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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

LibERI—A portable and performant multi-GPU accelerated library for electron repulsion integrals via OpenMP offloading and standard language parallelism

A portable and performant graphics processing unit (GPU)-accelerated library for electron repulsion integral (ERI) evaluation, named LibERI, has been developed and implemented via directive-based (e.g., OpenMP and OpenACC) and standard language parallelism (e.g., Fortran DO CONCURRENT). Offloaded ERIs consist of integrals over low and high contraction s, p, and d functions using the rotated-axis and Rys quadrature methods. GPU codes are factorized based on previous developments with two layers of integral screening and quartet presorting. In this work, the density screening is moved to the GPU to enhance the computational efficacy for large molecular systems. Here, the L-shells in the Pople basis set are also separated into pure S and P shells to increase the ERI homogeneity and reduce atomic operations and the memory footprint. LibERI is compatible with any quantum chemistry drivers supporting the MolSSI Driver Interface. Benchmark calculations of LibERI interfaced with the GAMESS software package were carried out on various GPU architectures and molecular systems. The results show that the LibERI performance is comparable to other state-of-the-art GPU-accelerated codes (e.g., TeraChem and GMSHPC) and, in some cases, outperforms conventionally developed ERI CUDA kernels (e.g., QUICK) while fully maintaining portability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Discovery of Innovative Polymers for Next-Generation Gas-Separation Membranes using Interpretable Machine Learning

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine-learning (ML) implementation for the discovery of innovative polymers with ideal separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. Here, we interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

Yang, Jason↗
DOE OSTI2026

Computational methods in solution-based plastics purification

Plastic waste can be recycled into resins with near-virgin properties by solution-based purification processes that selectively dissolve polymers, remove contaminants, or detach printing residues. Here, in this review, we examine computational methods for predicting the behavior governing solution-based plastic purification, motivated by the vast polymer–solvent–contaminant compositional space. We discuss thermodynamic and machine learning methods for predicting polymer–solvent and polymer–contaminant interaction and review physics-based molecular dynamics simulations that resolve molecular-scale phenomena within polymer matrices inaccessible to screening methods. We highlight how these methods have informed experimental design for dissolution-based recycling and solvent-based contaminant removal. Finally, we discuss the prospective role of agentic AI in integrating these computational tools with real-time sorting data to adapt purification conditions to the compositional variability of real post-consumer feedstocks. This review charts a path toward computationally guided solution-based purification workflows that can respond to the complexity inherent in plastic waste streams.

Altamimi, Ali [Univ. of Wisconsin, Madison, WI (Un↗
DOE OSTI2023

A short account of thermoelectric film characterization techniques

Thermoelectric films and periodic structures have particularly intriguing electrical and thermal transport features due to their low dimensionality. As a result, they have piqued the attention of researchers from across the spectrum of disciplines. Their applications span from cooling fast CPUs to providing energy for wearable devices. The progress in the techniques for synthesizing TE materials and fabricating thin films has facilitated the emergence of a flourishing research domain in the field of electrical and thermal transport at the nanoscale. Further, a significant proportion of contemporary electronic, opto-electronic, and solar energy components are composed of materials featuring numerous interfaces and nanoscale contacts. Consequently, it is imperative to explore the thermal energy transfer and charge carrier transport across the films with thickness dimensions in the nanometer range. The development of cutting-edge approaches for grasping complicated processes at the nanoscale is critical. This review provides a concise overview of the prevalent methodologies developed over the last two decades and employed for the characterization of the Seebeck coefficient and electrical and thermal conductivity of thermoelectric films.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Numerical Study of Mineral Nucleation and Growth on a Substrate

