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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A First Principles Approach to Spectral Phonon Transport in Heterostructures

Understanding thermal transport across interfaces which give rise to a thermal resistance (also known as Kapitza resistance) is a critical issue affecting the development of nanotechnologies. Much modern and emergent nanotechnology consist of adjacent materials, and phonon mediated heat transfer governs thermal behavior across internal interfaces in these devices. The physics of thermal transport in solids are governed both by phenomena occurring at the atomic scale and interactions with the material's microstructure. The forecasting of fundamental quantities such as temperature, heat flux and thermal conductivity typically employs the semi-classical Boltzmann transport equation to predict the macroscopic behavior of materials in terms of the microscopic dynamics of its heat carriers. Kapitza resistance was first discovered in liquid helium experiments and has led to a fundamental research thrust in micro and nano-scale heat transport, the behavior of thermal carriers across internal interfaces. Thermal interfacial resistance (TIR) is a widely studied phenomenon, first engaged by Swartz and Pohl through their development of the acoustic and diffuse mismatch methods, then continued through myriad efforts with varying methods and approaches in an attempt to resolve carrier behavior at thermal interfaces. Many of the fundamental approaches to TIR have been at the nanoscale, and research is conducted with molecular dynamics (MD) and density functional theory (DFT) methods. The limitations of these methods is system size; atomistic methods tend to be limited to system sizes of 100,000 atoms or less. Larger length-scale methods have also been pursued, based on the principles of acoustic or diffuse mismatch, but not all include simulation of TIR using a full phonon band spectrum, or temperature dependent methods. Our approach to enabling phonon transport in layered materials draws upon our previous work of demonstrating spectrally coupled phonon transport in homogeneous and heterogeneous materials. We use a semi-analytical approach in which the Bose-Einstein (B-E) statistics set the strength of the phonon radiance in a frequency group, but the B-E statistics are informed with information from the transport system. The B-E statistics in a single frequency group feels the influence of all the groups through the spatial temperature. We also include a new field term which is an indicator of the amount of non-equilibrium behavior of the phonon spectrum---this is added to the phonon source term in all groups to ensure closure and conservation of energy, as the phonon groups in the transport system and the analytical systems are coupled. This work builds upon our previous approach by adding a phonon coupling term at an internal interface, using the principles of the DMM through transmission and reflection coefficients. In this work, the coefficients are determined through computing a common temperature at the interface, influenced by the phonon band structure of both materials, in effect, providing mixing between the two material systems and using the common temperature to set the strength of the phonon radiance at the boundaries on either side of the interface. Our approach uses material properties computed along various crystallographic orientations, and while some isotropy is built into the interface condition, the material properties weight the phonon distributions in the proper crystalline direction. Greater resolution of phonon behavior in proximity to an interface, and more accurate predictions of TIR are obtained. While it is true the assumption of diffuse mismatch can yield inconsistent results compared to experiment especially at low temperatures, this work focuses on room temperature and beyond effects, for future applications in nuclear fuel, or thermoelectric devices; a modified mismatch approach may be feasible if applied properly. Additionally, our methods focus on bridging mesoscale to engineering scale

36 MATERIALS SCIENCE↗
DOE OSTI2022

Impact of Irradiation-induced Lattice Defects and Dopants on Thermal Transport in Oxide Nuclear Fuels

Advanced nuclear reactor concepts aim to use fuels that must withstand unprecedented temperature and radiation extremes. In these fuels, thermal energy transport under irradiation is directly related to fuel longevity, reactor safety, and is arguably one of the most important performance metrics. Here we provide a comprehensive, first-principles-informed treatment of phonon mediated thermal transport in a defect-bearing actinide oxide with direct comparison to experimental measurements. Pristine and proton irradiated thorium dioxide was chosen as a model system to treat the complexity of thermal transport in the presence of lattice defects. A thermal transport model is implemented using the linearized Boltzmann transport equation (LBTE) with input from first principles calculations and defect evolution models. The output of the LBTE is compared directly to mesoscopic measurements of thermal conductivity on length scales commensurate with defect accumulation. Parametric measurements of conductivity with irradiation dose and temperature reveal a monotonic decrease in conductivity with irradiation dose, in the range of 0.001 dpa to 0.1 dpa. Besides radiation-induced defects, doping the thorium dioxide crystal with small quantities of uranium atoms also results in a drastic reduction in thermal conductivity. Temperature-dependent measurements of thermal conductivity in uranium-doped thorium dioxide single crystals suggests a resonant scattering mechanism is responsible for the observed reduction. This comprehensive, atomistic- to meso-scale treatment provides the necessary basis to investigate thermal transport under irradiation in more complex systems that exhibit strong electron correlation. This is a poster presentation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Grain Boundary-Limited Thermal Transport in Suspended Thin Graphite across an Unexplored Thickness Regime

