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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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At least 397 records · Page 22

Ionic Liquids for Direct Air Capture of CO 2 using Electric‐Field‐Mediated Moisture Gradient Process (Final Technical Report)

The final report provides executive summary, a list of publications, and information on training graduate students and postdoctoral researchers. We carried out computational and experimental research on understanding molecular-level mechanism of how CO 2 is absorbed in a solution containing ethylene glycol as the solvent and KOH as the salt in the presence of ionic liquids and under the influence of electric field. In doing so, we developed an automated high-throughput method which allowed us to measure the solubility of CO 2 in a large number of ionic liquids, considerably speeding up the CO 2 solubility measurement. We also demonstrated how varying the concentration of ionic liquids in ethylene glycol can result in a maximum in ionic conductivity. Reaction of CO 2 and subsequent release results in a 50% reduction when the process is operated at an ionic liquid-ethylene glycol concentration yielding maximum ionic conductivity amongst all the ionic liquid-ethylene glycol combinations studied as a part of this research. We utilized machine learning models to identify unique ionic liquid-solvent combinations with ionic conductivity much higher than that measured for ionic liquid-ethylene glycol combinations. We demonstrated that the rate of CO 2 reaction with KOH in ethylene glycol can be optimized with the type of ionic liquid and its concentration. Overall, the research led to publication of 10 peer-reviewed research articles and several presentations at national conferences. We are also in the process of developing additional manuscripts based on the research carried out as a part of this project. Two graduate students and two postdoctoral researchers were supported on the funding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Robust Explanations using Diverse Adversarially Trained Ensembles, Multi-Modal Contrastive Learning, and Attribution-based Confidence Metrics

The primary objective of this project is to strengthen the trustworthiness of AI systems by designing algorithms that make their internal decision-making processes more understandable to human users. This involves creating clear, interpretable explanations for AI decisions and developing metrics to assess these explanations' validity and reliability. Significant progress has been achieved through (i) developing symbolic explanations, (ii) generating meaningful interpretive insights, (iii) establishing accuracy and confidence metrics, and (iv) devising methods to evaluate the knowledge boundaries of AI models. To date, the research findings have been shared in peer-reviewed publications, with accompanying scientific and technical information (STI) detailed below.

97 MATHEMATICS AND COMPUTING↗

LDRD FY25 Program Overview

As Lawrence Livermore National Laboratory’s (LLNL’s) Laboratory Directed Research and Development (LDRD) program enters its fifth decade of leading-edge research and development, its impact and importance have never been stronger. The program continues to advance strategic investments in pioneering science, technology, and engineering, ensuring LLNL will be ready to deliver on our mission as it evolves over the coming decades. Investing in LDRD research, and the people who perform this critical work, gives LLNL the ability to sustain our role as a leader in the Department of Energy and National Nuclear Security Administration enterprise. The LDRD program enables high-risk, high-payoff research that anticipates emerging threats and future mission needs. By nurturing the ingenuity of the Lab’s greatest asset, its people, LDRD funding advances not only our research but also grows and nurtures our workforce: engaging future innovators with student mentoring, challenging postdoctoral researchers to apply their skills to support national security, and strengthening the leadership skills of early career staff. This annual report documents how LDRD investments advance LLNL’s science, technology, and engineering across our mission space. To assess LDRD’s impact we track both short and long-term metrics such as peer-reviewed publications, number of students, or professional fellows. In addition to reviewing these metrics, I encourage you to delve deeper into the breadth of science and technology that illustrate the strategic value of this research portfolio. For instance, a recent exploratory research project used advanced manufacturing to construct miniaturized three-dimensional ion traps for a quantum computer with reduced quantum error rates to enable applications that address national security missions and support basic science. Another project has delved into studying detonation by examining deflagration to enhance the safety and security of the nuclear weapons stockpile. LDRD researchers are also deploying AI agents on two of the world’s most powerful supercomputers to automate and accelerate inertial confinement fusion experiments. Other teams are delivering more accurate optical constants to enable improved validation for aluminum to advance atomic and molecular physics models. LDRD-driven discoveries of how metals deform under extreme conditions strengthen our ability to model and design materials for demanding national security environments. National security challenges are increasingly complex and continuously evolving. LDRD focuses our most innovative science and technology on these challenges, ensuring the Laboratory is developing creative, forward-leaning solutions for our nation and the world. The following pages feature highlights of published scientific advances, patents, and honors that stem from LDRD investments. As you read this report, I hope you will understand how these investments position the Laboratory, and our partners, to meet the demands of the decades ahead.

