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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Introducing GPU Acceleration into the Python-Based Simulations of Chemistry Framework

We introduce the first version of GPU4P Y SCF, a module that provides GPU acceleration of methods in P Y SCF. As a core functionality, this provides a GPU implementation of two-electron repulsion integrals (ERIs) for contracted basis sets comprising up to g functions using the Rys quadrature. As an illustration of how this can accelerate a quantum chemistry workflow, we describe how to use the ERIs efficiently in the integral-direct Hartree–Fock build and nuclear gradient construction. Benchmark calculations show a significant speedup of 2 orders of magnitude with respect to the multithreaded CPU Hartree–Fock code of P Y SCF and the performance comparable to other open-source GPU-accelerated quantum chemical packages, including GAMESS and QUICK, on a single NVIDIA A100 GPU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Enabling reliability assessments of pre-commercial perovskite photovoltaics with lessons learned from industrial standards [Enabling reliability of pre-commercial perovskite photovoltaics with lessons learned from industrial standards]

Here, photovoltaic modules are expected to operate in the field for more than 25 years, so reliability assessment is critical for the commercialization of new photovoltaic technologies. In early development stages, understanding and addressing the device degradation mechanisms are the priorities. However, any technology targeting large-scale deployment must eventually pass industry-standard qualification tests and undergo reliability testing to validate the module lifetime. In this Perspective, we review the methodologies used to assess the reliability of established photovoltaics technologies and to develop standardized qualification tests. We present the stress factors and stress levels for degradation mechanisms currently identified in pre-commercial perovskite devices, along with engineering concepts for mitigation of those degradation modes. Recommendations for complete and transparent reporting of stability tests are given, to facilitate future inter-laboratory comparisons and to further the understanding of field-relevant degradation mechanisms, which will benefit the development of accelerated stress tests.

14 SOLAR ENERGY↗
DOE OSTI2025

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗
DOE OSTI2023

Novel Chalcopyrites for Advanced Photoelectrochemical Water Splitting

With the support of DoE’s EERE office, our team has established a unique tool-chest of capabilities, including theoretical modeling (Lawrence Livermore National Laboratory: LLNL), state-of-the-art synthesis (Hawaii Natural Energy Institute: HNEI, Stanford, and the National Renewable Energy Laboratory: NREL) and advanced materials and interfaces characterization (University of Nevada, Las Vegas: UNLV, and Lawrence Berkeley National Laboratory: LBNL), to accelerate the development of high efficiency and durable chalcopyrite materials for advanced photoelectrochemical (PEC) water splitting. Using this synergistic approach, we have successfully created new wide bandgap chalcopyrite photocathodes generating over 10 mA/cm 2 , developed innovative strategies to protect them from corrosion, and engineered novel integration methods to circumvent thin film materials mechanical, chemical and thermal incompatibility. In Task 1 “Modeling and synthesis of chalcopyrite photocathodes”, we expanded our library of wide bandgap chalcopyrites for PEC water splitting. With support from LLNL’s “Computational Materials Diagnostics and Optimization of PEC Devices”, LBNL’s “photophysical” and NREL’s “I-III-VI Compound Semiconductors for Water-Splitting” nodes, we investigated two new chalcopyrite candidates for PEC water splitting: Cu(In,Al)Se 2 and Cu(In,B)Se 2 . We also further developed ordered vacancy compounds, such as CuGa 3 Se 5 , with unprecedented durability during PEC waters splitting in acidic solutions. In Task 2 “Interfaces engineering for enhanced efficiency and durability”, we addressed both the non-ideal band-edge positions of chalcopyrites with respect to water redox potentials, as well as their chemical instability under PEC water splitting, with a buried-junctions approach. With help from NREL’s “High-Throughput Experimental Thin Film Combinatorial Capabilities” and “Corrosion Analysis of Materials” nodes, we engineered environmentally friendly n-type buffers, including Mn x Zn 1-x O, to adjust the chalcopyrite band-edge positions and achieved photovoltages as high as 925 mV. Also, we integrated non-precious catalytic-protecting layers, such as WO 3 , to enhance the water splitting long-term stability of chalcopyrite absorbers. Finally, in Task 3 “Hybrid photoelectrode device integration”, we proposed an innovative method to bond wide bandgap photocathodes onto narrow bandgap PV drivers at room temperature using conductive polymers. Our semi-monolithic approach addressed fundamental processing incompatibility issues, as both the photocathode and the PV driver are processed separately. Proof-of-concept whole-chalcopyrite tandems were obtained by consecutive exfoliation and transfer of fully integrated 1.85 eV CuGa 3 Se 5 and 1.13 eV CuInGaSe 2 stacks from their Mo/SLG substrates onto a new single FTO host substrate.

