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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 OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

FOS: Computer and information sciences↗
DOE OSTI2026

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

University Coalition for Fossil Fuel Energy Research

Following a nationwide open competition, the University Coalition for Fossil Energy Research (UCFER) was established in October 2015 through a cooperative agreement between Penn State and the Department of Energy (DOE) National Energy Technology Laboratory (NETL). Penn State lead UCFER with the objective of advancing basic and applied research for clean and low-carbon energy based on fossil fuels in support of the DOE’s mission. UCFER focused on research that improves the efficiency of production and use of fossil energy resources, while minimizing the environmental impacts and reducing greenhouse gas emissions. Penn State lead a team of nine universities (Massachusetts Institute of Technology, The Pennsylvania State University, Princeton University, Texas A&M University, University of Kentucky, University of Southern California, The University of Tulsa, University of Wyoming, and Virginia Polytechnic and State University) during the competition stage, adding seven more universities in 2017 (Carnegie Mellon University, Louisiana State University, The Ohio State University, University of North Dakota, University of Pittsburgh, University of Utah, and West Virginia University). This Coalition exhibited a wide geographical distribution across the U.S. bringing a wide variety of fossil energy expertise. This national university alliance was a major collaborative effort with NETL to address specific topics of R&D in NETL’s mission area, which involved one or more of NETL’s five core competencies (Geologic and Environmental Systems, Materials Engineering and Manufacturing, Energy Conversion Engineering, Systems Engineering and Analysis, and Computational Science and Engineering). The first five to six months of the project was the definitization stage. During this period, Penn State worked closely with NETL to finalize the Coalition organizational structure and By- Laws, prepare a statement of substantial involvement and a statement of project objectives, and develop operations and membership plans. A major component of this stage included preparing an execution plan to solicit research, evaluate proposals, recommend selected projects to NETL, and award projects. In addition, a plan was prepared to monitor projects, review projects, disseminate knowledge from research projects and develop an online system for Coalition research portfolio management. This included developing a website and several databases. The first of six rounds of solicitations started in mid-2016. Projects from the sixth solicitation started February 1, 2021, and ended January 31, 2023. Projects that were selected represented twelve technology lines. Approximately $16.6 million in funding was available for the six solicitations. Most of the funding was provided by DOE, Office of Fossil Energy (DOEFE) with the DOE Fuel Cells Technologies Office (DOE-FCTO) providing funding for a few projects. Coalition universities submitted 259 proposals in response to the solicitations, requesting approximately $67.0 million in funding, and forty-three projects were selected. However, one project withdrew after the principal investigator left the university. The management of the Coalition projects was a major activity by Penn State. Managing the Coalition projects consisted of monitoring the projects, reviewing the projects through annual technical review meetings, disseminating knowledge from the research projects, and developing an online system for Coalition research portfolio management. Penn State’s OMT monitored projects to ensure that all milestones (technical, schedule, budget) were met, expenditures were allowable, cost share (when applicable) were reported, and all technical reports were submitted. The OMT also posted the technical reports electronically on a secure members-only website for access and review by the Coalition members. Disseminating knowledge from the research projects was done through a website, newsletters, various meetings, conferences, journal articles, publicity/press releases, and project summaries that were prepared after each project was completed. Penn State kept NETL apprised of UCFER progress through quarterly reports (thirtyone were submitted by Penn State), verbal and written communications, yearly updates at the annual technical review meetings, and cost accrual reports. The UCFER project had a significant impacty. The UCFER program established the first national university alliance in fossil energy research with a major collaboration effort with DOE NETL that addressed specific topics in NETL’s research and development mission areas. It generated inter-university collaborations, which was another program interest. Twenty-two out of 259 proposals contained collaborations (≈8.5%) and three of forty-two funded projects involved inter-university collaborations (≈7.0%). The forty-two funded projects provided support at fourteen universities involving 269 personnel. Research was conducted by 106 faculty, 115 graduate and undergraduate students, forty-six research staff and post-doctoral scholars, and two visiting scholars. Students and post-doctoral scholars were also on-site at NETL through CRADAs. In addition, non-Coalition participants included six universities and sixteen companies and national laboratories. The non-Coalition participants were involved as subcontractors, providers of cost share, performed unpaid consultation and sample analysis, served as advisory board members, or were providers of samples and materials for testing. UCFER also produced visibility in that fifty-six refereed journal articles were published, fifty-seven conference papers and twenty-three posters were prepared, 190 presentations were given, eight patent applications were filed, two books/book chapters were written, and ten software codes were developed. Collaboration between NETL and the individual projects was a major requirement for all funded projects. This included NETL staff time to support collaboration, consultation, technical guidance, sample preparation and analysis, internships at NETL, on-site testing and equipment usage by Coalition participants at NETL, co-mentoring students, and coauthoring journal articles and conference papers. Collaboration was impacted by COVID-19 in that not all on-site activities could be performed. NETL personnel were coauthors on eight of the conference papers (fourteen percent of the conference papers that were prepared) and seventeen of the journal articles (thirty percent of the journal articles that were prepared). A website was developed for an online proposal solicitation and review process and to provide exposure to UCFER. A website analysis highlighted the large amount of member and general public interest in UCFER by interpreting access statistics from March 2016 through June 2023. Visitors to the site originated from many different organizations, businesses, and countries. The website provided a means to disseminate information to both the general public and the UCFER members and was successfully used for outreach activities. In addition, NETL required that RFP release, proposal submission, and proposal reviews all be performed online. Penn State successfully developed these capabilities in a secure section of the website, which were used throughout the UCFER project. It is recognized that each project had its technical successes. In addition, highlighted successes were compiled and summarized from the research projects. Information was requested from the PIs of completed projects. In addition, Penn State’s Operations Management Team reviewed subcontract reports to identify project successes. Examples of information requested from PIs included (not all-inclusive): new projects that have been funded as a result of UCFER funding; new commercial products; establishment of a new center; new patent; new software; best paper awards; highly-cited work; and graduate student successes. A total of forty-eight highlighted successes were reported.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1993

