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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Feasibility Analysis of Converter-Interfaced Combined Heat and Power System

As a promising new design concept, the converter-interfaced combined heat and power (CHP) system is coupled to the bulk grid through a rectifier and a grid-ready tied inverter. Compared to the traditional directly-coupled CHP system, it removes the requirement for oversizing the CHP generator, limits the short-circuit contribution of the generator and simplifies the grid integration process of CHP system. This paper evaluates the economic benefits of this concept by calculating the annualized Return-on-Investment (ROI) and comparing it to the directly-coupled system. The economic analysis includes timeseries simulations to compute energy transactions with the bulk grid as well as sizing the equipment to calculate the capital and operational costs. Obtained results indicate that in majority of user cases evaluated, the converter-interfaced CHP systems can provide better ROI than directly-coupled systems. Given the additional technical benefits provided by inverter-based distributed energy resources (DERs), the proposed concept is proved to be technically viable and economically feasible.

03 NATURAL GAS↗
DOE OSTI2021

Nanoscale Structure and Dynamics in Geochemical Systems

Neutron scattering is a powerful tool to elucidate the structure and dynamics of systems that are important to geochemists, including ion association in complex aqueous solutions, solvent-exchange reactions at mineral–water interfaces, and reaction and transport of fluids in nanoporous materials. This article focusses on three techniques: neutron diffraction, which can reveal the atomic-level structure of aqueous solutions and solids; quasi-elastic neutron scattering, which measures the diffusional dynamics at mineral–water interfaces; and small-angle neutron scattering, which can show how properties of nanoporous systems change during gas, liquid, and solute imbibition and reaction. Furthermore, the usefulness and applicability of the experimental results are extended by rigorous comparison to computational simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Data Processor 3 QASPR Project

The following discussion contains a high-level description of methods used to implement software for data processing. It describes the required directory structures and file handling required to use Excel's Visual Basic for Applications programming language and how to identify shot, test and capture types to appropriately process data. It also describes how to interface with the software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Summary Report from the 2025 Interfaces for Energy and the Environment Conference

The inaugural Interfaces for Energy and the Environment Conference (IEEC) took place on May 19-23, 2025, at Pacific Northwest National Laboratory (PNNL), Richland, Washington (USA). The aim of this first-of-its-kind interdisciplinary meeting was to provide a forum for participants to share the latest cutting edge experimental and computational advances in interfacial science across energy and environmental applications. The sessions below (elaborated further in the report summaries) highlighted fundamental and applied collaborative research aimed at understanding the interactions occurring at interfaces in aqueous environments, including, but not limited to, the fields of geochemistry, atmospheric chemistry, agriculture, environmental management, and catalysis. They were organized to stimulate and provide opportunities to create, renew, and deepen collaborations. The conference included activities such as oral and poster presentations, honoree mentoring session, and a team building exercise to support all career stages (detailed summaries of these activities are in the Appendices).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fundamental Investigations of Mechanical and Chemical Degradation Mechanisms in Lithium Ion Battery Materials (Final Technical Report)

The objective of our effort under the DOE EPSCoR Implementation grant is to establish a comprehensive and internationally recognized research program at Brown University and University of Rhode Island in understanding degradation mechanisms and to improve the cycle and calendar life of lithium ion battery (LIB) materials. A series of basic investigations are undertaken to characterize the mechanical and chemical degradation mechanisms, which can help enable new higher capacity and longer lasting electrode designs. Controlling mechanical and chemical degradation is the primary challenge in developing the next generation of higher energy density batteries. The development of failure resistant battery microstructures will require a fundamental understanding of the evolution of stress, deformation, damage, and electrochemistry in battery materials during cyclic charging and discharging. In addition, controlling the reactions at the electrode/electrolyte interface is critical for the formation of a stable SEI layer. We address these issues through a combination of controlled experiments on model battery materials and practical composite electrodes, together with multi-scale computations. Our effort is organized into three focus areas that encompass many critical challenges in Lithium Ion Battery Technologies: (i) Mechanical properties, fracture and damage in electrode materials; (ii) Chemistry and Mechanics of Solid Electrolyte Interphase (SEI); (iii) Mechanical and Chemical Integrity of Solid-Solid Interfaces in Practical Electrodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Developing an Automated Uncertainty Quantification Tool to Improve Watershed-Scale Predictions of Water and Nutrient Cycling