Here, we present systematic thermal conductivity (κ) measurements of suspended thin graphite ribbons, 234–527 nm thick, using a four-probe 3ω method. Unlike recent reports of phonon hydrodynamics and exceptionally high κ in micrometer-thick graphite ( Science, 2020), we observe significantly lower κ and no signatures of collective phonon flow in this intermediate thickness regime. Instead, our measured κ lies between few-layer graphene and bulk graphite. These results agree with a first-principles-informed Peierls–Boltzmann transport model with spatially resolved Monte Carlo sampling. Additionally, the temperature for the peak κ shifts lower with increasing thickness, due to the interplay of phonon-boundary and phonon-isotope scattering. Incorporating grain boundary scattering into simulations is necessary to replicate the experimental trends. These findings delineate the boundary between ballistic, hydrodynamic, and diffusive transport regimes in graphite and underscore the dominant role of disorder and geometry in phonon transport in quasi-two-dimensional materials, offering insights for nanoscale thermal management.

Boltzmann transport model↗
DOE OSTI2024

Impact of classical statistics on thermal conductivity predictions of BAs and diamond using machine learning molecular dynamics

Machine learning interatomic potentials (MLIPs) have greatly enhanced molecular dynamics (MD) simulations, achieving near-first-principles accuracy in thermal conductivity studies. In this work, we reveal that this accuracy, observed in BAs and diamond at sub-Debye temperatures, stems from an accidental error cancelation: classical statistics overestimates specific heat while underestimating phonon lifetimes, balancing out in thermal conductivity predictions. However, this balance is disrupted when isotopes are introduced, leading MLIP-based MD to significantly underpredict thermal conductivity compared to experiments and quantum statistics-based Boltzmann transport equation. This discrepancy arises not from classical statistics affecting phonon–isotope scattering rates but from its impact on the interplay between phonon–isotope and phonon–phonon scattering in the normal scattering-dominated BAs and diamond. In conclusion, this work underscores the limitations of MLIP-based MD for thermal conductivity studies at sub-Debye temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Characteristics Approach to the Finite Element Method

Herein, we present a new method for solving the linear Boltzmann transport equation. Two commonly used and well-understood methods for solving partial differential equations are the method of characteristics (MOC) and the finite element method (FEM). We propose a new method that combines the fundamental concept of the FEM with the analytic solution from the MOC to obtain coefficients for the FEM basis function expansion. Traditionally, coefficients for the FEM basis function expansion are obtained via matrix inversion. Instead, we solve for the coefficients with the MOC and represent the underlying fields with the basis function expansion using these coefficients. We provide a convergence study for our method with results from two sets of FEM basis functions: Gauss-Legendre and Gauss-Lobatto sets. We also compare two different variations of our method categorized as short characteristics and intermediate characteristics.

42 ENGINEERING↗
DOE OSTI2022

Anisotropic-strain-enhanced hole mobility in GaN by lattice matching to ZnGeN 2 and MgSiN 2

The key obstacle toward realizing integrated gallium nitride (GaN) electronics is its low hole mobility. Here, we explore the possibility of improving the hole mobility of GaN via epitaxial matching to II–IV nitride materials that have recently become available, namely, ZnGeN 2 and MgSiN 2 . We perform state-of-the-art calculations of the hole mobility of GaN using the ab initio Boltzmann transport equation. We show that effective uniaxial compressive strain of GaN along the [$1\bar{1}00$] by lattice matching to ZnGeN 2 and MgSiN 2 results in the inversion of the heavy hole band and split-off hole band, thereby lowering the effective hole mass in the compression direction. We find that lattice matching to ZnGeN 2 and MgSiN 2 induces an increase in the room-temperature hole mobility by 50% and 260% as compared to unstrained GaN, respectively. Further, examining the trends as a function of strain, we find that the variation in mobility is highly nonlinear; lattice matching to a hypothetical solid solution of Zn 0.75 Ge 0.75 Mg 0.25 Si 0.25 N 2 would already increase the hole mobility by 160%.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reduced order models for thermal radiative transfer problems based on moment equations and data-driven approximations of the Eddington tensor