Atmospheric breakup of a small comet in the Earth's atmosphere

The aerodynamic stresses can lead to the deformation and even to destruction of the meteoroids during their flight through the atmosphere. The pressure at the blunt nose of the cosmic body moving at very high speed through the dense layers of the atmosphere may be much larger than the tensile or the compressive strength of the body. So the usage of the hydrodynamics theory is validated. The estimates show that the transverse velocity of the substance of the body U is of the order of (rho(sub a)/rho(sub o))(sup 1/2)V where V is the velocity of the body and rho(sub o) is its density, rho(sub a) is the density of the atmosphere. The separation of the fragments is larger than the diameter of the body D if D is less than D(sub c) = 2H(square root of rho(sub a)/rho(sub o)), where H is the characteristic scale of the atmosphere. For an icy body one obtains U = 1/30(V) and critical diameter D(sub C) = 500 m. The process of the disintegration of the body is still not fully understood and so one can use the numerical simulation to investigate it. Such simulations where conducted for the Venusian atmosphere and the gaseous equation of state of the body was used. For the Earth atmosphere for the velocity V = 50 km/s the pressure at the blunt nose of the body is 25 kbar, and is of the order of bulk modulus of compressibility of the water or ice. The realistic EOS of water in tabular form was used. It was assumed that the initial shape of the body was spherical and the initial diameter D(sub o) of the body is 200 m and so it is smaller than the critical diameter D(sub C). The initial kinetic energy of the icy body is equivalent to the energy of the explosion 1200 Mt of TNT. The results of the simulation of the deformation of the body during its vertical flight through the atmosphere and during its impact into the ocean are presented.