Managing the flow of water, nutrients, and contaminants in watersheds is vital to addressing pressing issues related to water scarcity, access to clean drinking water, energy production, resilience to natural and anthropogenic perturbations, and ecological restoration. Decisions about the management of watersheds critically depend on the accuracy with which the flow of water and chemicals through the watershed can be predicted by computer models. Prediction uncertainty can be reduced by matching the model to data, which are collected in the field at great expense. The contribution of watershed characterization data to reducing uncertainty of relevant model predictions can be evaluated in a so-called data-worth analysis, which provides transparent, quantitative metrics about a data set’s value for the support of relevant watershed management objectives. To achieve this goal, we developed a software package that implements the data-worth analysis approach for use with state-of-the-art watershed models. The purpose of the proposed data-worth analysis is to help decision-makers allocate resources for watershed characterization such that the uncertainty in model predictions can be significantly reduced, which leads to better, more effective management decisions. At the same time, watershed characterization costs can be reduced. The specific technical objectives of this SBIR/STTR Phase II project were to develop a framework and associated software toolsets that implement the uncertainty quantification and data-worth analysis approach for use with state-of-the-art watershed models. This goal was achieved by (A) developing a user-friendly, robust software package that is accessible to a wide audience, including watershed managers, policy-makers, and public stakeholders; (B) by demonstrating application of the prototype on several use cases that are representative of complex watershed management challenges spanning a range of scales and that consider different open-source, DOE-based codes and other modeling platforms; and (C) by gathering information about the needs and requirements from potential users to help guide future developments, ensuring that the final product will be commercially viable. The developed software consists of a graphical user interface that guides the user through a sequence of analysis steps, supported by toolsets that leverage state-of-the-art computational simulation-optimization capabilities. A prototype of the software runs on multiple platforms (PC, Mac, multi-processor Linux environment), is linked to diverse watershed simulators (e.g., ECOSYS, TOUGH2, TOUGHREACT, Amanzi-ATS), performs multiple analysis tasks (predictive simulations, sensitivity analysis, uncertainty analysis, automatic parameter estimation, and data-worth analysis, multicomponent geothermometry), and is readily extensible to include external simulators and analysis tools. The software is being commercialized and will be continually updated to address user needs.

58 GEOSCIENCES↗
DOE OSTI2016

Full core LOCA analysis for BWR/6 - Methodology and first results

As part of collaboration between the Paul Scherrer Institute (PSI) and the Swiss regulator ENSI, a study aimed at core-wide estimates of the fuel rod behaviour during large-break loss-of-coolant-accidents (LB-LOCA) in BWR/6 plants was recently conducted on the basis of a Swiss reactor. To perform such full core LOCA analysis, a methodology consisting of a multi-physics sequence of interfaced best-estimate models and codes was established: CASMO-4E/SIMULATE-3 (C4/S3) for the core modelling, TRACE for the plant system analysis and FALCON for the fuel thermomechanical calculations during base irradiation (BI) as well as for the transient analyses (TA). As starting point, reference C4/S3 models validated for all operated cycles of the given plant were used to select as situation target, a recent cycle representative of modern BWR core loadings and fuel assembly designs. Based on the selected C4/S3 cycle model, PSI in-house computational modules were developed or updated in order to set up the TRACE full core model with regards to assembly geometries, fuel rods thermophysical properties and initial 3-D power distributions. Also, an interface to FALCON BI models was established for the transfer of the irradiation history, including primarily linear heat generation rates (LHGR), for an equivalent fuel pin. For each assembly, the power of the equivalent pin is defined with the maximum power of all pins at each axial position. However, in order to reduce the computational time of the fuel performance analyses, the whole core was subdivided into groups of assemblies, each represented by the most powerful assembly within the group. On this basis, the FALCON BI analyses were conducted with coupling to the PSI advanced model for gas release and swelling (GRWS-A) and an interface was developed to transfer the calculated fuel rod characteristics at end of irradiation to initialize the core fuel rods heat structures in the TRACE model. Subsequently, double-ended recirculation line rupture scenarios at hot-full-power (HFP) conditions were investigated with TRACE in order to determine a conservative transient case as function of cycle burnup, single failure criterion and availability of safety systems. For the most conservative case of this study, an interface was set-up to transfer the TRACE results as boundary conditions to the FALCON TA models, including thus primarily time and axial distributions of the clad outer temperatures. As final step, the FALCON TA were conducted for the representative assemblies in order to infer core-wide estimates of the fuel rod behaviour with specific focus on equivalent cladding reacted levels, hoop strains as well as margins to failure criteria. The objective of this paper is to present this methodology along with the obtained first results. Regarding the latter, it is found that principally, even for the most conservative LOCA scenario of this study, the clad temperature excursion remains mild enough at all core locations such that no significant rod ballooning and no cladding failure is predicted, something in line with corresponding analyses conducted earlier for BWR/4 plants. (authors)

