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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 1,279 records · Page 71

Accelerated Discovery and Design of Ultralow Lattice Thermal Conductivity Materials Using Chemical Bonding Principles

Semiconductors with very low lattice thermal conductivities are highly desired for applications relevant to thermal energy conversion and management, such as thermoelectrics and thermal barrier coatings. Although the crystal structure and chemical bonding are known to play vital roles in shaping heat transfer behavior, material design approaches of lowering lattice thermal conductivity using chemical bonding principles are uncommon. In this work, an effective strategy of weakening interatomic interactions and therefore suppressing lattice thermal conductivity based on chemical bonding principles is presented and a high-efficiency approach of discovering low κ L materials by screening the local coordination environments of crystalline compounds is developed. The resulting first-principles calculations uncover 30 hitherto unexplored compounds with (ultra)low lattice thermal conductivities from 13 prototype crystal structures contained in the Inorganic Crystal Structure Database. Furthermore, an approach of rationally designing high-performance thermoelectrics is demonstrated by additionally incorporating cations with stereochemically active lone-pair electrons. Here these results not only provide atomic-level insights into the physical origin of the low lattice thermal conductivity in a large family of copper/silver-based compounds but also offer an efficient approach to discover and design materials with targeted thermal transport properties.

36 MATERIALS SCIENCE↗

Machine Learning Reveals Memory of the Parent Phases in Ferroelectric Relaxors Ba(Ti$_{1-x}$,Zr x )O 3

Machine learning has been establishing its potential in multiple areas of condensed matter physics and materials science. Here, in this work, an unsupervised machine learning workflow is developed and used within a framework of first-principles-based atomistic simulations to investigate phases, phase transitions, and their structural origins in ferroelectric relaxors, Ba(Ti 1-x ,Zr x )O 3 . The applicability of the workflow is first demonstrated to identify phases and phase transitions in the parent compound, a prototypical ferroelectric BaTiO 3 . Then the workflow is applied for Ba(Ti 1-x ,Zrx)O 3 with x ≤ 0.25 to reveal i) that some of the compounds bear a subtle memory of BaTiO 3 phases beyond the point of the pinched phase transition, which could contribute to their enhanced electromechanical response; ii) the existence of peculiar phases with delocalized precursors of nanodomains—likely candidates for the controversial polar nanoregions; and iii) nanodomain phases for the largest concentrations of x.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Monolayer-like lattice dynamics in bulk WSe 2

Understanding the microscopic lattice dynamics is essential for regulating the thermal properties in two-dimensional layered materials. In transition metal dichalcogenides, the layered structures result in different but closely related phonon dispersions between monolayer and bulk. Here, by combining inelastic X-ray scattering and first-principles calculations, the lattice dynamics of tungsten diselenide (WSe 2 ) was investigated comprehensively, and a monolayer-like lattice dynamics in the bulk WSe 2 was revealed. We performed the first temperature-dependent phonon dispersions measurement and obtained the mode Grüneisen parameters of bulk WSe 2 , which are found to be in better agreement with the calculations on the monolayer system than those of the bulk. This observation indicates that lattice dynamics in bulk WSe 2 hold the characteristic of monolayers. The result provides valuable insights into the thermal properties of WSe 2 -based devices.

36 MATERIALS SCIENCE↗

Statistical Mechanics on Lattices (smol) v0.0.1

smol is a Python implementation of the Cluster Expansion Method and extensions of this methodology; which is used to fit applied lattice models from first principle calculations for subsequent use in Monte Carlo simulations for computing thermodynamic and statistical properties of atomic configuration. smol has a several notable advantages over other similar software packages. The first being its Python implementation which makes it easy to use even for users with little software and coding skills. Despite being implemented in Python, essential Monte Carlo routines are implemented in Cython such that performance is not compromised and is competitive even to similar software implemented in C/C++. Furthermore, the package has specific functionality for handling complex ionic materials (such as cathodes and electrolytes) that is not readily available in other packages. Lastly, the software has a flexible and modular design with the intention of making it fast and efficient to develop and extend the methodology.

