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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optimized Highly Efficient SSCB Using Organic Substrate Packaging for Electric Vehicle Applications

Solid State Circuit Breakers (SSCBs) are an attractive protection solution for their arcless current interruption and fast actuation speeds over mechanical breakers. This paper proposes a Bidirectional SSCB (BSSCB) with a thermally defined and digitally controlled current time profile for fault protection in EV and other low-voltage DC systems. The paper proposes an organic packaging approach utilizing flex circuitry to develop a reliable, cost-effective power module for BSSCBs. The paper studies transient heat transfer in the power modules using finite element analysis (FEA). An RC themal ladder network is extracted to define a fusing curve. To demonstrate and verify the design, a 1kV/50 A SiC MOSFET BSSCB prototype is fabricated and tested, having a power density of 60 W/cm3 and 4x reduction in form factor over presently researched breakers. Also, given are results for 750 V/150 A operation showing interruption in 2.4 μs.

organic power packaging↗
DOE OSTI2022

Evaluation of PV Module Packaging Strategies of Monofacial and Bifacial PERC Using Degradation Pathway Network Modeling

As the PV industry is rapidly expanding, it is important to thoroughly investigate the long-term impact of packaging strategies on the performance of PV modules. In this study, the variants in sets differ on the basis of manufacturer (A/B), encapsulant (EVA/POE), rear encapsulant (UV-cutoff/opaque/transparent), module architecture (GB/DG) and cell type (monofacial/bifacial). The minimodules were exposed for 2520 hours in modified damp heat, with or without full spectrum light. Every 504 hours, stepwise electrical characterization techniques were employed to track changes in minimodules. Degradation pathway modeling using network structural equation modeling was employed to study pairwise relationships between variables and service lifetime prediction in minimodules. Through this study, differences in quality control are identified in minimodules made by different manufacturers. Minimodules with UV-cutoff rear encapsulant show relatively better stability, whereas the ones with opaque rear encapsulant show greater power loss. In addition, GB having UV-cutoff rear encapsulation and GB with POE having opaque rear encapsulation were identified to be stable as they lack a best model fit. Here, the primary power loss mechanism in degrading variants is interconnect corrosion.

14 SOLAR ENERGY↗
DOE OSTI2020

Determining Outgassing of Foam Packaging Material

When transporting highly radioactive material, it is vital to provide a successful delivery. Without proper containment, radioactive materials can become exposed to the surrounding environment and pose a serious threat. To ensure a safe transition of radioactive material, packaging components must be able to withstand high levels of heat during the event of a fire while maintaining the integrity of the structure to safety contain the radioactive material. Various types of polyurethane and silicone have been selected to observe at high temperatures to analyze outgassing characteristics of the materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Load-Packaged AC/DC and DC/DC Power Electronics Converter Performance Data

This data set contains experimentally characterized performance data from load-packaged alternating current to direct current (AC/DC) and direct current to direct current (DC/DC) power electronics converters associated with lighting devices and miscellaneous electrical loads typically found in commercial buildings in the United States. The data set contains input power, output power, efficiency, and harmonic spectrum data for 58 AC/DC converters and 35 DC/DC converters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Pyomo.DOE: An open-source package for model-based design of experiments in Python

Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.

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

Implementation of real‐time TDDFT for periodic systems in the open‐source PySCF software package

Abstract We present a new implementation of real‐time time‐dependent density functional theory (RT‐TDDFT) for calculating excited‐state dynamics of periodic systems in the open‐source Python‐based PySCF software package. Our implementation uses Gaussian basis functions in a velocity gauge formalism and can be applied to periodic surfaces, condensed‐phase, and molecular systems. As representative benchmark applications, we present optical absorption calculations of various molecular and bulk systems and a real‐time simulation of field‐induced dynamics of a (ZnO) 4 molecular cluster on a periodic graphene sheet. We present representative calculations on optical response of solids to infinitesimal external fields as well as real‐time charge‐transfer dynamics induced by strong pulsed laser fields. Due to the widespread use of the Python language, our RT‐TDDFT implementation can be easily modified and provides a new capability in the PySCF code for real‐time excited‐state calculations of chemical and material systems.