Here a new group of structure and asymptotic preserving reduced-order models (ROMs) for multidimensional nonlinear thermal radiative transfer (TRT) problems is presented. They are formulated by means of the nonlinear projective approach and data compression techniques. The nonlinear projection is applied to the Boltzmann transport equation (BTE) to derive a hierarchy of low-order moment equations. Approximation of the Eddington tensor that provides exact closure for the system of moment equations is found with projection-based data-driven methodologies. These include the (i) proper orthogonal decomposition (POD), (ii) dynamic mode decomposition (DMD) and (iii) a variant of the DMD. A parameterization is derived for this ROM for the temperature of radiation incoming to the problem domain (the radiation drive temperature). This parameterization is informed from results of a dimensionless study of the TRT problem. Analysis of the ROMs is performed on the classical Fleck-Cummings TRT multigroup test problem in 2D geometry with a radiation-driven Marshak wave. Numerical results are presented to demonstrate the performance of these ROMs for the simulation of evolving radiation and heat waves. Results show these models to be sufficiently accurate for practical computations with rather low-rank representations of the Eddington tensor. As the rank of the approximation is increased, the errors of solutions generated by the ROMs gradually decreases.

42 ENGINEERING↗
DOE OSTI2022

Accelerated computation of lattice thermal conductivity using neural network interatomic potentials

We report with the development of the density functional theory (DFT) and ever-increasing computational capacity, an accurate prediction of lattice thermal conductivity based on the Boltzmann transport theory becomes computationally feasible, contributing to a fundamental understanding of thermal conductivity as well as a choice of the optimal materials for specific applications. However, steep costs in evaluating third-order force constants limit the theoretical investigation to crystals with high symmetry and few atoms in the unit cell. Currently, machine learning potentials are garnering attention as a computationally efficient high-fidelity model of DFT, and several studies have demonstrated that the lattice thermal conductivity could be computed accurately via the machine learning potentials. However, test materials were mostly crystals with high symmetries, and the applicability of machine learning potentials to a wide range of materials has yet to be demonstrated. Furthermore, establishing a standard training set that provides consistent accuracy and computational efficiencies across a wide range of materials would be useful. To address these issues, herein we compute lattice thermal conductivities at 300 K using neural network interatomic potentials. As test materials, we select 25 materials with diverse symmetries and a wide range of lattice thermal conductivities between 10 -1 and 10 3 Wm -1 K -1 . Among various choices of training sets, we find that molecular dynamics trajectories at 50–700 K consistently provide results at par with DFT for the test materials. In contrast to pure DFT approaches, the computational cost in the present approach is uniform over the test materials, yielding a speed gain of 2–10 folds. When a smaller reduced training set is used, the relative efficiency increases by up to ~50 folds without sacrificing accuracy significantly. The current work will broaden the application scope of machine learning potentials by establishing a robust framework for accurately computing lattice thermal conductivity with machine learning potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Wide-range continuous tuning of the thermal conductivity of La0.5Sr0.5CoO3-δ films via room-temperature ion-gel gating

Abstract Solid-state control of the thermal conductivity of materials is of exceptional interest for novel devices such as thermal diodes and switches. Here, we demonstrate the ability to continuously tune the thermal conductivity of nanoscale films of La 0.5 Sr 0.5 CoO 3- δ (LSCO) by a factor of over 5, via a room-temperature electrolyte-gate-induced non-volatile topotactic phase transformation from perovskite (with δ ≈ 0.1) to an oxygen-vacancy-ordered brownmillerite phase (with δ = 0.5), accompanied by a metal-insulator transition. Combining time-domain thermoreflectance and electronic transport measurements, model analyses based on molecular dynamics and Boltzmann transport equation, and structural characterization by X-ray diffraction, we uncover and deconvolve the effects of these transitions on heat carriers, including electrons and lattice vibrations. The wide-range continuous tunability of LSCO thermal conductivity enabled by low-voltage (below 4 V) room-temperature electrolyte gating opens the door to non-volatile dynamic control of thermal transport in perovskite-based functional materials, for thermal regulation and management in device applications.

