plan and schedule, including necessary resources and costs, for a borehole disposal concept and robust and transparent pre-closure and post-closure safety assessments. The safety assessments will require iteration with process level models at both site and regional scales. Upon completion, the information collected by this effort will allow the IAEC to make decisions regarding the viability and applicability of an intermediate depth (<500m) borehole for disposal in the vadose zone of the Yamin Plain. This FY21-23 final report is provided in lieu of a workshop report that was originally planned for delivery in January, 2024. Due to the conflict in Israel and associated delays, the workshop has been delayed to April 2024. The workshop will be held at LLNL but offsite and will switch to hybrid if travel restrictions remain in place. The associated workshop report will be provided as part of a new FY24-26 LCP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

An Online Prototype Toolset for Predicting and Optimizing P&T Performance (FY23 Status Report)

A new web-based toolset is being developed to support ongoing remediation optimization efforts and implementation of an adaptive site management strategy for the 200 West Area Pump-and-Treat (P&T) system at the Hanford Site. This toolset, comprising the well performance index tool and the well optimization pre-screening tool, will offer a user-friendly interface to predict and optimize the P&T well network’s performance at a preliminary level. Efforts in fiscal year (FY) 2023 focused on three main components: updating the existing deep learning model for predicting P&T performance, designing and developing a prototype of a web-based performance index tool, and initiating the conceptual design of the well optimization pre-screening tool. The well performance index tool is based on a pre-trained deep learning model that allows users to select a target contaminant and well screen length, then visualize the predicted performance of potential new wells across the site. The well optimization pre-screening tool includes two separate modules: the pre-computed scenario viewer, which organizes and visualizes offline optimization simulation results, and the quick analysis module, which provides real-time model prediction using user-specified well locations. In FY24, the plan is to add web-based applications to SOCRATES for both the well performance prediction tool and the optimization prescreening tool, with accompanying user and theory guides. These tools are intended to enable an accessible, easily applied, and transparent approach to remedy planning and decision-making.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Task 12 PV Sustainability - Life Cycle Inventories and Life Cycle Assessments of Photovoltaic Systems

Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated impacts in the life cycles of products (i.e., goods and services). One of the major goals of IEA PVPS Task 12 is to provide guidance on assuring consistency, balance, transparency and quality of LCA to enhance the credibility and reliability of the results. The current report presents the latest consensus life cycle inventories among the authors, PV LCA experts in North America, Europe, Asia and Australia. At this time consensus is limited to four technologies for which there are well-established and up-to-date life cycle inventory (LCI) data (mono- and multi-crystalline Si, CdTe, CIGS, as well as one emerging technology (perovskite silicon tandem). LCIs are necessary for LCA and the availability of such data is often the greatest barrier for conducting LCA. The Task 12 LCA experts have put great efforts in gathering and compiling the LCI data presented in this report. These include detailed inputs and outputs during manufacturing of cell, wafer, module, and balance-of-system (i.e., structural and electrical components) that were estimated from actual production and operation facilities. In addition, data are presented to enable analyses of various types of PV installations; these include operational data of rooftop and ground-mount PV systems and country-specific PV-mixes. The LCI datasets presented in this report are the latest that are available to the public describing the status in 2018 for crystalline Si (some manufacturing data from 2011 were not updated), 2015 and 2017-2018 for CdTe, 2010 for CIGS, 2010 for HCPV, and 2017 for perovskite silicon tandem technology.

14 SOLAR ENERGY↗
DOE OSTI2024

Guidelines for Home Energy Professionals: Standard Work Specifications (SWS) Maintenance Charter and Procedures

The SWS were built by industry, for industry, and DOE and NREL facilitated the process to create them. The goal of the SWS maintenance process is to continue the consensus-based engagement to ensure the SWS content remains a relevant resource for promoting industry- accepted practices and maintaining consistency throughout the industry. This SWS Maintenance Charter and Procedures document defines the SWS maintenance process to provide transparency to stakeholders in how the SWS are maintained.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Protective Catalyst Systems on III-V and Si-based Semiconductors for Efficient, Durable Photoelectrochemical Water Splitting Devices

The overall goal of this project was to develop unassisted water splitting devices based on III-V materials, creating pathways to improve performance in terms of efficiency, improve durability, and cost. One major objective is to develop pathways to systems that can ultimately achieve > 20% solar-to-hydrogen (STH) efficiency. Another objective was to develop pathways to high efficiency systems that can operate on-sun for at least 2 weeks. With respect to cost, this research provide new approaches to tandem photoelectrode design and fabrication that one day may allow for costs to reach $200/m 2 . Two distinct water splitting schemes were explored: Scheme 1 aims to develop high efficiency devices with tandem III-V photoabsorbers (e.g. GaInP 2 /GaInAs) with Scheme 2 targeting cost reduction while maintaining high efficiency by growing InGaN on crystalline Si (InGaN/Si). Both schemes were employed to couple with thin film, semi-transparent, catalytic/protection layers containing reduced or zero precious metal content that can enhance durability while maintaining high efficiency and enabling low material costs. Overall the project greatly advanced the technology to developing high performance systems with increased durability, as demonstrated by true on-sun testing through partnership with the National Renewable Energy Laboratory (NREL).

08 HYDROGEN↗