Teterev, A. V.↗
DOE OSTI2022

Efficient light-trapping in ultrathin GaAs solar cells using quasi-random photonic crystals

Ultrathin solar cells reduce material usage and allow the use of lower-quality materials thanks to their one order of magnitude smaller thickness than their conventional counterparts. However, efficient photonic light-trapping is required to harvest the incident light efficiently for an otherwise insufficient absorber thickness. Quasi-random photonic crystals are predicted to have high efficient light-trapping while being more robust under angle and thickness variations than simple photonic crystals. In this study, we experimentally demonstrate a light-trapping solution based on quasi-random photonic crystals fabricated by polymer blend lithography. We control the average lattice parameter by modifying the spin-coating speed. We demonstrate an ultrathin GaAs cell of 260 nm with a rear quasi-random pattern with submicron features, and a J sc = 26.4 mA/cm 2 and an efficiency of 22.35% under the global solar spectrum.

14 SOLAR ENERGY↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2025

Exploring the Structure–Function Relationship in Iridium–Cobalt Oxide Catalyst for Oxygen Evolution Reaction across Different Electrolyte Media

Renewable hydrogen generation from water electrolysis offers a viable path to decarbonization if the costs can be reduced. The iridium-based anode catalyst is one of the most expensive components in electrolyzers. We propose reducing iridium usage by substituting Ir with Co, a more affordable metal, in the mixed oxide phase to enhance the catalytic activity while minimizing Ir consumption. A modified surfactant-assisted Adams fusion synthesis technique was developed as a scalable method for producing IrCo oxide nanoparticles. The synthesized material outperforms the commercial baseline, iridium oxide with carbon (IrOx_C), in both acidic and alkaline media. Acid etching (IrCo_ae) further enhances activity by selectively removing Co to expose more active sites. IrCo_ae achieved a significantly lower overpotential at 10 mA/cm 2 compared to IrOx_C, with reductions of approximately 18% under acidic conditions and 14% under alkaline conditions. This work demonstrates that the proposed synthesis method enables efficient Ir utilization and can be adapted to enhance catalyst stability for renewable hydrogen production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

1-Watt Radioisotope Power System for Small Spacecraft

A variety of mission concepts have been studied by NASA and the U. S. Department of Energy that would utilize low power Radioisotope Power Systems (RPS) for small probes, landers, rovers, and communication repeaters. These missions would contain science measuring instruments that could be distributed across planetary surfaces for operation in temporarily or permanently shadowed regions. High efficiency dynamic RPS could be mission enabling for science measurements on the moon, such as collecting real-time, event-based, or cumulative space radiation measurements including primary galactic cosmic rays (GCR), solar particle events (SPE), and secondary particles liberated during atmospheric and/or surface reactions. Small RPS would use fractional versions of the General Purpose Heat Source (GPHS) or Light Weight Radioisotope Heater Units (LWRHU), to heat the power conversion technologies. Capable of three to four times higher conversion efficiency than static technologies, dynamic RPS would provide an equal amount of power using less fuel or more power using an equal amount of fuel. Providing spacecraft with more power could decrease duty cycling of basic functions and increase the quality and abundance of science data. Low power Stirling convertors are being developed at NASA Glenn Research Center (GRC) to provide future micro spacecraft with electrical power by converting heat from one or more LWRHUs. An initial concept would convert eight Watts of heat to one Watt of electrical power output for science instruments and communication. The initial design, called Small Stirling Technology Exploration Power (smallSTEP), is 11 cm diameter X 32 cm long, weighs around 3 kg, and could be used to charge batteries or capacitors for higher power burst usage. Development of the 1-watt RPS includes maturation of a Stirling engine and linear alternator, an electronics controller, and an evacuated metal foil insulation package. Test hardware and facilities are being prepared for initial demonstration of the subassemblies in a laboratory environment.

Wilson, Scott↗
DOE OSTI2021

Landfilled coal ash for carbon dioxide capture and its potential as a geopolymer binder for hazardous waste remediation

In this report, the legacy of global fossil fuel usage is not just the increase in global warming due to CO 2 production, but also the billions of tons of toxic coal ash disposed in landfills. This investigation evaluates the merits of using high-calcium landfilled coal fly ash of different disposal durations and granulated blast furnace (GBF) slag as primary raw materials for production of a new class of geopolymer binder. Processing of landfilled coal fly ash, GBF slag and supplementary raw materials into a geopolymer binder was accomplished by a simple, scalable milling process in the absence of heating under a carbon dioxide environment. The resultant geopolymer cement binders were tested for carbon dioxide uptake, compressive strength, and heavy metal stabilization. The geopolymer binder demonstrated a desired balance of carbon dioxide uptake, strength and safety. These results also indicate that the performance of the geopolymer binder depends on the landfill disposal age of the coal fly ash.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2020