We report nucleation and growth processes of minerals and other crystals can significantly affect one another due to the transport limitations and local depletion of reactive ions in the solution. Most numerical models and experimental measurements have typically focused on either growth or nucleation, but not both. In this work, we incorporate a heterogeneous nucleation process based on classical nucleation theory into a microcontinuum model that implements the Darcy–Brinkman–Stokes approach to study the interplay between nucleation and crystal growth on a substrate in diffusive systems. We demonstrate how the Damköhler number (reaction rate) and nucleation rate prefactor change the effective nucleation rate on a substrate. Higher surface growth rates deplete the solute concentration around the nuclei that appear initially on the substrate, creating islands that screen against further nucleation. The model predicts that measured nucleation rates may be affected by the history of crystal nucleation on the substrate. In the extreme case of high growth rates relative to diffusion, it predicts that the rate of subsequent nucleation is limited by reactant depletion. We introduce a nondimensional number α to represent the relation between surface propagation rate during growth and the heterogeneous nucleation rate. We show that it is important to control Damköhler number and α to achieve similar precipitation regimes at different reaction and nucleation rates. We suggest that the observed universality can guide the interpretation of experimental results on nucleation rates, since matching experiment can be achieved by tuning transport, reaction, and nucleation parameters simultaneously. In addition, we show how the bulk solution concentration affects the structure and topology of precipitation on a substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dielectric screening in perovskite photovoltaics

Abstract The performance of perovskite photovoltaics is fundamentally impeded by the presence of undesirable defects that contribute to non-radiative losses within the devices. Although mitigating these losses has been extensively reported by numerous passivation strategies, a detailed understanding of loss origins within the devices remains elusive. Here, we demonstrate that the defect capturing probability estimated by the capture cross-section is decreased by varying the dielectric response, producing the dielectric screening effect in the perovskite. The resulting perovskites also show reduced surface recombination and a weaker electron-phonon coupling. All of these boost the power conversion efficiency to 22.3% for an inverted perovskite photovoltaic device with a high open-circuit voltage of 1.25 V and a low voltage deficit of 0.37 V (a bandgap ~1.62 eV). Our results provide not only an in-depth understanding of the carrier capture processes in perovskites, but also a promising pathway for realizing highly efficient devices via dielectric regulation.

14 SOLAR ENERGY↗
DOE OSTI2024

A machine learning approach for determining temperature-dependent bandgap of metal oxides utilizing Allen–Heine–Cardona theory and O’Donnell model parameterization

To evaluate the high temperature sensing properties of metal oxide and perovskite materials suitable for use in combustion environments, it is necessary to understand the temperature dependence of their bandgaps. Although such temperature-driven changes can be calculated via the Allen–Heine–Cardona (AHC) theory, which assesses electron–phonon coupling for the bandgap correction at given temperatures, this approach is computationally demanding. Another approach to predict bandgap temperature-dependence is the O’Donnell model, which uses analytical expressions with multiple fitting parameters that require bandgap information at 0 K. This work employs data-driven Gaussian process regression (GPR) to predict the parameters employed in the O’Donnell model from a set of physical features. We use a sample of 54 metal oxides for which density functional theory has been performed to calculate the bandgap at 0 K, and the AHC calculations have been carried out to determine the shift in the bandgap at non-zero temperatures. As the AHC calculations are impractical for high-throughput screening of materials, the developed GPR model attempts to alleviate this issue by predicting the O'Donnell parameters purely from physical features. To mitigate the reliability issues arising from the very small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as quantify the uncertainty associated with the predictions. The method captures well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions of the O’Donnell parameters and, therefore, the bandgap as a function of temperature for any novel material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