42 ENGINEERING↗
DOE OSTI2022

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Free fermion entanglement with a semitransparent interface: the effect of graybody factors on entanglement islands

We study the entanglement entropy of free fermions in 2d in the presence of a partially transmitting interface that splits Minkowski space into two half-spaces. We focus on the case of a single interval that straddles the defect, and compute its entanglement entropy in three limits: Perturbing away from the fully transmitting and fully reflecting cases, and perturbing in the amount of asymmetry of the interval about the defect. Using these results within the setup of the Poincaré patch of AdS _2 2 statically coupled to a zero temperature flat space bath, we calculate the effect of a partially transmitting AdS _2 2 boundary on the location of the entanglement island region. The partially transmitting boundary is a toy model for black hole graybody factors. Our results indicate that the entanglement island region behaves in a monotonic fashion as a function of the transmission/reflection coefficient at the interface.

Kruthoff, Jorrit↗
DOE OSTI2020

First-Principles Quantum Transport Modeling of Spin-Transfer and Spin-Orbit Torques in Magnetic Multilayers

A unified approach for computing (i) spin-transfer torque in magnetic trilayers like spin valve and magnetic tunnel junction, where injected charge current flows perpendicularly to interfaces, and (ii) spin-orbit torque in magnetic bilayers of the type ferromagnet/spin-orbit-coupled material, where injected charge current flows parallel to the interface, was reviewed. The experimentally explored and technologically relevant spin-orbit-coupled materials include 5d heavy metals, topological insulators, Weyl semimetals, and transition metal dichalcogenides. This approach requires to construct the torque operator for a given Hamiltonian of the device and the steady-state nonequilibrium density matrix, where the latter is expressed in terms of the nonequilibrium Green’s functions and split into three contributions. Tracing these contributions with the torque operator automatically yields field-like and damping-like components of spin-transfer torque or spin-orbit torque vector, which is particularly advantageous for spin-orbit torque where the direction of these components depends on the unknown-in-advance orientation of the current-driven nonequilibrium spin density in the presence of spin-orbit coupling. Illustrative examples are provided by computing spin-transfer torque in a one-dimensional toy model of a magnetic tunnel junction and realistic Co/Cu/Co spin valve, both of which are described by first-principles Hamiltonians obtained from noncollinear density functional theory calculations, as well as by computing spin-orbit torque in a ferromagnetic layer described by a tight-binding Hamiltonian which includes spin-orbit proximity effect within ferromagnetic monolayers assumed to be generated by the adjacent monolayer transition metal dichalcogenide. In addition, it is shown here how spin-orbit proximity effect, quantified by computing (via first-principles retarded Green’s function) spectral functions and spin textures on monolayers of realistic ferromagnetic material like Co in contact with heavy metal or monolayer transition metal dichalcogenide, can be tailored to enhance the magnitude of spin-orbit torque. Furthermore, errors made in the calculation of spin-transfer torque are quantified when using Hamiltonian from collinear density functional theory, with rigidly rotated magnetic moments to create noncollinear magnetization configurations, instead of proper (but computationally more expensive) self-consistent Hamiltonian obtained from noncollinear density functional theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

The Virtual Environment for Reactor Applications (VERA): Design and architecture

VERA, the Virtual Environment for Reactor Applications, is the system of physics capabilities being developed and deployed by the Consortium for Advanced Simulation of Light Water Reactors (CASL). CASL was established for the modeling and simulation of commercial nuclear reactors. VERA consists of integrating and interfacing software together with a suite of physics components adapted and/or refactored to simulate relevant physical phenomena in a coupled manner. VERA also includes the software development environment and computational infrastructure needed for these components to be effectively used. We describe the architecture of VERA from both software and numerical perspectives, along with the goals and constraints that drove major design decisions, and their implications. We explain why VERA is an environment rather than a framework or toolkit, why these distinctions are relevant (particularly for coupled physics applications), and provide an overview of results that demonstrate the use of VERA tools for a variety of challenging applications within the nuclear industry.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Atomic-scale interface engineering of Majorana edge modes in a 2D magnet-superconductor hybrid system

Topological superconductors are predicted to harbor exotic boundary states—Majorana zero-energy modes—whose non-Abelian braiding statistics present a new paradigm for the realization of topological quantum computing. Using low-temperature scanning tunneling spectroscopy, here, we report on the direct real-space visualization of chiral Majorana edge states in a monolayer topological superconductor, a prototypical magnet-superconductor hybrid system composed of nanoscale Fe islands of monoatomic height on a Re(0001)-O(2 × 1) surface. In particular, we demonstrate that interface engineering by an atomically thin oxide layer is crucial for driving the hybrid system into a topologically nontrivial state as confirmed by theoretical calculations of the topological invariant, the Chern number.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