US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory's (ORNL's) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high performance computing (HPC) needs; and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2019 was a big year as OLCF staff ran five world-class resources (the leadershipclass computers Titan and Summit, the large analysis cluster called Eos, and the massive parallel filesystems called Atlas and Alpine)) and also began power and cooling upgrades for a 2021 exascale system called Frontier. While continuing exceptional operation of Titan, Eos, and Rhea, the OLCF released the Summit supercomputer for production on January 1, 2019. Summit debuted as the most capable and efficient system in its class and has been recognized as the most powerful system in the world for its performance on both the high performance linpack (HPL) and conjugate gradient (HPCG) benchmark applications since June 2018 according to TOP500. Summit represents the culmination of a multiyear effort between the OLCF, IBM, NVIDIA, and Mellanox to deliver a system that is unmatched for modeling, simulation, data analysis, and learning. To hit the ground running with science-ready applications on day one, application teams worked closely with the OLCF through the Center for Accelerated Application Readiness (CAAR) program for years in advance of the Summit deployment. CY 2019 was filled with outstanding results and accomplishments: a very high rating from users on overall satisfaction for the sixth year in a row; a tremendous amount of core-hours delivered to researchers from two leadership-class systems; and success in delivering on the allocation split of roughly 60%, 30%, and 10% of core-hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director's Discretionary (DD) programs, respectively (see Operational Performance section). These accomplishments, coupled with the high utilization rates (overall and capability usage), represent the fulfillment of the promise of both leadership-class machines: efficient facilitation of leadership-class computational applications. Table ES.1 presents a summary of the 2019 OLCF metric targets and the associated results. More information can be found in the Operational Performance section for each OLCF resource. The scientific accomplishments of OLCF users are a strong indication of long-term operational success, with publications this year in such notable journals and publications as Nature, Nature Physics, Nature Plants, Physical Review X, Journal of the American Physical Society, Cell, Nano Letters, and Trends in Biotechnology. Crucial domain-specific discoveries facilitated by resources at the OLCF are described in the High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility (OAR) Strategic Results section. For example, researchers used Summit to pinpoint and understand the production of proteins from genetic information, including mutations and the functional expression of disease (Section 8.2).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Screen printable copper pastes for silicon solar cells

The current work demonstrates the successful metallization of a PERC silicon solar cell with screen-printable copper (Cu) paste that is sintered at elevated temperature in air atmosphere. The existing state of the art in Silicon (Si) solar cell metallization is silver (Ag) paste; Cu cost is 1/100th the cost of Ag and has a comparable conductivity. However, Cu undergoes rapid oxidation at elevated temperatures and the high diffusion of Cu into Si restricts its usage in the metallization of silicon solar cells. In this paper, a Cu paste containing a proprietary mixture of antioxidant additives and diffusion inhibitors was used to make front gridlines on PERC cells. The Cu-printed cells were fired in an IR belt furnace with a peak temperature of 576°C in air atmosphere. The solar cells discussed here reached an efficiency of 19%, which is 88% of the efficiency measured for a commercial Ag-printed cell. The working devices were further characterized using STEM, EDX, ToF-SIMS and long-term suns-V oc studies demonstrating an absence of Cu diffusion. Furthermore, thermally stressing the Cu-printed solar cells yielded a reduction of less than 1.9% of the initial pseudo fill factor (pFF) after 1000 hours at 200°C. Here, the shunt resistance of cells monitored over 3 years remained within 2.5% of its initial value, which demonstrates the effectiveness of the Cu diffusion barrier.