08 HYDROGEN↗
DOE OSTI2017

INL’s TAP Systems

The starting point for many consumer products is the industrial manufacture of platform chemicals. The recent boom in domestic shale gas production makes it possible to envision a new resource for chemical manufacturing. Catalysts are the accelerants behind most industrial chemical reactions. A sophisticated research technique using a Temporal Analysis of Products (or TAP) reactor can now help. By shedding light on a catalyst’s fundamental step-by-step process, a TAP reactor can help chemists and chemical engineers understand why a new catalyst works better in the lab than in the chemical plant.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2026

Development of Digital Twin-Informed Predictive Maintenance for Critical Components in Advanced Reactors

Small modular reactors (SMRs) and microreactors, along with other advanced reactor (AR) technologies, are key to the future of nuclear energy. For these systems to achieve low operating costs, high reliability, and flexibility across applications, their operation and maintenance must be optimized. Digital twin (DT) technology is one of the technologies that enables real-time (or faster than real-time) monitoring and prognosis of critical components which are vital for operational efficiency, low costs, and enhanced safety of ARs, accelerating their deployment. DT technology provides dynamic virtual representation of physical assets by integrating real-time data, physics-based models, and advanced analytics, which is critical to optimizing the performance of the entire energy system throughout the life cycle. DTs empower engineers and operators to virtually explore different scenarios, configurations, and control strategies, allowing for the identification of optimal solutions that maximize reactor efficiency, safety, and economics.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Rapid Alloy Surface Engineering through Closed-Vessel Reagent Pyrolysis

For rapid surface engineering of Cr-containing alloys by low-temperature nitrocarburization, we introduce a process based on pyrolysis of solid reagents, e.g., urea, performed in an evacuated closed vessel. Upon heating to temperatures high enough for rapid diffusion of interstitial solute, but low enough to avoid second-phase precipitation, the reagent is pyrolyzed to a gas atmosphere containing molecules that (i) activate the alloy surface by stripping away the passivating Cr 2 O 3 -rich surface film (diffusion barrier) and (ii) rapidly infuse carbon and nitrogen into the alloy. We demonstrate quantitatively that this method can generate a subsurface zone with concentrated carbon and nitrogen comparable to what can be accomplished by established (e.g., gas-phase- or plasma-based) methods, but with significantly reduced processing time. As another important difference to established gas-phase processing, the interaction of gas molecules with the alloy surface can have auto-catalytic effects by altering the gas composition in a way that accelerates solute infusion by providing a high activity of HNCO. The new method lends itself to rapid experimentation with a minimum of laboratory equipment.

36 MATERIALS SCIENCE↗
DOE OSTI2019

CLAS12 First Experiments and Hadron Structure

The new CLAS12 large acceptance spectrometer was recently installed in Hall B as part of the 12 GeV upgrade project at Jefferson Laboratory that served to double the maximum electron beam energy of the accelerator. The approved CLAS12 experimental physics program spans a broad scientific scope designed to address fundamental and critical issues in nuclear physics such as detailed spectroscopy of the excited baryon spectrum including a search for hybrid baryons where the glue serves as an active structural component, elucidation of the role of gluons in hadronic structure, studies of the implications of short range forces acting in nucleons and nuclei, and detailed investigations that serve to reveal the structure of ground and excited states including 3-D imaging of the ground state nucleons and exploration of the N --> N* form factors in the transition from the regimes of confinement to perturbative QCD. These studies will address questions on the nature of the mass of hadrons, quark-gluon confinement, and how such a diversity of hadrons emerges from QCD. The commissioning of the CLAS12 spectrometer was completed during an Engineering Run that took place in Dec. 2017 and Jan. 2018. This was followed by the first physics production running periods spanning 23 weeks in the spring and fall of 2018. This talk will review the initial CLAS12 physics program and highlight the current status of the ongoing physics analyses. *The Southeastern Universities Research Association (SURA) operates the Thomas Jefferson National Accelerator Facility for the United States Department of Energy under Contract No. DE-AC05-84ER40150. This material is based upon work supported by the US Department of Energy, Office of Science, Office of Nuclear Physics under Contract No DE-AC05-06OR23177.

