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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Software engineering to sustain a high-performance computing scientific application: QMCPACK

We provide an overview of the software engineering efforts and their impact in QMCPACK, a production-level ab-initio Quantum MonteCarlo open-source code targeting high-performance computing (HPC) systems. Aspects included are: (i) strategic expansion ofcontinuous integration (CI) targeting CPU, using GitHub Actions runners, and graphics processing units (GPU) in pre-exascalesystems, using self-hosted hardware; (ii) incremental reduction of memory leaks using sanitizers, (iii) incorporation of Dockercontainers for CI and reproducibility, and (iv) refactoring efforts to improve maintainability, testing coverage, and memory lifetime management. We quantify the value of these improvements by providing metrics to illustrate the shift towards a predictive, rather than reactive, sustainable maintenance approach. Our goal, in documenting the impact of these efforts on QMCPACK, is to contribute to the body of knowledge on the importance of research software engineering (RSE) for the sustainability of community HPC codes and scientific discovery at scale.

Godoy, William↗
DOE OSTI2026

Polymer Deconstruction and Redesign Strategies for Plastics Recycling

Advancing plastics recycling requires both the selective deconstruction of existing polymers and the design of new materials that enable efficient reuse without loss of performance. This perspective highlights an integrated approach that is rooted in polymer chemistry, catalysis, and process engineering which can enable a circular plastics economy. Here, we outline recent advances in catalytic, solvolytic, and enzymatic pathways for plastic deconstruction, and examine the molecular design principles driving next-generation recyclable-by-design and bio-based polymers. Despite these advances, major knowledge gaps remain in understanding the evolution of polymer morphology and catalyst structure during deconstruction, assessing deconstruction processes with realistic polymers, and offering redesigned polymers with competitive cost and environmental advantage over conventional plastics. United States Department of Energy (U.S. DOE) national laboratories offer unique capabilities to address these challenges through in situ and operando characterization, high-throughput experimentation, environmental studies, technoeconomic and life cycle assessment, scale-up support, and collaboration networks. Advances made in understanding plastic deconstruction mechanisms and structure-property correlations of redesigned polymers inform emerging research directions including autonomous experimentation, real-time feedback-enabled process optimization, and protein engineering for enzymatic depolymerization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Heavy Duty Natural Gas Single Cylinder Research Engine Installation, Commissioning, and Baseline Testing

Natural Gas (NG) Internal Combustion Engines (ICE) are a promising alternative to diesel engines for on-road heavy-duty applications to reduce greenhouse gas and harmful pollutant emissions. NG engines have not been widely adopted due to the lower thermal efficiency compared with diesel engine counterparts. To develop the base knowledge required to reach the desired efficiency, a Single Cylinder Engine (SCE) is the most effective platform to acquire reliable and repeatable data. A SCE test cell was developed using a Cummins 15-liter six-cylinder heavy-duty engine block modified to fire one cylinder (2.5-liter displacement). A Woodward Large Engine Control Module (LECM) is integrated to permit implementation of real-time advanced combustion control. Intake and exhaust characteristics, fuel composition, and exhaust gas recirculated substitution rate (EGR) are fully adjustable. A high-speed data acquisition system acquires in-cylinder, intake, and exhaust pressure for combustion analysis. The baseline testing shows reliable and consistent results for engine thermal efficiency, indicated mean effective pressure (IMEP), and coefficient of variance of the IMEP over a wide range of operating conditions while achieving effective control of all engine control and operation variables. This test cell will be used to conduct a research program to develop new and innovative control algorithms and CFD optimized combustion chamber designs, allowing ultra-high efficiency and low emissions for NG ICE heavy-duty on-road applications.

03 NATURAL GAS↗
DOE OSTI2022

IER-517: Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK)

Nuclear criticality experiments are essential to the validation of nuclear data used in simulation software. The quality of nuclear data becomes paramount as simulation software becomes more relied upon for criticality safety studies and designs of nuclear systems. To improve the quality of nuclear data, experimenters can design critical experiments that are sensitive to isotope reaction pairs in materials of interest. The efforts conducted by the Organisation for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA) Working Party on Nuclear Criticality Safety (WPNCS) Subgroup 8: Preservation of Expert Knowledge and Judgement Applied to Criticality Benchmarks (SG8) to categorize benchmarks according to their usefulness for nuclear data validation have been of great importance. Based on the OECD studies benchmark experiments included in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook are concisely used by nuclear data evaluators, criticality safety engineers and others to validate nuclear data and simulation results. A lack of benchmarks sensitive to molybdenum in the (ICSBEP), particularly in the intermediate range, was noted by Los Alamos National Laboratory (LANL), the French Institut de Radioprotection et de Sûreté Nucléaire (IRSN), and Y-12 National Security Site prompting them to submit a joint integral experiment request to the Nuclear Criticality Safety Program (NCSP) in 2019. The request included both HEU and Plutonium systems in order to validate differential nuclear data focusing on the intermediate energy range but also includes thermal and fast configurations. This document represents the preliminary design work for a series of molybdenum integral experiments known as Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A case study of high-temperature polyetherimide film capacitor fabrication