14 SOLAR ENERGY↗
DOE OSTI2024

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗
DOE OSTI2025

Fundamental Studies of Soiling and Cementation of PV Cover Glass Materials: Addressing Reliability with Advanced X-ray Scattering/Spectroscopy and First Principles Modeling (Final Technical Report)

Accumulation of soils and other particulate matter on the front cover glass of solar photovoltaic (PV) modules results in transmission losses that detrimentally affect the power output of PV installations. The conventional solution to this problem is manual abrasive scrubbing of modules, which entails significant water usage and manpower. To further combat this issue, there is a concerted effort within the PV industry to develop anti-soiling (AS) coatings to mitigate power losses due to soiling of PV modules, which can exceed 35% in some cases. However, relatively little is known about the fundamental physical and chemical mechanisms that enable anti-soiling behavior. In this project, a combination of advanced X-ray analysis tools and first principles computational modeling has employed to understand the physical and chemical interactions between environmental soils and PV cover glass materials. The specific objectives were: 1) investigate soiling interactions and cementation behavior of relevant PV materials, including bare glass, conventional antireflective (AR) coatings, and a commercial AS coating, using a library of representative particulate soils, and 2) utilize first principles computational spectroscopy modeling to interpret the experimental X-ray spectroscopy measurements and determine the detailed surface chemistry changes that occur on these surfaces in the presence of soiling and cementation.

14 SOLAR ENERGY↗
DOE OSTI2023

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below $5\%$ MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗
DOE OSTI2022

Ames National Laboratory Annual Site Environmental Report for CY2021

The primary purpose of this report is to summarize the performance of Ames National Laboratory’s environmental programs, present highlights of significant environmental activities, and confirm compliance with environmental regulations and requirements for calendar year 2021. This report is a working requirement of Department of Energy Order 231.1B, Environment, Safety and Health Reporting. It includes descriptions of the Laboratory’s site, mission, the status of its compliance with applicable environmental regulations, its planning and activities to maintain compliance, and a comprehensive review of its environmental protection, surveillance and monitoring activities. Ames National Laboratory is located on the campus of Iowa State University (ISU) and occupies 13 buildings owned by the Department of Energy (DOE). See the Laboratory’s Web page for location and Laboratory overview. The Laboratory also leases space in ISU owned buildings. In 2021, the Laboratory accumulated and disposed of hazardous waste under a U.S. Environmental Protection Agency (EPA) issued generator number. All waste was handled according to applicable EPA, State, and local regulations and DOE Orders. The Laboratory operates as a Small Quantity Generator (SQG) of hazardous waste. There were no radiological air emissions or exposures to the general public due to Laboratory activities in 2021 (See U.S. Department of Energy Air Emissions Annual Report in Appendix A.) The Laboratory has an established Environmental Radiological Protection Program (Plan 10200.041) per DOE Order 458.1 requirements. Plans, policies, and procedures are in place to protect the public and the environment against undue risk from radiation associated with DOE radiological activities. As indicated in prior Site Environmental Reports, formal pollution prevention awareness, waste minimization and recycling programs have been in practice since 1990, with improvements implemented most recently in 2017 with Iowa State University’s shift toward single-stream recycling. Included in recycling efforts are items such as batteries, monitors, corrugated cardboard, lamps, miscellaneous electronic office equipment, mixed paper, newsprint, food/beverage containers, and laboratory glassware. Ames National Laboratory also recycles/reuses salvageable metal, used oil, and foamed polystyrene peanuts, and encourages chemical redistribution and sharing among research groups. Ames National Laboratory reported its contractual performance to DOE-Ames Site Office (AMSO) through the Laboratory’s Performance Evaluation Measurement Plan (PEMP), and a performance level of “B+” was achieved in 2021 for Sustain Excellence and Enhance Effectiveness of Integrated Safety, Health, and Environmental Protection As reported in Site Environmental Reports for prior years, the Laboratory’s Environmental Management System (EMS) has been integrated into the Laboratory’s Integrated Safety Management System (ISMS) since 2005. The integration of EMS into Laboratory business practices allows the Laboratory to systematically review, address and respond to environmental impacts. In addition to DOE-identified objectives and targets, the EMS Steering Committee recommends annual environmental goals for the Laboratory. Due to the COVID-19 pandemic and limited onsite work staff, goals of reducing water usage and travel/commuting to promote the reduction of scope 3 greenhouse gases were achieved. All contract deliverables and environmental compliance activities were still met during this time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Vacuum-Free, All-Solution, and All-Air Processed Organic Photovoltaics with over 11% Efficiency and Promoted Stability Using Layer-by-Layer Codoped Polymeric Electrodes