Barroso-Luque, Luis↗

Decoupling excitons from high-frequency vibrations in organic molecules

The coupling of excitons in π-conjugated molecules to high-frequency vibrational modes, particularly carbon–carbon stretch modes (1,000–1,600 cm -1 ) has been thought to be unavoidable. These high-frequency modes accelerate non-radiative losses and limit the performance of light-emitting diodes, fluorescent biomarkers and photovoltaic devices. Here, by combining broadband impulsive vibrational spectroscopy, first-principles modelling and synthetic chemistry, we explore exciton–vibration coupling in a range of π-conjugated molecules. We uncover two design rules that decouple excitons from high-frequency vibrations. First, when the exciton wavefunction has a substantial charge-transfer character with spatially disjoint electron and hole densities, we find that high-frequency modes can be localized to either the donor or acceptor moiety, so that they do not significantly perturb the exciton energy or its spatial distribution. Second, it is possible to select materials such that the participating molecular orbitals have a symmetry-imposed non-bonding character and are, thus, decoupled from the high-frequency vibrational modes that modulate the π-bond order. We exemplify both these design rules by creating a series of spin radical systems that have very efficient near-infrared emission (680–800 nm) from charge-transfer excitons. We show that these systems have substantial coupling to vibrational modes only below 250 cm -1 , frequencies that are too low to allow fast non-radiative decay. This enables non-radiative decay rates to be suppressed by nearly two orders of magnitude in comparison to π-conjugated molecules with similar bandgaps. Our results show that losses due to coupling to high-frequency modes need not be a fundamental property of these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-consistent many-electron theory of electron work functions and surface potential characteristics for selected metals

Electron work functions, surface potentials, and electron number density distributions and electric fields in the surface region of 26 metals were calculated from first principles within the free electron model. Calculation proceeded from an expression of the total energy as a functional of the electron number density, including exchange and correlation energies, as well as a first inhomogeneity term. The self-consistent solution was obtained via a variational procedure. Surface barriers were due principally to many-body effects; dipole barriers were small only for some alkali metals, becoming quite large for the transition metals. Surface energies were inadequately described by this model, which neglects atomistic effects. Reasonable results were obtained for electron work functions and surface potential characteristics, maximum electron densities varying by a factor of over 60.

Smith, J. R.↗

The search for high-entropy fuel-cell catalysts using disorder descriptors

The transition to a hydrogen economy depends on efficient, affordable catalysts for fuel cells. Platinum—the industry standard for fuel-cell electrodes—is costly and scarce, highlighting the need for practical alternatives. High-entropy alloys offer vast compositional diversity and tunable properties that can mitigate these issues, yet their chemical complexity and configurational disorder have hindered rational discovery. Here, we introduce a data-driven framework that couples machine learning with first-principles disorder descriptors—including the entropy forming ability, disordered enthalpy-entropy descriptor, and electronic-structure similarity metrics to platinum—to predict alloy synthesizability and catalytic performance. These descriptors are applied for the first time in the context of fuel-cell catalyst discovery. The workflow rapidly screens more than 20 000 compositions and identifies several platinum-free candidates that are economically viable, readily scalable, and exhibit promising predicted activity. These results demonstrate that disorder descriptors are reliably predicted by machine learning models and can be effectively integrated into materials-discovery pipelines, accelerating innovation across complex compositional spaces.

fuel-cell catalysts↗

Negative linear compressibility in Se at ultra-high pressure above 120 GPa

A series of in situ synchrotron X-ray diffraction (XRD) measurements were carried out, combined with first-principles calculations, to study structural phase transitions of selenium at high pressures and room temperature. Several phase transitions were observed, among which an isostructural phase transition was found at around 120 GPa for the first time. Evolved from the rhombohedral (space group R$\bar{3}$m) structure (Se-V), the new phase (Se-V') exhibited an interesting increase of lattice parameter a at pressures from 120 to 148 GPa, known as negative linear compressibility (NLC). The discovery of NLC behavior observed in this work is mainly attributed to the accuracy and fine steps controlled by the membrane system for in situ XRD data collected with an exposure time of 0.5 s. After 140 GPa, a body-centered cubic (b.c.c.) structure Se-VI (space group Im$\bar{3}$m) was formed, which remains stable up to 210 GPa, the highest pressure achieved in this study. The bulk moduli of phases Se-V, Se-V' and Se-VI were estimated to be 83 ± 2, 321 ± 2 and 266 ± 7 GPa, respectively, according to the P–V curve fit by the third-order Birch–Murnaghan equation of state. The Se-V' phase shows a bulk modulus almost 4 times larger than that of the Se-V phase, which is mainly due to the effect of its NLC. NLC in a higher pressure range is always more significant in terms of fundamental mechanism and new materials discovery, yet it has barely been reported at pressures above 100 GPa. This will hopefully inspire future studies on potential NLC behaviors in other materials at ultra-high pressure.