Capacitors, as the basic building block of power electronics and electrical systems, are the major constraint of the increasingly integrated power systems that require new capable polymer dielectric films operating at higher temperatures >125 °C. Despite tremendous research efforts on the lab scale, there remains a considerable barrier and knowledge basis for converting polymeric films to functioning capacitors desired in actual applications. Here, the authors tackled the polyetherimide (PEI) film scale up issues and developed various engineering processes for film de-wrinkling, optimal metallization, static elimination, and capacitor fabrication improvement. The authors discovered various fabrication challenges such as the electrostatic charge, metallization scheme, winding tension, and end electrode disconnects. To fabricate a high yield of PEI capacitor bobbins, it is necessary to utilize static eliminators (radioactive ionizers), moderately thick aluminum metallization (15–30 Ω/sq), and winding tension (60–100 g). It is also effective to evaluate capacitance, dielectric loss, equivalent series resistance, and thermal cycling stability of capacitors. This work sheds some light on converting PEI films and other polymeric films to capacitors on a scale up fabrication effort. The practical learning from film handling to capacitor fabrication in this work provided the necessary knowledge for manufacturing high-temperature polar film capacitors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An Educational Program on Concentrated Solar Power and Heliostats for Power Generation and Industrial Processes

The objective of this project was to design and implement a comprehensive educational and applied research program in Concentrated Solar Thermal Power (CSTP) and heliostat technologies at Northeastern University. In alignment with the U.S. Department of Energy's Heliostat Consortium (HelioCon) goals, the project aimed to expand student and public understanding of CSTP systems while simultaneously contributing to workforce development and the broader decarbonization strategy. A particular emphasis was placed on integrating hands-on student design projects and publicly disseminating educational content relevant to CSTP systems. The project addressed a critical gap in renewable energy education: CSTP and heliostats, despite their importance in utility-scale solar energy, are rarely included in standard mechanical engineering programs. This project established new pathways for students to engage with the topic through the creation of a 4-credit graduate/senior elective course, development of five industry-facing short courses, and the inclusion of CSTP-based capstone design projects. Over two academic years, 36 students across six senior design teams developed and tested technologies such as deformable heliostats, beacon-based tracking systems, and solar-powered pyrolizers for biomass-to-biochar conversion. Concurrently, 30 undergraduate and graduate students were enrolled in the new academic course centered around CSTP principles. To ensure the relevance and accessibility of the short course content, the project team engaged with industry professionals, technical policy stakeholders, and potential course participants through structured surveys and informal consultations. Feedback from 28 respondents guided the structure, length, and delivery format of the courses - resulting in a modular design broken into five workshops. The feedback emphasized the need for flexible, asynchronous delivery and practical case studies, particularly in areas such as heliostat control, thermal storage, and solar fuel production. This engagement helped align the courses with the evolving knowledge demands of the renewable energy workforce and ensured that participants from both technical and policy backgrounds could meaningfully benefit from the material. The research and educational activities advanced the understanding of heliostat control systems, optical performance under misalignment, and thermal system integration in solar-driven pyrolysis applications. Methods and designs explored in this project proved to be both technically effective and economically feasible at the lab scale. Prototypes were constructed using commercially available components and custom-fabricated elements, demonstrating that meaningful performance improvements can be achieved with modest material and fabrication costs, supporting the feasibility of student-led research in this field. The public benefit of this project is twofold. First, it cultivates a pipeline of engineers trained to be familiar with CSTP principles, an essential workforce need identified by the Department of Energy for achieving its 2030 cost and deployment targets. Second, it contributes openly accessible educational materials, course content, and experimental frameworks to the broader community, enabling other institutions to adopt or adapt similar programming. Through outreach activities, curriculum integration, and technical exposure, this project contributes to a more informed and capable renewable energy workforce while supporting innovation in heliostat and CSTP system design. A new technical report is being prepared to document the development of the course and its outcomes, with plans to publish it in the ASME Open Access Journal of Engineering to ensure global accessibility, free of cost.