Nonfullerene organic photovoltaics (OPVs) have achieved a breakthrough in pushing the efficiency beyond 15%. Although this sheds light on OPV commercialization, the high cost associated with the scalable device fabrications remains a giant challenge. Herein, a vacuum-free, all-solution and all-air processed OPV is reported that yields 11.12% efficiency with a fill factor of 0.725, due to the usages of high-merit polymeric electrodes and modified active blends. The design principle toward the high-merit electrodes is to induce heavy acid doping into the matrices for a raised carrier concentration and mobility, make a large removal of insulating components in the whole matrices rather than surfaces, and restrain the formation of large-domain aggregates. A unique layer-by-layer doping is developed to enable the polymeric electrodes with record-high trade-offs between optical transmittance and electrical conductivity. Moreover, solvent vapor annealing is proposed to boost device efficiency and it has the advantages of finely adjusting the active blend morphology and raising the electron mobility. The resulting devices are highly efficient and most (≈91%) of the initial efficiency are maintained in 30 day storage. Finally, this work indicates bright future for making cost-effective all-solution processed OPVs in air.

14 SOLAR ENERGY↗
DOE OSTI2023

Implementation of an ICS Ransomware Testbed: Scenarios, Variants, and Evaluation Methods

Ransomware attacks on Industrial Control Systems (ICS) have emerged as a formidable threat to the United States’ critical infrastructure, eliciting grave concerns regarding national security. In March 2023, the FBI Internet Crime Complaint Center (IC3) unveiled its 2022 Internet Crime Report, highlighting a concerning 870 complaints related to ransomware impacting U.S. critical infrastructure. Of the country's 16 critical infrastructure sectors, 14 encountered at least one ransomware attack. Notably, while the Healthcare and Public Health sector suffered the most, reporting 210 attacks, sectors pivotal to ICS networks and governmental organizations were also targeted: the Defense Industrial Base reported 1 attack, Water and Wastewater Systems 3, Chemical 19, Energy 15, Government Facilities 115, and Critical Manufacturing 157. For instance, a ransomware attack on a major chemical company could jeopardize not only its production but also pose environmental risks should systems controlling hazardous materials be compromised. In 2022, three ransomware variants predominantly targeted U.S. critical infrastructure: HIVE, with 87 attacks; ALPHV/BlackCat, with 114; and LOCKBIT, with 149. Several cyber-attacks, such as the MOVEit data breach in May 2023 and the Colonial Pipeline ransomware attack in May 2021, have been so impactful that they commanded national attention. The DarkSide hacking group's assault on the Colonial Pipeline, initiated on May 6th, 2021, stands as one of the most substantial and publicly acknowledged cyber-attacks against U.S. critical infrastructure. The group exploited an exposed Virtual Private Network (VPN) password, paving the way for initial intrusion and subsequent data theft. A mere day later, DarkSide unleashed a ransomware attack that compromised vital accounting and billing systems, prompting an immediate shutdown of the pipeline to mitigate further ransomware proliferation across its network. This crisis spurred a robust response from the U.S. president and regulators, culminating in a national emergency declaration related to the pipeline shutdown on May 9th, 2021. This incident mirrors the 2017 NotPetya ransomware attack that significantly impacted the shipping giant Maersk, highlighting an urgent need for fortified cybersecurity across various industries. Future incidents, akin to the Colonial Pipeline attack, could potentially be mitigated—or entirely averted—should government agencies and private entities scrutinize system vulnerabilities, exploring various ransomware types and entry points. Proactive measures, such as conducting experiments on VPN accounts or auditing passwords to pinpoint duplicate usage across diverse systems and software, might illuminate feasible entry points and vulnerability zones within an organization's systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