36 MATERIALS SCIENCE↗

High Performance Parallel Methods for Space Weather Simulations

This is the final report of our NASA AISRP grant entitled 'High Performance Parallel Methods for Space Weather Simulations'. The main thrust of the proposal was to achieve significant progress towards new high-performance methods which would greatly accelerate global MHD simulations and eventually make it possible to develop first-principles based space weather simulations which run much faster than real time. We are pleased to report that with the help of this award we made major progress in this direction and developed the first parallel implicit global MHD code with adaptive mesh refinement. The main limitation of all earlier global space physics MHD codes was the explicit time stepping algorithm. Explicit time steps are limited by the Courant-Friedrichs-Lewy (CFL) condition, which essentially ensures that no information travels more than a cell size during a time step. This condition represents a non-linear penalty for highly resolved calculations, since finer grid resolution (and consequently smaller computational cells) not only results in more computational cells, but also in smaller time steps.

Hunter, Paul↗

Machine learning enabled discovery of application dependent design principles for two-dimensional materials

Abstract The unique electronic and mechanical properties of two-dimensional (2D) materials make them promising next-generation candidates for a variety of applications. Large-scale searches for high-performing 2D materials are limited to calculating descriptors with computationally demanding first-principles density functional theory. In this work, we alleviate this issue by extending and generalizing crystal graph convolutional neural networks to systems with planar periodicity and train an ensemble of models to predict thermodynamic, mechanical and electronic properties. We carry out a screening of nearly 45,000 structures for two separate applications: mechanical strength and photovoltaics. By collecting statistics of the screened candidates, we investigate structural and compositional design principles that impact the properties of the structures surveyed. Our approach recovers some well-accepted design rules: hybrid organic-inorganic perovskites with lead and tin tend to be good candidates for solar cell applications and titanium based MXenes usually have high stiffness coefficients. Interestingly, other members of the group 4 elements also contribute to increasing the mechanical strength of MXenes. For all-inorganic perovskites, we discover some compositions that have not been deeply studied in the field of photovoltaics and thus open up paths for further investigation. We open-source the code-base to spur further development in this space.

Venturi, Victor (ORCID:0000000156727549)↗

Influence of Solutocapillary Convection on Macrovoid Defect Formation in Polymeric Membranes

The focus of this research project involved the dry-cast process for polymeric membrane formation, whereby evaporation of solvent from an initially homogeneous polymer/solvent/ nonsolvent solution results in phase separation and the formation of polymer-rich and polymer-lean phases. Under certain conditions the polymer-lean phase gives rise to very large and usually undesirable, tear-drop-shaped pores (size approx. 10 - 50 microns) termed macrovoids (MVs). Although in many cases the presence of MV pores has deleterious effects on membrane performance, there are a number of innovative applications where the presence of such pores is highly desirable. Although researchers have proposed a variety of mechanisms for MV formation over the past three decades, two main hypotheses are currently favored: one asserts that MV growth can be attributed solely to diffusion (the diffusive growth hypothesis), whereas the other states that solutocapillary convection (the SC hypothesis) at the MV interface contributes to growth. The overall goal of this research was to obtain a more comprehensive understanding of the fundamental mechanism of MV growth. This research incorporates a coupled modeling and experimental approach to test a solutocapillary convection hypothesis for the growth of macrovoid pores in polymeric membranes. Specifically, we utilized a modification of the first principles model developed by two of the PIs (ARG and WBK) for dry-cast CA membranes. For the experimental component, two separate and mutually complementary approaches were used to study MV growth. In the first, membranes cast in a zero-g environment aboard the NASA KC-135 aircraft were compared with those cast on the ground to assess the effect of the buoyancy force on membrane morphology and MV size and shape. In the second approach, videomicroscopy flow visualization (VMFV) was utilized to observe MV formation and growth in real time and to assess the effect of surface tension on the MV growth dynamics. As a result of these fundamental studies, our research group advanced a new hypothesis for MV pore development in polymeric membranes.