14 SOLAR ENERGY↗
DOE OSTI2025

MSD CoP Webinar: "Generative agents: A new frontier for representing human actors and their behavior in MSD models"

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Talk #1: Behavioral Generative Agents for Energy Operations Presenter: Dr. Cong Chen (Thayer School of Engineering, Dartmouth College) Abstract: Accurately modeling consumer behavior in energy operations remains challenging due to inherent uncertainties, behavioral complexities, and limited empirical data. This talk introduces a novel approach leveraging generative agents--artificial agents powered by large language models--to realistically simulate customer decision-making in dynamic energy operations. Talk #2: Simulating multiple human perspectives in socio-ecological systems using large language models Presenter: Dr. Yongchao Zeng (Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU) of the Karlsruhe Institute of Technology in Germany) Abstract: Understanding socio-ecological systems requires insights from diverse stakeholder perspectives. This talk describes a novel simulation system called HoPeS (Human-oriented Perspective Shifting). HoPeS enables model users to not only explore simulated socio-ecological systems (SESs) from a third-person observer's perspective but also take any of the simulated stakeholder roles, like playing an RPG game. By shifting multiple perspectives, model users can reflect and integrate the situated knowledge learned through the participatory simulation, approximating a more holistic and less biased understanding of SESs. Moderators: Jim Yoon (MSD CoP Human Systems Modeling Working Group Co-Chair); Stefano Galelli (MSD CoP Using AI to Enhance MSD Research Working Group Co-Chair); Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: November 13th, 2025 from 12-1 PM EST.

Artificial Intelligence↗
DOE OSTI2022

Integral Experiment Final Design for Thermal/Epithermal eXperiments (TEX) Plutonium Additional Mixed Spectrum Configurations

This report presents the final design (CED-2) for three additional mixed-spectra configurations for plutonium Thermal/Epithermal eXperiments (TEX) to target the intermediate energy region (IER-553). The baseline cases of IER-184 (PU-MET-MIXED-002 [2]) spanned the entire fission energy spectrum. Case 3, which had a median fission energy (MFE) of approximately 6E-5 MeV and had a fission fraction of about 42% in the intermediate energy range, resulted in a $k_{eff}$ overestimation of 1.1%. Compared to 749 previous ICSBEP plutonium benchmarks, the baseline cases accurately predicted the experiments in the thermal and fast regions where the majority of benchmarks inhabit. The benchmarks in the intermediate energy region to date are sparse and overestimate $k_{eff}$ with an average C/E between 1.02 and 1.03. The additional proposed configurations span the whole of the intermediate energy region. The experimental design utilizes the plutonium/aluminum metal alloy Zero Power Physics Reactor (ZPPR) Plutonium-Aluminum No-Nickel (PANN) plates with varying polyethylene moderator thicknesses to span the intermediate fission energy region. Each of the cases have varying fractions of thermal, intermediate, and fast fissions. The designs were chosen to maximize the intermediate energy fraction. The experiment will take place on the universal critical assembly machine, Planet. The layers will be split as equally as possible between the lower platen and the upper stationary platform of Planet. The upper half of the experimental configuration will also have an upper reflector of polyethylene of specified thicknesses to achieve criticality when the lower platen is raised fully. The previous IER-184 configurations, specifically Case 3, were used to determine the configurations for the additional experiments and neutronics calculations were used to fine-tune the configurations to ensure criticality. The quadrature sum uncertainty in Δ$k_{eff}$ for Case 3 in PU-MET-MIXED-002 was found to be 0.00219. Section 3.8 gives a detailed description of the uncertainties calculated. The additional configurations, which are based directly on Case 3, are expected to have similar uncertainties. However, it is possible to reduce the overall uncertainty of Δ$k_{eff}$ for the additional configurations using the knowledge obtained from the calculations in the benchmark.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A Systems Engineering Approach to Accident Response Planning.

This paper explores the Systems Engineering structure, strategies and tools for real world scenarios involving work with accident response planning. A systems engineering approach must be taken by the technical teams to prepare for a successful response and design the technical systems in support of the operations. The scope of this project is focused on laying out the foundation of the systems engineering approach taken to help the teams develop an accident response strategy and identify new engineering designs in support of these operations for the black box systems. This Masters project involved several interdisciplinary teams & stakeholders. Identifying the proper tools to use was key to addressing the big picture needs of the multiple stakeholders. The integrated project work primarily took place over the course of eight weeks via integrated team meetings. Other work in support of this project was conducted off-line as needed by the project lead. Details on the prospective timeline, milestones, key dates and work scope can be referenced in this paper. Key systems engineering methodologies and tools used in support of this project included but is not limited to: Market Surveys and Interviews Project Charter Feasibility Study Swim Lane Diagram Knowledge Management Plan. A full suite of tools and the details regarding the application of these tools and results of this study is provided in this report.