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

A Study on Recycled Polymers Recovered from Multilayer Plastic Packaging Films by Solvent–Targeted Recovery and Precipitation (STRAP)

Multilayer plastic film use increased in multiple packaging applications due to its versatility and overall increased performance over monolayer structures. However, the performance gains from multiple layers also make recycling difficult because they contain multiple polymers that can be immiscible and burdensome to traditional mechanical recycling operations. A possible solution is the solvent-targeted recovery and precipitation (STRAP) process, but the effect on the retrieved polymer is still unknown. Here, the STRAP process is applied to two different multilayer films and samples of recovered polymers are evaluated for physical, molecular, and thermal properties. Changes in the molecular weight are not significant, but differences in thermal properties are reported along with the coprecipitation of different polymers. Solvent retention in the polymer matrix from STRAP reduced the glass transition temperature of samples, but enhanced drying recovered it. Heavy metals, such as Cd, Cr, and Pb are not detected, indicating regulatory compliance for different applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

PTM‐Psi : A python package to facilitate the computational investigation of p ost‐ t ranslational m odification on p rotein s tructures and their i mpacts on dynamics and functions

Abstract Post‐translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python‐based workflow, called PTM‐Psi , integrates several established open‐source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non‐standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S ‐nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM‐Psi for interpreting sequence–structure–function relationships derived from thiol redox proteomics data. We demonstrate that the S ‐nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

TeraChem: A graphical processing unit-accelerated electronic structure package for large-scale ab initio molecular dynamics

TeraChem was born in 2008 with the goal of providing fast on-the-fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low-cost parallel computer architecture that became more accessible for general-purpose GPU computing with the release of CUDA in 2007. The evaluation of the electron repulsion integrals (ERIs) is a major bottleneck in electronic structure codes and provides an attractive target for acceleration on GPUs. Thus, highly efficient routines for evaluation of and contractions between the ERIs and density matrices were implemented in TeraChem. Here, electronic structure methods were developed and implemented to leverage these integral contraction routines, resulting in the first quantum chemistry package designed from the ground up for GPUs. This GPU acceleration makes TeraChem capable of performing large-scale ground and excited state calculations in the gas and condensed phase. Today, TeraChem's speed forms the basis for a suite of quantum chemistry applications, including optimization and dynamics of proteins, automated and interactive chemical discovery tools, and large-scale nonadiabatic dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

A Package of Momentum and Heat Transfer Coefficients for the Stable Surface Layer Extended by New Coefficients over Sea Ice

The bulk transfer coefficients of momentum, heat, and humidity belong to the main ingredients of numerical weather prediction and climate models. They are needed for the calculation of turbulent fluxes in the surface layer and often rely on the Monin–Obukhov similarity theory requiring universal stability functions. The problem of a derivation of transfer coefficients based on different stability functions has been considered by many researchers over the years but it remains to this day. In this work, dedicated to the memory of S.S. Zilitinkevich, we also address this task, and obtain transfer coefficients from three pairs of theoretically derived stability functions suggested by Zilitinkevich and co-authors for stable conditions. Additionally, we construct non-iterative parametrizations of these transfer coefficients based on earlier work. Results are compared with state-of-the-art coefficients for land, ocean, and sea ice. The combined parametrizations form a package in a universal framework relying on a semi-analytical solution of the Monin-Obukhov similarity theory equations. A comparison with data of the Surface Heat Budget of the Arctic Ocean campaign (SHEBA) over sea ice reveals large differences between the coefficients for land conditions and the measurements over sea ice. However, two schemes of Zilitinkevich and co-authors show, after slight modification, good agreement with SHEBA although they had not been especially developed for sea ice. One pair of the modified transfer coefficients is superior and is compatible to earlier SHEBA-based parametrizations. Finally, an algorithm for practical use of all transfer coefficients in climate models is given.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CASM — A software package for first-principles based study of multicomponent crystalline solids

CASM is a software package that enables first-principles based studies of crystalline materials. It has been designed to treat coupled chemical, mechanical, vibrational, and magnetic degrees of freedom to determine ground state and finite temperature properties of crystals. The symmetry of the underlying parent crystal structure is used to enumerate perturbations of the parent crystal structure and generate derivative structures which can be input to first-principles calculations in order to explore the ground state energy landscape. CASM algorithmically constructs cluster expansions that fully couple discrete and continuous degrees of freedom, and generates highly efficient code to evaluate the cluster expansion basis functions. Widely used machine learning methods are integrated for fitting expansion coefficients to first-principle calculations. The fully parameterized cluster expansions can be combined with (kinetic) Monte Carlo methods to calculate finite temperature thermodynamic and kinetic properties. CASM Alloy Manager identifies distinct parent crystal structures in an alloy system, creating individual projects for each, and integrating the results. The integrated infrastructure facilitates the linkage between first-principles statistical mechanics predictions with higher length scale computational methods, such as phase field simulations. In conclusion, CASM projects are designed to be easy to share in repositories, to re-use, and to extend to include additional chemical species or types of degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2021

$\mathrm{Perturbo}$: A software package for ab initio electron–phonon interactions, charge transport and ultrafast dynamics