42 ENGINEERING↗
NASA NTRS2010

GUI to Facilitate Research on Biological Damage from Radiation

A graphical-user-interface (GUI) computer program has been developed to facilitate research on the damage caused by highly energetic particles and photons impinging on living organisms. The program brings together, into one computational workspace, computer codes that have been developed over the years, plus codes that will be developed during the foreseeable future, to address diverse aspects of radiation damage. These include codes that implement radiation-track models, codes for biophysical models of breakage of deoxyribonucleic acid (DNA) by radiation, pattern-recognition programs for extracting quantitative information from biological assays, and image-processing programs that aid visualization of DNA breaks. The radiation-track models are based on transport models of interactions of radiation with matter and solution of the Boltzmann transport equation by use of both theoretical and numerical models. The biophysical models of breakage of DNA by radiation include biopolymer coarse-grained and atomistic models of DNA, stochastic- process models of deposition of energy, and Markov-based probabilistic models of placement of double-strand breaks in DNA. The program is designed for use in the NT, 95, 98, 2000, ME, and XP variants of the Windows operating system.

Cucinotta, Frances A.↗
DOE OSTI2025

OpenSn: A massively parallel, open-source simulation environment for discrete ordinates radiation transport

OpenSn is an open-source, massively parallel deterministic radiation transport code for solving the discrete-ordinates ( S N ) form of the Boltzmann transport equation on unstructured, arbitrary polyhedral meshes. It supports high-fidelity simulations involving steady-state, eigenvalue, and adjoint problems for neutral particles (e.g., neutrons, photons, multi-particles), using the multigroup approximation in energy. OpenSn combines angular discretization via discrete ordinates with a discontinuous Galerkin finite element method (DGFEM) in space, enabling accurate resolution of transport physics on arbitrary polyhedral cells, included locally refined spatial grids. It includes multiple angular quadrature types, including locally refined angular quadratures. Written in modern C++ with a Python API, OpenSn runs efficiently on platforms ranging from laptops to supercomputers. The transport sweep algorithm is implemented using a task-based, directed-acyclic-graph (DAG) approach for each angle and supports asynchronous parallelism across thousands of MPI ranks. Group-set aggregation improves compute intensity, and synthetic acceleration techniques (e.g., diffusion synthetic acceleration, second-moment method) enhance solver convergence. OpenSn has been verified on reactor physics problems and demonstrated excellent weak and strong scaling performance on more than 32,768 processes, making it a versatile and robust platform for large-scale transport simulations in complex geometries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

MPACT 4.4 Theory Manual

MPACT is a three-dimensional (3D) full-core neutron transport code capable of calculating subpin power distributions. Calculations are based on the Boltzmann transport equation for neutron fluxes for problems in which the detailed geometrical configuration of fuel components such as the pellet and cladding are explicitly retained. The cross-section data needed for the neutron transport calculation are obtained directly from a multigroup cross section library, which has traditionally been used by lattice physics codes to generate few-group homogenized cross sections for nodal core simulators. Hence, MPACT assumes neither a priori homogenization nor group condensation for the full core spatial solution. The 3D MPACT transport solution can be obtained using the method of characteristics (MOC), which employs discrete ray tracing within each fuel pin. However, for practical reactor applications, the direct application of MOC to 3D core configurations requires an excessive amount of memory and computing time due to the very large number of rays. For practical 3D full-core calculations, MPACT commonly uses an approximate “2D/1D” method that treats the radial (x and y) variables differently from the axial (z) variable. In particular, the radial dependence of the solution is calculated using transport theory, and the axial dependence is calculated using diffusion or P 3 theory. The 2D/1D method requires the core to be divided into a vertical stack of axial slices with a thickness of Δ z ≈ 5–10 cm. Each axial slice is divided radially into coarse spatial cells with boundaries that usually constitute the pin cell boundaries, for which Δ x = Δ y ≈ 1.5 cm. Then, each coarse radial cell (pin cell) is divided into 50–100 fine radial cells, which resolve the angular flux in the fuel, cladding, and moderator regions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