36 MATERIALS SCIENCE↗

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗

Physics of Ultra-High Energy Density Relativistic Plasmas from Ordered Nanostructures

This award funded a four-year program at Colorado State University on the physics of ultra-high energy density plasmas generated by focusing femtosecond, >1021 Wcm-2 laser pulses onto ordered nanowire arrays. We used the ALEPH petawatt-class Ti:Sa laser with its high contrast 400 nm second harmonic beamline to irradiate arrays of Ni and TiO2 nanowires made by template assisted electrodeposition and atomic layer deposition over a wide range of average densities. We met two of the three original project goals: radial ion acceleration via doppler shifted K shell emission, and time and spectrally resolved K shell measurements. The main experimental advance was integrating the Lawrence Livermore National Laboratory (LLNL) TREX ultrafast x-ray streak camera with a suite of spherically bent quartz Bragg crystal spectrometers built using Princeton Plasma Physics Laboratory (PPPL) methodology. This is the first TREX-on-bent-quartz setup fielded at a femtosecond, >1021 Wcm-2 facility. It is now a permanent diagnostic at ALEPH and is offered to the LaserNetUS user community. The program produced three peer reviewed journal articles that acknowledge this award. The platform will continue at the upgraded CSU ATLAS facility, where the ALEPH laser is being upgraded to 2 PW.

Hollinger, Reed [Colorado State University]↗

Integrated Anaerobic Membrane Bioreactor (AnMBR) – electro assisted fermentation platform for total resource recovery from diverse wastewaters

The overall objective of the project was to demonstrate a successful wastewater resource recovery platform comprising an Anaerobic Membrane Bioreactor (AnMBR) to achieve >50% Carbon sequestration efficiency as Volatile Fatty Acids (VFAs) or as methane gas from agricultural (animal feeding operations) wastewater along with the generation of final water exceeding Biological Nutrient Removal (BNR) standards for indirect potable reuse by coupling with constructed wetlands has been successfully accomplished. The AnMBR achieved stable performance over 350 days, removing 80–90% of COD and BOD₅ and recovering methane (0.17±0.07 L CH4/g COD at 66.5±0.03% v/v) at 3-5 LMH flux and 5-9 days HRT with 3-5% w/v total solids. Phosphorus recovery via CaO addition in an 80-L coagulation-flocculation-sedimentation unit ranged from 40.6% to 99.7%, yielding products with 11.4–13.6% P content and citric acid solubility of 32–38.6% P, comparable to rock phosphate mineral. Ammonium adsorption achieved ~94.5% recovery with exchange capacity of 10 – 16 g NH4-N/kg clinoptilolite. The CW polishing step met Kansas discharge standards for BOD5 and TN (<30 and <10 mg /L,) and approached the TP standard (~2.5 – 4 mg P/L). These findings have either already resulted in two peer reviewed publications, two patent applications, and one publication in conference proceedings.

42 ENGINEERING↗

Multi-Scale Modeling and Prototype Development for Electrochemical CO2 Reduction (CRADA Final Report)

In this CRADA project, Lawrence Livermore National Laboratory, Stanford University, SLAC National Laboratory, and TotalEnergies collaboratively executed a multidisciplinary investigation of electrochemical reduction of CO2 to produce sustainable fuels and chemicals. Overall, the project led to an increased understanding of the fundamental processes involved in CO2 electrolysis, from the atomistic scale to the full electrolyzer device scale, ultimately leading to design guidelines for CO2 electrolyzers that will help in their future commercialization. As the model systems, Ag- and Cu-based catalysts were investigated in various forms depending on the electrochemical platform that was utilized to study the activity, selectivity, and durability towards electrochemical CO2 reduction. By employing experimental, theoretical, and computational techniques, the project team experimentally validated multi-physics models, evaluated the experimental levers that lead to increased electrolyzer reaction selectivity and energy efficiency, and used computational optimization to design higher performance electrodes. The learnings of this project were extensively documented in publicly available peer-reviewed journal publications and conference presentations, which serve as a foundation for further work to build from.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Open-Air Manufacturing of Efficient Large-Area Perovskite Solar Cells to Meet Stability and Cost Targets

This SETO-funded project (DE-EE0009516) developed a fully open-air manufacturing pathway for perovskite solar cells and modules, eliminating vacuum-based processing steps while improving device stability. Open-air ultrasonic spray deposition, solution combustion synthesis, rapid thermal processing, and atmospheric plasma curing were developed and optimized for all functional device layers — perovskite absorber, hole transport layers (HTLs), electron transport layers (ETLs), transparent conducting oxides (TCOs), and rear electrodes — without reliance on vacuum. Sprayed organic ETLs preserved perovskite crystal structure and enabled power conversion efficiencies exceeding 20%, and open-air processed TCOs and rear electrodes achieved optoelectronic performance comparable to sputtered alternatives at substantially lower manufacturing cost. Device stability was assessed through accelerated aging protocols aligned with IEC and ISOS standards, combined with high-throughput optical diagnostics that identified key degradation mechanisms and antagonistic interactions among heat, humidity, and illumination stressors. A comprehensive technoeconomic analysis quantified the cost and throughput advantages of open-air manufacturing over conventional vacuum-based processes, identifying vacuum deposition as the dominant cost driver and demonstrating a clear pathway toward the $0.02/kWh target. The project produced five peer-reviewed journal publications, eleven conference presentations, two patents/applications, and five Ph.D. dissertations.