We report Perturbo is a software package for first-principles calculations of charge transport and ultrafast carrier dynamics in materials. The current version focuses on electron–phonon interactions and can compute phonon-limited transport properties such as the conductivity, carrier mobility and Seebeck coefficient. It can also simulate the ultrafast nonequilibrium electron dynamics in the presence of electron–phonon scattering. Perturbo uses results from density functional theory and density functional perturbation theory calculations as input, and employs Wannier interpolation to reduce the computational cost. It supports norm-conserving and ultrasoft pseudopotentials, spin–orbit coupling, and polar electron–phonon interactions for bulk and 2D materials. Hybrid MPI plus OpenMP parallelization is implemented to enable efficient calculations on large systems (up to at least 50 atoms) using high-performance computing. Taken together, Perturbo provides efficient and broadly applicable ab initio tools to investigate electron–phonon interactions and carrier dynamics quantitatively in metals, semiconductors, insulators, and 2D materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

SuperScreen: An open-source package for simulating the magnetic response of two-dimensional superconducting devices

Quantitative understanding of the spatial distribution of magnetic fields and Meissner screening currents in two-dimensional (2D) superconductors and mesoscopic thin film superconducting devices is critical to interpreting the results of magnetic measurements of such systems. Here, we introduce SuperScreen, an open-source Python package for simulating the response of 2D superconductors to trapped flux and applied time-independent or quasi-DC magnetic fields for any value of the effective magnetic penetration depth, Λ. Given an applied magnetic field, SuperScreen solves the 2D London equation using an efficient matrix inversion method to obtain the Meissner currents and magnetic fields in and around structures composed of one or more superconducting thin films of arbitrary geometry. Further, SuperScreen can be used to model screening effects and calculate self- and mutual-inductance in thin film superconducting devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models

We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.

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

RANSBox: A zero-dimensional modular software package for Reynolds-averaged Navier-Stokes modeling

RANSBox is a zero-dimensional software package for Reynolds-averaged Navier-Stokes (RANS) modeling developed at Lawrence Livermore National Laboratory to support common implementation of RANS models across a variety of host codes with different numerical schemes and code bases. Herein this work describes the key features of RANSBox including “model-agnostic integration,” which allows new models to be implemented in RANSBox and quickly deployed to host codes without additional changes to the host code base. Three one-dimensional test problems with analytical asymptotic properties are described which can be used to verify correctness of RANSBox integration. Results for these problems are then compared across different RANS models in a single code and across different codes with a common RANS model. By using a common model implementation in RANSBox, host codes with different numerical schemes and formal orders of accuracy are demonstrated to predict the expected behavior for the three test problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

HydroEcoLSTM: A Python package with graphical user interface for hydro-ecological modeling with long short-term memory neural network

Machine learning (ML) is emerging as a promising tool for modeling hydro-ecological processes due to the increasing availability of large environmental data. However, the use of ML requires sufficient programming knowledge due to a lack of a graphical user interface (GUI). In this study, we introduced a GUI package, named HydroEcoLSTM, with the long short-term memory network (LSTM) as the core model, that allows non-ML experts to utilize their domain knowledge to construct complex ML models. We demonstrated the functionalities of HydroEcoLSTM with two practical examples, including (1) predictions of streamflow in both gauged and ungauged catchments and (2) predictions of multiple outputs (i.e., streamflow and isotope transport from two catchments). The simulation results obtained in both case experiments are satisfactory. In the first example, the average Nash–Sutcliffe Efficiency (NSE) for streamflow simulation during the testing period is 0.79 while the application of the trained model in two assumed ungauged catchments also achieves the average NSE of 0.68. In the second example, the average NSE for streamflow and instream isotope simulation during the testing period is 0.71. Ultimately, applications of HydroEcoLSTM with real-world examples demonstrate its potential use for practical applications and research without requiring extensive coding skills.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Comprehensive Chemistry Evaluation and Diagnostics Package for E3SM – ChemDyg Version 1.1.0

The Chemistry Evaluation and Diagnostics Package (ChemDyg) is an open-source tool designed for the Energy Exascale Earth System Model (E3SM) developed by the U.S. Department of Energy. ChemDyg facilitates routine evaluation, tailored development, and in-depth analysis of atmospheric chemistry through its modular architecture, allowing users to compare model outputs with observational data. Version 1.1.0 introduces a robust set of diagnostic capabilities, including climatology, time evolution of key tracers, diurnal and annual cycle analyses, and extensive budget diagnostics. These features help identify model discrepancies and enhance the representation of atmospheric chemistry in E3SM. Each self-contained diagnostic set includes dedicated scripts and documentation for ease of use. The interactive HTML output improves data accessibility, accelerating chemistry model development. Additionally, ChemDyg's flexible framework allows for customization, enabling users to create unique diagnostic sets for specific scientific contributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