X-ray Computed Tomography of Irradiated and Unirradiated AGR-3/4 Compacts

X-ray Computed Tomography (XCT) has been utilized to image and characterize compacts from the combined third and fourth irradiation of the Advanced Gas Reactor (AGR) Program, AGR-3/4, fuel. The experiment contained tristructural isotropic (TRISO)-coated fuel particles as well as designed-to-fail (DTF) fuel particles. Two irradiated compacts, representing the lower and higher range of AGR-3/4 burnup (4.85% and 14.92% fissions per initial heavy metal atom FIMA) were examined. These represent the first known highly irradiated TRISO fuel compacts to be examined via X-ray CT. Additionally, two unirradiated compacts from the same production batch as the examined irradiation compacts were also imaged for a baseline comparison. As XCT of irradiated TRISO compacts is not a commonly implemented characterization technique, a significant portion of the report focuses on developed methodology and imaging conditions. A specialized sample shielding device was developed and fabricated specifically to limit received dose to staff during sample preparation for XCT and to minimize excess gamma radiation dose to sensitive electronic components with the utilized X-ray system. Significant penetration through the uranium oxycarbide fuel kernels by significantly hardening the X-ray beam with specialized proprietary filters acquired from Carl Zeiss NTS Ltd. The filter utilized resulted in an average X ray photon energy of ~110 keV which approaches uranium’s K-edge (~115 keV), maximizing penetration for a microfocus X-ray source. The gamma-radiation emitted from the irradiated AGR-3/4 TRISO compacts, has the same properties and mechanisms for interaction with matter as X-rays, thus the detection of gamma-radiation by the utilized X-ray detectors was initially a concern. However, although ?-rays did produce an observable signal on the X-ray detector, its contribution to the overall imaging results appeared negligible upon 3D reconstruction. The neglibile impact on the resulting 3D reconstructed volumes were likely the result of: (1) a significantly lower detection efficiency for ?-rays relative to X-rays; (2) An X-ray flux at the detector several orders of magnitude higher than that of the impinging ?-rays from the irradiated compacts. These results suggest that irradiated compacts with significantly higher radiation fields can be examined in the future if an acceptable route for sample handling and preparation can be determined. Additionally, the 3D imaging results of XCT can provide a valuable means of assessing compacts. While in many ways complimentary to traditional post irradiation examination techniques such as optical ceramography, XCT can provide additional insight into compact features traditionally difficult to discern directly from cross-sectional imaging alone. Preliminary analyses on kernel size, morphology (aspect ratio and sphericity), and kernel orientation were presented. Sphericity, a simple morphological shape descriptor, was utilized to screen for kernel extrusions within the high burnup compact. The number of kernel extrusions identified via XCT represented an approximate two-fold increase from the quantity of extruded particles observed (via optical ceramography) in adjacent compacts from the same irradiation capsule. While numerical analysis of the compact datasets was highly preliminary, initial results show promise for providing complimentary metrics to current AGR-3/4 PIE and potentially additional insight into the processes driving TRISO fuel degradation during reactor operation. Additional analyses to be performed at a later date include a more detailed examination of kernel size, kernel sphericity (and observed kernel extrusions), and sphericity. Given all particles can be observed in a single data volume possible correlation of spatial position with observed kernel features will also be made at a later date.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Computational Approach for Rapidly Predicting Temperature–Dependent Polymer Solubilities Using Molecular–Scale Models

One promising approach to recycle multicomponent plastic waste (e. g., multilayer plastic films) is selective dissolution. Selective dissolution is a solvent-mediated process in which differences in polymer solubility in a carefully chosen solvent system are exploited to recover a target polymer. Here, a computational approach was developed that rapidly predicts temperature-dependent polymer solubilities to guide the design of solvent systems for solvent-mediated polymer recycling. Polymer conformations were obtained from molecular dynamics simulations by modeling the polymer as a short oligomer and then used as input to the conductor-like screening model for real solvents (COSMO-RS) for solubility predictions. Using polyethylene (PE) and ethylene vinyl alcohol (EVOH) as representative polymers, the effect of simulation parameters was systematically studied, and predicted solubilities were found to be in good agreement with experimental measurements. Furthermore, the applicability of the approach was demonstrated by identifying selective solvents for PE and EVOH dissolution from a library of 524 solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Improving bamboo’s fuel and storage properties with a net energy export through torrefaction paired with catalytic oxidation

Using torrefied char, or biocoal, as solid fuel provides an opportunity to introduce a sustainable feedstock into the energy market. The goals of this study were to investigate how torrefaction improves the energy content and the grindability of a Malaysian bamboo along with understanding the potential for integrated energy recovery from torrefaction gases. The feedstock was torrefied at 250–290 °C for 1 h and the combustion characteristics and grindability of the solid products along with the composition of torrefied gas species were measured. The results showed a beneficial increase in elemental carbon increased from 47 to 63 wt% at 290 °C torrefaction, reflecting an increase in higher heating value from 17.8 to 25.6 MJ/kg. The combustion behavior of all the products appeared to show three distinct combustion zones; however, torrefaction severity leading to higher combustion temperature and time as the fixed carbon augmented with the increase of torrefaction temperature. This increase in severity also lead to more friable and grindable material, and the 290 °C condition required a factor of 2.7 less hold-up time in the mill compared to the raw bamboo, and a factor of 8.5 less energy (938 and 111 kWh/tonne respectively). Through analysis of the gas and volatile formation, a case study showed that catalytic oxidation can convert nearly 100% of the embodied chemical energy into usable thermal energy. These experimental findings were scaled to a 100,000 tonne/y capacity torrefaction plant and in the moderate case of 270 °C operating temperature, the plant has 1.25 GJ/tonne excess energy beyond what the process needs.