Greenberg, Alan R.↗

Development of a Stirling System Dynamic Model With Enhanced Thermodynamics

The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.

Regan, Timothy F.↗

CFD Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

Current reduced-order thermal model for cryogenic propellant tanks is based on correlations built for flat plates collected in the 1950's. The use of these correlations suffers from inaccurate geometry representation; inaccurate gravity orientation; ambiguous length scale; and lack of detailed validation. This study uses first-principles based CFD methodology to compute heat transfer from the tank wall to the cryogenic fluids and extracts and correlates the equivalent heat transfer coefficient to support reduced-order thermal model. The CFD tool was first validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the present prediction and experimental data have been found for flows in laminar as well turbulent regimes. The convective heat transfer between the tank wall and cryogenic propellant, and that between the tank wall and ullage gas were then simulated. The results showed that the commonly used heat transfer correlations for either vertical or horizontal plate over-predict heat transfer rate for the cryogenic tank, in some cases by as much as one order of magnitude. A characteristic length scale has been defined that can correlate all heat transfer coefficients for different fill levels into a single curve. This curve can be used for the reduced-order heat transfer model analysis.

Yang, H. Q.↗

Adaptive simulations enable computational design of electron beam processing of nanomaterials with supersonic micro-jet precursor

Focused Electron Beam Induced Processing (FEBIP) is a powerful tool for the “direct-write” of nanomaterials with the possibility of atomistic control on suspended 2D material substrates. FEBIP capabilities have been significantly expanded by using a localized jet-based delivery of precursors, and especially when a thermally energized supersonic micro-jet enhances the delivery of mass flux along with controlling the far-from-equilibrium thermodynamic state of adsorbed adatoms. The possibilities of growing nanomaterials with “dialed-in” composition with ultra-high growth rates and aspect ratios up to 100:1 have been demonstrated using the supersonic micro-jet-FEBIP. Bringing this scientific discovery to the level of maturity required for practical applications in additive nanomanufacturing requires simulation tools that are capable of capturing the complex flow physics of micro-jet-substrate interactions that bridge a wide range of flow regimes from the high-density gas micro-jet expanding into the vacuum environment of FEBIP. To address this significant computational challenge, a new approach has been developed and described in this work for a multiscale adaptive DSMC (Direct Simulation Monte Carlo) algorithm to predict the micro-jet gas dynamics in an FEBIP environment, spanning the full range of flow regimes from low Knudsen (Kn) number O(0.01) continuum flow to high Kn of O(10) for the molecular flow within a unified computational framework. Here, the fundamental principles of the adaptive DSMC algorithm are described, its viability as a DSMC technique is demonstrated, and computational improvements for the benchmark cases are discussed in the context of advancing 3D nanofabrication with FEBIP. Ultimately, combining the first principle simulations via adaptive DSMC with the complementary experimental data will enable the creation of the powerful CAD tools for in silico design and optimal operation of micro-jet-FEBIP.