42 ENGINEERING↗
DOE OSTI2024

Geospatial Data Platform for All

Spatiotemporal data has evolved in scale due to augmented use in cross-domain applications. Simultaneously, there is substantial growth in the availability of Geographic Information Systems (GIS) data provided by the United States Geological Survey (USGS) along with other federal, state, county, or local agencies through open-data portals and public access APIs. However, data availability does not equate with accessibility. Large-scale analyses and applications require robust, performant data management with co-location of data storage and computing. The insufficiency of data management infrastructure compels researchers to adopt ad hoc project- specific GIS data storage solutions (e.g., copying data to High-Performance computer file systems). As an ad hoc storage strategy does not scale, it hampers cross-domain analyses causing difficulty in data reuse and utilizing existing code bases. Furthermore, GIS data is complex and requires expertise to analyze and manipulate due to its intricate data structures and data-specific projection transformations. Despite the challenges, we recognize that derived GIS data products, e.g., satellite or LIDAR-based images, can be used in downstream applications such as AI by domain, but non-GIS experts. To address the data needs and overcome the challenges, we are working towards a GIS Data Platform focused on efficient data storage, data discovery and access, and an API to enable common workflows. We propose a knowledge-graph (KG) approach for data discovery, whereby datasets are semantically linked to higher- level constructs such as projects and research areas. The semantic data links enable researchers to explore datasets in a top-down approach by specifying relevant and meaningful terms (assists in finding hidden data). An advantage is that the nodes and edges in a knowledge graph create built-in semantic documentation. Deeper spatiotemporal connections between data sources can be encoded via Graph Neural Networks (GNN) (Zhang et al., 2021). The KG approach can be extended to integrate the data itself in a Virtual KG (VKG). Our work will derive inspiration from large-scale VKG efforts that have been undertaken or are currently underway as part of the OpenStreetMap project (Ding et al., 2021). For DOE Data Days, we share the proposed geospatial data platform hybrid (cloud/on-prem) architecture, our work-to-date on storing, retrieving, and transforming LiDAR and raster data relevant to two important NREL use-cases, including the Renewable Energy Potential (reV) Model, and present our proposal for a KG based data discovery engine.

data platform↗
DOE OSTI2023

Characterization of Quantum Frequency Processors

Frequency-bin qubits possess unique synergies with wavelength-multiplexed lightwave communications, suggesting valuable opportunities for quantum networking with the existing fiber-optic infrastructure. Although the coherent manipulation of frequency-bin states requires highly controllable multi-spectral-mode interference, the quantum frequency processor (QFP) provides a scalable path for gate synthesis leveraging standard telecom components. Here, we summarize the state of the art in experimental QFP characterization. Distinguishing between physically motivated “open box” approaches that treat the QFP as a multiport interferometer, and “black box” approaches that view the QFP as a general quantum operation, we highlight the assumptions and results of multiple techniques, including quantum process tomography of a tunable beamsplitter—to our knowledge the first full process tomography of any frequency-bin operation. Our findings should inform future characterization efforts as the QFP increasingly moves beyond proof-of-principle tabletop demonstrations toward integrated devices and deployed quantum networking experiments.

42 ENGINEERING↗
DOE OSTI2020

Integrated dispersion compensated mode-locked quantum dot laser

Quantum dot lasers are excellent on-chip light sources, offering high defect tolerance, low threshold, low temperature variation, and high feedback insensitivity. Yet a monolithic integration technique combining epitaxial quantum dot lasers with passive waveguides has not been demonstrated and is needed for complex photonic integrated circuits. We present here, for the first time to our knowledge, a monolithc offset quantum dot integration platform that permits formation of a laser cavity utilizing both the robust quantum dot active region and the versatility of passive GaAs waveguide structures. This platform is substrate agnostic and therefore compatible with the quantum dot lasers directly grown on Si. As an illustration of the potential of this platform, we designed and fabricated a 20 GHz mode-locked laser with a dispersion-engineered on-chip waveguide mirror. Due to the dispersion compensation effect of the waveguide mirror, the pulse width of the mode-locked laser is reduced by a factor of 2.8.