TomoPyUI : a user-friendly tool for rapid tomography alignment and reconstruction

The management and processing of synchrotron and neutron computed tomography data can be a complex, labor-intensive and unstructured process. Users devote substantial time to both manually processing their data ( i.e. organizing data/metadata, applying image filters etc. ) and waiting for the computation of iterative alignment and reconstruction algorithms to finish. In this work, we present a solution to these problems: TomoPyUI , a user interface for the well known tomography data processing package TomoPy . This highly visual Python software package guides the user through the tomography processing pipeline from data import, preprocessing, alignment and finally to 3D volume reconstruction. The TomoPyUI systematic intermediate data and metadata storage system improves organization, and the inspection and manipulation tools (built within the application) help to avoid interrupted workflows. Notably, TomoPyUI operates entirely within a Jupyter environment. Herein, we provide a summary of these key features of TomoPyUI , along with an overview of the tomography processing pipeline, a discussion of the landscape of existing tomography processing software and the purpose of TomoPyUI , and a demonstration of its capabilities for real tomography data collected at SSRL beamline 6-2c.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Exploring Applications of Random Walks on Spiking Neural Algorithms

Neuromorphic computing has many promises in the future of computing due to its energy efficient and scalable implementation. Here we extend a neural algorithm that is able to solve the diffusion equation PDE by implementing random walks on neuromorphic hardware. Additionally, we introduce four random walk applications that use this spiking neural algorithm. The four applications currently implemented are: generating a random walk to replicate an image, finding a path between two nodes, finding triangles in a graph, and partitioning a graph into two sections. We then made these four applications available to be implemented on software using a graphical user interface (GUI).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Characterizing Structure-Dependent TiS 2 /Water Interfaces Using Deep-Neural-Network-Assisted Molecular Dynamics

As a promising layered electrode material, TiS 2 -based capacitive deionization (CDI) devices for water desalination have attracted significant attention. However, TiS 2 /H 2 O interfacial features, potentially important for device optimization, remain unidentified. Using Deep Potential Molecular Dynamics (DPMD), we characterized distinct aqueous interfaces introduced by four TiS 2 terminations expected to be present as water intercalates into TiS 2 , namely, Armchair, Zigzag, Zigzag-L, and Zigzag-R. First, we assessed important representative physical properties of the system to validate the deep potentials (DPs). DPMD simulations agree well with experiments and first-principles simulations, suggesting the DPs are accurate and reliable. Subsequent simulations of these TiS 2 /water interfaces revealed how TiS 2 surface termination influences the structure of interfacial water. This effect is most evident in the first and second water layers close to the TiS 2 surface, and more pronounced when spontaneous dissociative adsorption of water occurs. The extent of water dissociation on each surface was evaluated using enhanced sampling. Zigzag-L is the only interface where proton transfer from adsorbed water to TiS 2 surface S atoms is thermodynamically and kinetically favored. The coexistence of surface four-fold-coordinated Ti (Ti 4c ) and one-fold-coordinated S (S 1c ) is found to be essential to making proton transfer feasible on the Zigzag-L surface. Furthermore, remaining unprotonated S 1c atoms can act as good proton acceptors after water dissociation. Thus, TiS 2 with Zigzag-L termination may be a surface to avoid in CDI device construction, given that pH fluctuations adversely affect performance. Furthermore, this work provides new understanding of TiS 2 /H 2 O interfacial features that could aid future design and optimization of TiS 2 -based CDI devices for water desalination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Mapping reactive flow patterns in monolithic nanoporous catalysts

The development of high-efficiency porous catalyst membranes critically depends on our understanding of where the majority of the chemical conversions occur within the porous structure. This then requires mapping of chemical reactions and mass transport inside the complex nanoscale architecture of porous catalyst membranes which is a multiscale problem in both the temporal and spatial domains. In order to address this problem, we developed a multiscale mass transport computational framework based on the lattice Boltzmann method that allows us to account for catalytic reactions at the gas–solid interface by introducing a new boundary condition. In good agreement with experiments, the simulations reveal that most catalytic reactions occur near the gas-flow facing side of the catalyst membrane if chemical reactions are fast compared to mass transport within the porous catalyst membrane.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Assessing entropy for catalytic processes at complex reactive interfaces

When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.

Kollias, Loukas↗