36 MATERIALS SCIENCE↗

Variational Self-Consistent Theory for Beam-Loaded Cavities

A new variational theory is presented for beam loading in microwave cavities. The beam{field interaction is formulated as a dynamical interaction whose stationarity according to Hamilton’s principle will naturally lead to steady-state solutions that indicate how a cavity’s resonant frequency, Q and optimal coupling coefficient will detune as a result of the beam loading. A driven cavity Lagrangian is derived from first principles, including the effects of cavity wall losses, input power and beam interaction. The general formulation is applied to a typical klystron input cavity to predict the appropriate detuning parameters required to maximize the gain (or modulation depth) in the average Lorentz factor boost, (Δ γ). Numerical examples are presented, showing agreement with the general detuning trends previously observed in the literature. The developed formulation carries several advantages for beam-loaded cavity structures. It provides a self-consistent model for the dynamical (nonlinear) beam{field interaction, a procedure for maximizing gain under beam-loading conditions, and a useful set of parameters to guide cavity-shape optimization during the design of beam-loaded systems. Enhanced clarity of the physical picture underlying the problem seems to be gained using this approach, allowing straightforward inclusion or exclusion of different field configurations in the calculation and expressing the final results in terms of measurable quantities. Two field configurations are discussed for the klystron input cavity, using finite magnetic confinement or no confinement at all. Formulating the problem in a language that is directly accessible to the powerful techniques found in Hamiltonian dynamics and canonical transformations may potentially carry an additional advantage in terms of analytical computational gains, under suitable conditions

43 PARTICLE ACCELERATORS↗

Computational Fluid Dynamics Based Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

Current reduced-order thermal model for cryogenic propellant tanks is based on correlations built for flat plates collected in the 1950's. The use of these correlations suffers from: inaccurate geometry representation; inaccurate gravity orientation; ambiguous length scale; and lack of detailed validation. The work presented under this task uses the first-principles based Computational Fluid Dynamics (CFD) technique to compute heat transfer from tank wall to the cryogenic fluids, and extracts and correlates the equivalent heat transfer coefficient to support reduced-order thermal model. The CFD tool was first validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the present prediction and experimental data have been found for flows in laminar as well turbulent regimes. The convective heat transfer between tank wall and cryogenic propellant, and that between tank wall and ullage gas were then simulated. The results showed that commonly used heat transfer correlations for either vertical or horizontal plate over predict heat transfer rate for the cryogenic tank, in some cases by as much as one order of magnitude. A characteristic length scale has been defined that can correlate all heat transfer coefficients for different fill levels into a single curve. This curve can be used for the reduced-order heat transfer model analysis.

Yang, H. Q.↗

Quantum Phase Engineering of Two-Dimensional Post-Transition Metals by Substrates: Toward a Room-Temperature Quantum Anomalous Hall Insulator

In this work, we propose a new strategy to engineer topological and magnetic properties of two-dimensional (2D) hexagonal lattices consisting of post-transition metals. Our first-principles calculations demonstrate that substrates serve as templates to form 2D lattices with high thermodynamic stability, where their topological properties as well as magnetic properties sensitively change as a function of lattice constants, i.e., the system undergoes a first-order phase transition from nonmagnetic to ferromagnetic state above a critical lattice constant. Consequently, substrates can be used to explore versatile magnetic, electronic, and quantum topological properties. We establish phase diagrams of versatile quantum phases in terms of exchange coupling and spin–orbit coupling effectively tuned by the lattice constants. We further reveal the first room-temperature quantum anomalous Hall (QAH) effect, i.e., Sn on 2√3 × 2√3 graphane is a QAH insulator with a large spin–orbit coupling gap of ~0.2 eV and a Curie temperature of ~380 K by using the 2D anisotropic Heisenberg model.

36 MATERIALS SCIENCE↗

Fermion–boson many-body interplay in a frustrated kagome paramagnet

Kagome-nets, appearing in electronic, photonic and cold-atom systems, host frustrated fermionic and bosonic excitations. However, it is rare to find a system to study their fermion–boson many-body interplay. Here we use state-of-the-art scanning tunneling microscopy/spectroscopy to discover unusual electronic coupling to flat-band phonons in a layered kagome paramagnet, CoSn. We image the kagome structure with unprecedented atomic resolution and observe the striking bosonic mode interacting with dispersive kagome electrons near the Fermi surface. At this mode energy, the fermionic quasi-particle dispersion exhibits a pronounced renormalization, signaling a giant coupling to bosons. Through the self-energy analysis, first-principles calculation, and a lattice vibration model, we present evidence that this mode arises from the geometrically frustrated phonon flat-band, which is the lattice bosonic analog of the kagome electron flat-band. Our findings provide the first example of kagome bosonic mode (flat-band phonon) in electronic excitations and its strong interaction with fermionic degrees of freedom in kagome-net materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