Zhang, Zeyu (ORCID:0000000271576272)↗
DOE OSTI2025

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Enhancing Cloud Cybersecurity: Prescriptive Controls for Operational Technology

This whitepaper provides strategic insights and recommendations into security cloud-based solutions for electric utilities, encompassing operational technology (OT), virtual power plants (VPP), distributed energy resources (DERs), applications, networks, and data storage as they transition to and leverage cloud infrastructure through managed service providers (MSPs) and cloud service providers (CSPs). Principles derived from established frameworks serve as a foundation for best practices across cybersecurity projects and remove the constraints of settling on a single framework. For organizations that prefer not to integrate a specific framework altogether, elements of the proposed approach could be adopted or tailored to best fit defined requirements and expected functionalities. The Cirrus assessment, a utility cloud feasibility tool, and the roadmap it provides serve as a precursor to this paper, which seeks to be a valuable resource for defining next steps following cloud technology integration feasibility appraisal. With its comprehensive approach to adoption, the Cirrus framework offers strategic guidance on responsibly preparing for or deploying a utility cloud solution. The previously published whitepaper, “Use Case-Informed Framework for Utility Cloud Migration,” details the guiding strategy, research, and deployment of cloud solutions within electric and interconnected grid systems. Before implementing the controls suggested in this document, it is recommended that stakeholders complete Cirrus's cloud integration assessment and pair the results with their unique cybersecurity controls to form a comprehensive cloud-based utility cybersecurity plan. The Cirrus outcome will consider a series of future architectures for the grid before and after the energy transition and evaluate the arguments for and against cloud applications for each electric and interconnected grid layer. This document is a companion to the original whitepaper, "Use Case-Informed Framework for Utility Cloud Migration" to further identify and recommend security controls based on Cirrus’s cloud integration assessment output. The following whitepaper outlines the cybersecurity controls that secure cloud-service models pertinent to the electric sector using the predefined categories identify, protect, detect, and respond and recover. The objective is to outline prescriptive security controls based on the type of architecture and data stored in the cloud. The focus includes dissecting the shared responsibility model and elucidating what on-premises Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) entail. A pivotal consideration in this context is allocating responsibility for foundational cybersecurity aspects—having used Cirrus for the cloud integration assessment. The ensuing controls detailed herein also represent a checklist of controls necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and strategic foresight in a safe and responsible manner.

42 ENGINEERING↗
DOE OSTI2020

A Systems Engineering Approach to Accident Response Planning

This paper explores the Systems Engineering structure, strategies and tools for real world scenarios involving work with accident response groups. A systems engineering approach must be taken by the technical teams to prepare for a successful response and design the technical systems in support of the operations. The scope of this project is focused on laying out the foundation of the systems engineering approach taken to help the teams develop an accident response strategy and identify new engineering designs in support of these operations for the black box systems. This Master’s project involves several interdisciplinary teams & stakeholders across different areas. Identifying the proper tools to use is key to addressing the big picture needs of the multiple stakeholders. This project explores some of the key tools used by the integrated team. The integrated project work will primarily take place over the course of 8 weeks via integrated team meetings. Other work in support of this project will take place off-line as needed by the project lead. Details on the prospective timeline, milestones, key dates and work scope can be referenced in other sections of this paper. Key systems engineering methodologies and tools used thus far in support of this project includes: 1) Market Surveys and Interviews, 2) Project Charter, 3) Feasibility Study, 4) Swim Lane Diagram, and 5) Knowledge Management Plan.