Carman, Daniel↗
DOE OSTI2018

Four-harmonic buncher for radioactive and stable beams switching at the ATLAS facility [Four-harmonic buncher for radioactive and stable beams combination at the ATLAS facility]

Here, the Argonne Tandem Linac Accelerator System (ATLAS) is planning an upgrade to a multi-user facility to simultaneously accelerate both stable beams from an ECR ion source and radioactive beams from an Electron Beam Ion Source charge breeder. The ATLAS Multi-User Upgrade will need to provide high transmission of ion beams with a mass-to-charge ratio up to 7 as it enables more options to alternate radioactive and stable beams. Currently, the bunching is provided with a lumped circuit multi-harmonic buncher, which cannot effectively operate at the required amplitude of the saw-tooth voltage for ions with mass-to-charge ratio of 7 due to thermal issues. RadiaBeam Systems in collaboration with Argonne National Laboratory has designed a four-harmonic coaxial resonator buncher with the ATLAS fundamental frequency of 12.125 MHz, and a compact, less than 2-m-long, footprint, capable of providing the required voltage of 6.2 kV. This device allows fast and reliable pre-bunching of DC ion beams with the capability of fast switching of heavy-ion radioactive and stable beams for delivery to multiple users. In this paper, we will discuss the RF and engineering design considerations of this buncher.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Atomic layer deposition of nickel sulfide thin films and their thermal and electrochemical stability

Nickel sulfides (NiS x ) show promise for a range of energy and other applications, but their (in)stability under processing and operating conditions is scarcely studied. Herein, we have developed a new NiS x atomic layer deposition process using an easily synthesized NiCl 2 (TMPDA) precursor (TMPDA = N,N,N′,N′-tetramethyl-1,3-propanediamine) with H 2 S. Thin films deposited at 165–225 °C consist mostly of the β-NiS phase and display low resistivity (∼40–120 μΩ cm), high purity (<3 at% impurities), and a rough morphology. The thermal stability of the NiS x thin films is studied using high-temperature X-ray diffraction, revealing that structural and compositional changes occur in reducing, inert, and oxidizing atmospheres at approximately 300–400 °C. Under electrochemical water splitting conditions, the films are unstable in acid due to dissolution, especially at oxidizing potentials. In an alkaline electrolyte, we do not observe Ni dissolution, but β-NiS transforms to Ni 3 S 2 under HER conditions, possibly supplemented with Ni and/or Ni(OH) 2 species. Under alkaline OER, all sulfur is lost and NiOOH is formed. In addition to offering an attractive, scalable route to the synthesis of NiS x thin films, our work highlights the importance of thermal and electrochemical (in)stability of sulfides as a crucial step for understanding and engineering materials for energy and other applications.

Mattinen, Miika [Univ. of Helsinki (Finland); Stan↗
DOE OSTI2019

Rayleigh-Taylor-instability experiments with elastic-plastic materials

A rotating wheel experimental facility was developed to investigate incompressible Rayleigh-Taylor instability in elastic-plastic materials. A soft solid (mayonnaise) was chosen as the elastic-plastic material for experiments; material properties that include shear modulus and yield strength were fully characterized using a vane spindle type rheometer. Initial perturbations of varying amplitudes and wavelengths were generated on the interface of the soft solid using sinusoidal cutting guides. A backlit imaging technique was used in conjunction with a high-speed camera to track the motion of the interface at various phases of the instability. Results for both two- and three-dimensional perturbations were compared to study the acceleration required for instability and the growth after the interface yielded. Exponential growth rates were observed after instability was reached with trends of increasing growth rates for lower initial amplitudes. It was found that the acceleration required for instability increased when initial amplitude and wavelength decreased. Here, three-dimensional interfaces were found to be more stable. For both cases, a decrease in initial amplitude produced a more stable interface that increased the threshold acceleration required for the instability. Critical amplitude conditions for instability were calculated and compared with various analytical models and other experimental results.