09 BIOMASS FUELS↗
DOE OSTI2020

Performance of 8 × 8 × 32 and 10 × 10 × 32 mm 3 CdZnTe position-sensitive virtual Frisch-grid detectors for high-energy gamma ray cameras

CdZnTe (CZT) crystals with thicknesses up to 20 mm and diameters up to 75 mm have become available from Redlen Technologies, Inc. for making large-volume gamma-ray detectors. The modified growth and optimized annealing conditions allowed Redlen to minimize the dark current and improve the uniformity of CZT crystals. Two detector designs, pixelated (H3D) and position-sensitive virtual Frisch-grid (VFG), have greatly benefitted from the availability of such big crystals. Encouraging results from testing of 40×40×15 mm 3 pixelated detectors were recently reported by the University of Michigan. In this work, we evaluated the spectroscopic properties of 8×8×32 and 10×10×32 mm 3 crystals configured as position-sensitive VFG detectors. Both digitized waveforms and an analog ASIC were used to read and process the signals from the detectors and test their spectral- and spatial-resolution. The VFG design provides the flexibility to scale-up the dimensions of the detectors for the desired efficiency, while the position information allows for correcting the detectors' response non-uniformity caused by crystal defects and devices geometry, thereby reducing the instrument cost and making them more feasible for emerging applications in gamma-ray astronomy, nonproliferation, portal screening and nuclear safeguards, where large detector arrays are often required.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Re-Envisioning RCx: Achieving Max Potential HVAC Controls Retrofits through Modernized BAS Hardware and Software

Most existing buildings have sub-optimal heating, ventilation, and air conditioning (HVAC) controls, resulting in wasted energy and occupant discomfort. Retro-commissioning (RCx) addresses many of these issues, but it is a lengthy and highly customized process. Limited capabilities of existing building automation system hardware restricts the scope of most RCx projects. Incentive programs consider building automation system (BAS) hardware retrofits to be high-capital investments and do not allow them in typical RCx programs. This paper describes work that the authors are leading to facilitate technical and market innovation in the BAS industry to unlock large savings in existing commercial buildings through deep retrofits of BAS hardware and software. California and New York research projects are demonstrating BAS retrofits leveraging the American Society of Heating, Refrigeration, and Air Conditioning Engineers’ (ASHRAE) new Guideline 36 high performance sequences of operation to achieve greater than 20 percent whole building energy savings, while saving costs and reducing risk through streamlined processes and standardization across BAS manufacturer product lines and across implementation practices. This paper describes market barriers that impede achieving deep savings from BAS retrofits in custom incentive and traditional RCx programs and presents a new maximum potential BAS retrofit model that addresses these barriers. The new model leverages the authors’ efforts in market enablement through open standards, BAS industry partnerships, and tools for cost-effective scaling that includes tools for project screening, savings calculations, and measurement and verification (M&V). This approach is widely applicable and will be ready for at-scale implementation within two years.

Paliaga, Gwelen↗
DOE OSTI2021

Rational approach to drug discovery for human schistosomiasis

Human schistosomiasis is a debilitating, life-threatening disease affecting more than 229 million people in as many as 78 countries. There is only one drug of choice effective against all three major species of Schistosoma, praziquantel (PZQ). However, as with many monotherapies, evidence for resistance is emerging in the field and can be selected for in the laboratory. Previously used therapies include oxamniquine (OXA), but shortcomings such as drug resistance and affordability resulted in discontinuation. Employing a genetic, biochemical and molecular approach, a sulfotransferase (SULT-OR) was identified as responsible for OXA drug resistance. By crystallizing SmSULT- OR with OXA, the mode of action of OXA was determined. This information allowed a rational approach to novel drug design. Our team approach with schistosome biologists, medicinal chemists, structural biologists and geneticists has enabled us to develop and test novel drug derivatives of OXA to treat this disease. Using an iterative process for drug development, we have successfully identified derivatives that are effective against all three species of the parasite. One derivative CIDD-0149830 kills 100% of all three human schistosome species within 5 days. The goal is to generate a second therapeutic with a different mode of action that can be used in conjunction with praziquantel to overcome the ever-growing threat of resistance and improve efficacy. The ability and need to design, screen, and develop future, affordable therapeutics to treat human schistosomiasis is critical for successful control program outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Machine learning enables interpretable discovery of innovative polymers for gas separation membranes