42 ENGINEERING↗
DOE OSTI2020

The role of peer review and science for advancing public understanding

We live in a time of rapid change. The Covid-19 pandemic has united the world to understand and develop solutions to protect the health and wellbeing of society. At the same time, access to information on the internet and social media has exploded. People are exposed to information with many claims. Some of the information is relevant and accurate. A significant fraction may be inaccurate, biased, and potentially dangerous. With Covid-19, the information might point to cures that are toxic or risks that are not relevant. The scientific community has developed a process to develop and convey knowledge. The validation of results and their interpretation is critical to advancing knowledge. The core of the scientific process is based on developing a hypothesis-driven concept, designing and executing an experimental approach to prove or disprove the hypothesis, conducting a statistical analysis of the results to confirm their validity, and interpreting their meaning and impact. When their work is completed the scientist prepares to publish the work. Publication requires peer review. Hypotheses, experimental approaches, results, and interpretation of results are independently and anonymously reviewed by a scientific peer. The reviewers are selected based on their expertise in the field. The peer review process is essential for the integrity of the scientific process. Without a robust scientific process, society cannot discriminate between validated results and interpretations and biased, inaccurate, and potentially dangerous conjecture. With inaccurate science society and policy makers may make poor decisions that could hurt people and the world around them. While scientists should not censor information available to the public, scientists have a responsibility to inform the public. We must articulate what the scientific process is and why it is essential when considering the validity of information. Scientist are responsible for pointing out when public information has not been vetted through a scientific process and therefore cannot be considered conclusive. Scientists are responsible for highlighting information that has been generated and vetted with the scientific process. Over time, our goal is for the public to value the scientific process based on peer review. The public could become enlightened to the necessity for peer review to support decisions and action. Scientists need to contribute to advancing public knowledge. When invited to serve as a peer reviewer, scientists have a responsibility to contribute to the process. We all are extremely busy making peer review a distraction. While peer review does not directly benefit our own work and career, it benefits our chosen field of science. This is very important for the research area that our journal, Water-Energy Nexus, is focusing on. We cover the convergence of science and technology integrating across large spatial ranges (micro to global) in environmental pollution and the balance of remediation issues with energy use. Water-Energy Nexus wants to provide scientists with a platform for scientific debate and discussion on this rich and complicated topic. With the manuscripts submitted to WEN cover integrated research topics across a broad range of subjects from environment sciences through energy engineering, the role of peer review is essential. Peer review on a new submission to WEN should not be biased towards a specific science field. It should be done considering the complex nature of issues in the water-energy nexus. Scientists need to contribute to the public dialog. To accomplish these goals, we need to be honest, accurate, articulate, and use understandable language. The impact of WEN is very diverse affecting society in many ways. The scientific audience for WEN is diverse and readers may not fully understand the content of the papers outside their research expertise. Therefore, scientists, especially those who want to contribute to WEN, should work with communications specialists to convey message to benefit society. The audience includes the general public and researchers outside the author’s core specialty. While the peer-reviewed journal article is the cornerstone of our careers and critical for advancing scientific knowledge, a general interest story could benefit society even more. The author cannot lose sight that our work has two audiences, the science community, and more importantly, our family, friends, neighbors, and policy makers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Low-Power Characterization and Integration of Carbon Black Resistive Ink for Aerosol Jet-Printed RF Components

Aerosol jet printing (AJP) is gaining attention in additive manufacturing research, especially in the discipline of microwave engineering. Currently, no reliable AJP method exists to fabricate resistors that are both electrically small and with a resistance compatible with waveguide impedances for use in microwave components. In this work, the commercially available Metalon JR-038 is characterized and used to fabricate a resistor that is 100 μ m long by 250 μ m wide for the first time to the best of our knowledge. Furthermore, this resistor was then used to fabricate a Ka-band Wilkinson power divider using only the AJP process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

ML-ACCEPT: Machine-Learning-enhanced Automated Circuit Configuration and Evaluation of Power Converters

This project, ML-ACCEPT, took a significant step toward achieving the first objective of the DIFFERENTIATE program: to help engineers to more rapidly and cost-effectively consider a wider range of more novel concepts before selecting an engineering-optimal architecture for high-fidelity detailed design and evaluation. Compared to existing methods, the ML-ACCEPT project investigated innovative technologies to make the design of power converters more cost-effective and time-efficient by i) integrating recent breakthroughs in ML, power electronics, simulation software, and optimization to research, develop, and developed a suite of ML-enhanced hypothesis generation tools for power converter design; and ii) facilitating the integration of the proposed software tools into existing power-converter design work-flows. Some existing tools for power-converter design have a certain level of intelligence to aid the design process, but to our knowledge none of them has ML-enhanced capability of automating the electrical circuit design process by selecting, configuring, and tailoring the individual components that enable available resources (e.g., high-voltage DC power) to be converted to the desired output (e.g., lower-voltage DC power with a desired voltage ripple), subject to application-specific (e.g., plasma generation and automotive applications) thermal and packaging considerations. The state-of-the-art circuit design of power converters is still heavily reliant on human experts to select the optimal topology and search for design parameters with human’s experience and intuitions, which can be very time-consuming, inefficient, and labor intensive. The team is composed of University of Michigan-Dearborn (UM-Dearborn), Lawrence Livermore National Laboratory (LLNL), Oak Ridge National Laboratory (ORNL), Modelon Inc., and lighthouse customers.

42 ENGINEERING↗