42 ENGINEERING↗
DOE OSTI2023

An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies

Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. However, without proper image collection and interpretation, triage decisions can be hard to make. While automation approaches can enhance these triage applications, tissue phantoms must be developed to train and mature these novel technologies. Here, we have developed a tissue phantom modeling the ultrasound views imaged during the enhanced focused assessment with sonography in trauma exam (eFAST). The tissue phantom utilized synthetic clear ballistic gel with carveouts in the abdomen and rib cage corresponding to the various eFAST scan points. Various approaches were taken to simulate proper physiology without injuries present or to mimic pneumothorax, hemothorax, or abdominal hemorrhage at multiple locations in the torso. Multiple ultrasound imaging systems were used to acquire ultrasound scans with or without injury present and were used to train deep learning image classification predictive models. Performance of the artificial intelligent (AI) models trained in this study achieved over 97% accuracy for each eFAST scan site. We used a previously trained AI model for pneumothorax which achieved 74% accuracy in blind predictions for images collected with the novel eFAST tissue phantom. Grad-CAM heat map overlays for the predictions identified that the AI models were tracking the area of interest for each scan point in the tissue phantom. Overall, the eFAST tissue phantom ultrasound scans resembled human images and were successful in training AI models. Tissue phantoms are critical first steps in troubleshooting and developing medical imaging automation technologies for this application that can accelerate the widespread use of ultrasound imaging for emergency triage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Systems Engineering Approach for Design and Implementation of a Gas Breech for Actinide Experiments at the JASPER Facility

The Joint Actinide Shock Physics Experimental Research (JASPER) Facility is located approximately 65 miles north of Las Vegas, Nevada at the Nevada National Security Site (NNSS). The primary mission is to conduct shock physics research on actinide materials in support of NNSA’s Stockpile Stewardship Program. JASPER experiment uses a two-stage light gas gun to accelerate projectiles into targets at velocities up to 8 km/s (17,000 mph). The first stage uses an ignited propellent to drive a piston to compress gas in the pump tube. At the second stage, the gas compression exceeds a specified pressure and a rupture valve at the end of the pump tube opens. This launches a projectile to impact the target. The target is housed inside the target assembly and the debris field is contained inside the primary target chamber (PTC). The PTC is placed inside the secondary confinement chamber (SCC) as an added protection against possible contamination. These major components are illustrated in Figure 1.JASPER is capable of generating and measuring data on the properties of radioactive chemical elements at high shock pressures, temperatures, and strain rates approximating the conditions in nuclear weapons by using a two-stage gas gun. The data is used to determine material equations-of-state and validate computer models of material response. The work advances predictive capability, thus ensuring confidence in the nuclear stockpile.

42 ENGINEERING↗
DOE OSTI2020

Process intensification education contributes to sustainable development goals. Part 1

In 2015 all the United Nations (UN) member states adopted 17 sustainable development goals (UN-SDG) as part of the 2030 Agenda, which is a 15-year plan to meet ambitious targets to eradicate poverty, protect the environment, and improve the quality of life around the world. Although the global community has progressed, the pace of implementation must accelerate to reach the UN-SDG time-line. For this to happen, professionals, institutions, companies, governments and the general public must become cognizant of the challenges that our world faces and the potential technological solutions at hand, including those provided by chemical engineering. Process intensification (PI) is a recent engineering approach with demonstrated potential to significantly improve process efficiency and safety while reducing cost. It offers opportunities for attaining the UN-SDG goals in a cost-effective and timely manner. However, the pedagogical tools to educate undergraduate, graduate students, and professionals active in the field of PI lack clarity and focus. This paper sets out the state-of-the-art, main discussion points and guidelines for enhanced PI teaching, deliberated by experts in PI with either an academic or industrial background, as well as representatives from government and specialists in pedagogy gathered at the Lorentz Center (Leiden, The Netherlands) in June 2019 with the aim of uniting the efforts on education in PI and produce guidelines. In this Part 1, we discuss the societal and industrial needs for an educational strategy in the framework of PI. The terminology and background information on PI, as it relates to educational implementation in industry and academia, are provided as a preamble to Part 2, which presents practical examples that will help educating on Process Intensification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, the development of new coating systems is hindered by the large design space and difficulty in predicting the properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate the thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict the phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate the accurate prediction of the anisotropy of the CTE in good agreement with the diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

36 MATERIALS SCIENCE↗