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine learning (ML) implementation for the discovery of innovative polymers with ideal performance. Specifically, multitask ML models are trained on experimental data to link polymer chemistry to gas permeabilities of He, H 2 , O 2 , N 2 , CO 2 , and CH 4 . We interpret the ML models and extract valuable insights into the contributions of different chemical moieties to permeability and selectivity. We then screen over 9 million hypothetical polymers and identify thousands that lie well above current performance upper bounds, including hundreds of never-before-seen ultrapermeable polymer membranes with O 2 and CO 2 permeability greater than 10 4 and 10 5 Barrers, respectively. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Site 200 #1400 Block Area New Trailers Project, Soil Sampling and Analysis Plan/Quality Assurance Plan

Lawrence Livermore National Laboratory's (LLNL) Project Management Office (PMO) is proposing to install a series of modular trailers and install associated underground utilities in the 1400 Block at the Livermore Site. This Sampling and Analysis Plan (SAP) outlines the processes and procedures to collect environmental and geotechnical soil samples from the project area and to send the samples to the appropriate laboratory or laboratories for analysis or testing. The resulting environmental laboratory data will determine whether excavated soils can be reused on the project, or which type of landfill or landfills the soils may be sent for disposal. This SAP has been prepared and is organized to be consistent with LLNL's Soils Screening and Management Plan (SSMP) (LLNL, 2019), as well as the U.S. Environmental Protection Agency's (EPA) Data Quality Objectives programs (EPA, 2006).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Preliminary Assessment of Qiskit Quantum Simulator Capabilities for Development of Quantum Hopfield Neural Network for Anomaly Detection Applications (Q4 Report)

Quantum information processing offers potentially faster performance compared to the classical counterpart. The goal of this work is to investigate performance of Quantum Hopfield Neural Network for applications to anomaly detection. Preliminary study consist of assessment of computational capabilities of Qiskit quantum simulator. Eventual objective is to implement Quantum Hopfield Network algorithm for detection of weak nuisance and anomaly signal in the presence of strong and highly varying background in gamma radiation data measured during environmental screening.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Characterization of compositional variation and solidification condition on rapid solidification behavior of beta stabilized titanium

Rapid solidification (RS) is a field of study that has increased in importance due to the rise of additive manufacturing (AM) techniques. The breakdown of equilibrium at the solid-liquid interface results in an inability to use traditional solidification models that have been applied to great success in casting. As such, there is a current need for a high-throughput testing method to screen alloys at rapid solidification conditions without the significant cost for powder atomization. In this work, twin hammer splat quenching (SQ) is utilized and theoretically developed as a technique uniquely placed to test alloy systems for AM applications. Using analytical thermal spray models and numerical heat transfer simulations, the cooling rate and solidification conditions of splat quenching are compared across several parameters to evaluate the key parameters for generating cooling rates relevant to AM process. Once a framework for the cooling rates and relevancy of SQ are developed, SQ was used to process alloy compositions in the Ti5553 alloy space (AMS 7026) to study the formation of detrimental secondary phases occurring upon rapid quenching from the melt. A martensitic phase is found to occur at the lower end of the standard, but the composition listed in the standard were found to be safe. Finally, the rapid solidification behavior of Ti-5553 is evaluated by comparing splat quenching, laser welding, and plasma atomization that offer a wide window of solidification conditions. The segregation and solidification structure are analyzed and compared to models to provide a deeper understanding of the solidification behavior of beta stabilized titanium alloys.

Williamson, Christopher J.↗
DOE OSTI2024

Excitons in 2D Magnets

Theoretical abilities that we built: In our QSGW formalism, the electronic eigenfunctions are calculated self-consistently in presence of the ladder e-h vertex corrections to the screened Coulomb exchange. Charge and self-energies are recalculated iterated until the desired tolerance is achieved in the one-particle Green's function. Further, to include the multi-determinantal (spin-flip structure of multiplets) nature of many body correlations we combine QSGW with DMFT. Below we explore various classes of strongly correlated magnetic systems where excitons are sufficiently described within either the QSGW or the QSGW +DMFT approach. In the process, we establish the digrammatic requirements for a minimum-sufficient theory for describing excitons in large classes of materials.

2D magnets↗