SCEPTRE 2.7 User's Guide

Sandia’s Computational Engine for Particle Transport for Radiation Effects (SCEPTRE) is a computer code that solves the linear Boltzmann transport equation, particularly targeting coupled photon-electron problems. It uses unstructured finite element meshes in space, multigroup in energy, and discrete ordinates (Sn) or other methods in angle. SCEPTRE uses an xml-based input file to specify the problem. This report documents the options and syntax of that input file.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

SCEPTRE 2.6 User's Guide

Sandia’s Computational Engine for Particle Transport for Radiation Effects (SCEPTRE) is a computer code that solves the linear Boltzmann transport equation, particularly targeting coupled photon-electron problems. It uses unstructured finite element meshes in space, multigroup in energy, and discrete ordinates (S n ) or other methods in angle. SCEPTRE uses an xml-based input file to specify the problem. This report documents the options and syntax of that input file.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

First-Principles Studies on Sc 2 RuZ (Z = Si, Ge, Sn) Inverse Heusler Alloys: Structural, Electronic, and Transport Properties

The continuous demand for efficient, nontoxic, and thermally stable materials for room-temperature energy conversion motivates the exploration of novel thermoelectric systems beyond the traditional magnetic Heusler alloys. While full and half-Heusler compounds, especially Co-, Ni-, and Mn-based systems, have demonstrated promising thermoelectric properties, their typically high operating temperatures and magnetic complexities limit their applicability in ambient thermal management. In this context, we investigate whether Sc-based inverse Heusler alloys can offer a viable nonmagnetic alternative with competitive thermoelectric performance. In this work, we perform a systematic first-principles study of the inverse Heusler compounds Sc 2 RuZ (Z = Si, Ge, Sn), focusing on their structural, electronic, mechanical, and thermodynamic-thermoelectric properties. Density Functional Theory (DFT) was employed to compute optimized lattice structures and band dispersion, while dynamical stability was assessed via phonon calculations. Thermoelectric transport coefficients, including Seebeck coefficient, electrical conductivity, and thermal conductivity, were estimated using the semiclassical Boltzmann transport theory within the constant relaxation time approximation. Our results show that all Sc 2 RuZ compounds are thermodynamically stable semiconductors with indirect band gaps of 0.12–0.16 eV and exhibit high elastic moduli, especially Sc 2 RuSn, which demonstrates superior stiffness and incompressibility. Importantly, all compounds display promising room-temperature thermoelectric characteristics, including high Seebeck coefficients and power factors. These findings reveal that Sc 2 RuZ alloys represent a rare class of stable, nonmagnetic inverse Heusler semiconductors with intrinsic thermoelectric potential at room temperature, unlike many existing Heusler systems optimized for spintronics or high-temperature operation. This work expands the known design space for Heusler-based thermoelectrics and offers a theoretical basis for experimental realization of efficient, low-temperature, nonmagnetic thermoelectric materials.

alloys↗
DOE OSTI2022

Mesoscopic finite-size effects of unconventional electron transport in PdCoO 2

A wide range of unconventional transport phenomena has recently been observed in single-crystal delafossite metals. Here, we present a theoretical framework to elucidate electron transport using a combination of first-principles calculations and numerical modeling of the anisotropic Boltzmann transport equation. Using PdCoO 2 as a model system, we study different microscopic electron and phonon scattering mechanisms and establish the mean free path hierarchy of quasiparticles at different temperatures. We treat the anisotropic Fermi surface explicitly to numerically obtain experimentally-accessible transport observables, which bridge between the “diffusive,” “ballistic,” and “hydrodynamic” transport regime limits. Further, we illustrate that the distinction between the “quasiballistic” and “quasihydrodynamic” regimes is challenging and often needs to be quantitative in nature. From first-principles calculations, we populate the resulting transport regime plots and demonstrate how the Fermi surface orientation adds complexity to the observed transport signatures in micrometer-scale devices. Our work provides key insights into microscopic interaction mechanisms on open hexagonal Fermi surfaces and establishes their connection to the macroscopic electron transport in finite-size channels.

36 MATERIALS SCIENCE↗