14 SOLAR ENERGY↗

Waste Glass Property Database and Data Qualification Plan

The U.S. Department of Energy vitrification facilities currently employ glass property-composition models to ensure processability of waste streams and acceptability of the final glass products. The efficiency (e.g., process flexibility, reduced down time, and reduced cost) of waste vitrification is directly tied to the size of the waste processing envelope. To increase the size of the processing envelope, a larger database was developed. The database will improve the prediction accuracy of glass properties, leading to higher waste loadings, higher waste throughput, broader process flexibility, and reduced mission life. Some of the data in this expanded database has insufficient quality assurance (QA) rigor for use in nuclear facility operation and glass qualification. A plan was developed to qualify high-value data under the appropriate QA rigor for use at the Hanford Waste Treatment and Immobilization Plant’s High-Level Waste (HLW) Facility. This qualification plan first compares the data coverage over the composition region of interest to Hanford HLW by property. Those studies that significantly improve the data coverage in the Hanford HLW glass composition region were prioritized for qualification activities. Qualification methods including QA equivalence, peer review, data corroboration, and confirmatory testing have been assigned to each high-priority study.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

FullWave — A Full Wave Parallel Code for Modeling RF Fields in Hot Tokamak Plasma

FullWave is a computer code that simulates how radio-frequency (RF) waves travel and deposit energy in the hot plasma inside a fusion reactor. RF waves are used to heat the plasma and drive electrical current, which is essential for sustaining fusion reactions. The code uses a new algorithm that can handle much finer spatial detail than previous codes — more than 100 times finer — while running efficiently on national supercomputers. It incorporates a detailed physics model that captures subtle kinetic effects important for accurate prediction of wave behavior. Under this project, FullWave was extended to cover multiple RF frequency ranges relevant to present and future tokamaks, and validated against experimental parameters from the DIII-D tokamak at General Atomics. Results were published in peer-reviewed journal articles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

HT Model Dataset

This website contains the dataset that was used for writing the manuscript "HT Model: Using the Molecular Transformer for predicting hydrotreating reactions" (PNNL-SA-186589) The dataset includes a collection of hydrotreating reactions compiled from 41 peer-reviewed literature sources. These sources contain experimental data related to hydrotreating reactions. These reactions involve the reaction of chemical compounds with hydrogen gas in the presence of a catalyst to remove heteroatoms or to convert specific functional groups. The dataset contains reactions both with and without reaction conditions. Reaction conditions refer to the specific parameters under which the reaction takes place, such as temperature and pressure. For each reaction, the dataset includes both SMILES and SELFIES representations. SMILES (Simplified Molecular Input Line Entry System) and SELFIES (SELF-referencIng Embedded Strings) are two popular notations used to represent chemical structures in a compact and standardized format. The dataset was created with the aim of training a predictive model, specifically using the Molecular Transformer architecture.

bioprocessing, hydrotreating, deep learning algori↗

E3SMv2 simulation output from sensitivity study on cloud formation

This dataset contains E3SMv2 simulation output files discussed in the manuscript approved for IR in PNNL-SA-206024. The dataset was used to examine the occurrences of ultra-low cloud droplet number concentrations in E3SMv2. Submitting the manuscript to a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that.

Wan, Hui [PNNL] (ORCID:0000000152944116)↗

E3SMv1 simulation output from sensitivity study on aerosol process coupling

This dataset contains annual mean and 6-hourly output data from a set of E3SMv1 simulations that demonstrates the impact of numerical process coupling on the simulated dust life cycle. The simulations are documented and analyzed in the attached manuscript (pdf file). Publishing the manuscript in a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that. The data files to be uploaded are currently saved on Compy under /compyfs/wanh895/scidac_share/cflx_2023/

Wan, Hui↗

Intrinsic value of the international benchmark projects, ICSBEP and IRPhEP, for advanced reactor development

The International Criticality Safety Benchmark Evaluation Project, a sanctioned program under the auspices of the Nuclear Energy Agency of the Organisation for Economic Co-operation and Development, has been a highly successful and productive collaboration, now encompassing over 5,000 evaluated experimental benchmarks trusted and relied upon throughout the international nuclear communities. The success of this project led to the development of the International Reactor Physics Experiment Evaluation Project, which is dedicated to the evaluation of benchmark experiment data to sustain current and future reactor physics validation needs. These exemplary programs, and their widely utilized handbooks, serve as gold standards to which other databases strive to emulate. The purpose of the two projects is to preserve modern and legacy experimental data and evaluate it in a standardized handbook format to provide quality benchmarks to support modern and future criticality safety and reactor physics validation. These two projects have often served as the mechanism through which historic and modern neutronics experiments are evaluated and shared across international borders, to best provide unique, high-quality peer-reviewed, and often otherwise unavailable, benchmark data. The contents of these handbooks are utilized not only in validating criticality safety, reactor physics, and advanced reactor calculations, but are used to validate neutronics calculations and nuclear data for most other nuclear applications. This paper discusses both international programs and available content to enable advanced reactor design validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