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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Investigation of Exciton Delocalization and Exciton Coherence in Chromophores and Acoustic Nanostructures

Quantum materials have a rich potential for providing transformative energy technologies ranging from new energy efficient computation paradigms to lossless energy transport across the national grid. The field of quantum materials, however, is still in its infancy with many quantum materials systems requiring cyrogenic temperatures to be viable. Few viable, room-temperature quantum materials systems have been identified; therefore, identifying additional such systems is vitally important. This state of the science combined with the low number of potential systems that exhibit room-temperature quantum character make this field of research fertile ground for EPSCoR states (states eligible for funding under the Established Program to Stimulate Competitive Research program) such as Idaho to compete on a national level. As a result, this project proposed and accomplished two main goals in advancing two room-temperature quantum materials systems: (1) advance the science for demonstrating room temperature exciton delocalization in two excitonic systems and (2) build capacity and expertise in developing and understanding quantum materials at both Boise State University and Idaho National Laboratory. The work at Boise State focused mainly on the use of nucleic acid self-assembled chromophore molecule networks that offer a much easier and mature approach to construct aggregates of chromophores that can be tailored to specific two-dimensional and three-dimensional geometries and allow exciton manipulation towards achieving room-temperature quantum computation. A second complementary effort performed at Boise State and INL focused on confining excitons on quantum length scales using coherent surface acoustic phonons

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture

Abstract Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li 7 P 3 S 11 , a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.

Chemistry↗
DOE OSTI2025

Magnet-superconductor hybrid quantum systems: a materials platform for topological superconductivity

Magnet–superconductor hybrid (MSH) systems have recently emerged as one of the most significant developments in condensed matter physics. This has generated, in the last decade, a steadily rising interest in the understanding of their unique properties. They have been proposed as one of the most promising platforms for the establishment of topological superconductivity, which holds high potential for application in future quantum information technologies. Their emergent electronic properties stem from the exchange interaction between the magnetic moments and the superconducting condensate. Given the atomic-level origin of such interaction, it is of paramount importance to investigate new magnet–superconductor hybrids at the atomic scale. In this regard, scanning tunneling microscopy (STM) and spectroscopy are playing a crucial role in the race to unveil the fundamental origin of the unique properties of MSH systems, with the aim to discover new hybrid quantum materials capable of hosting topologically non-trivial unconventional superconducting phases. In particular, the combination of STM studies with tight-binding model calculations have represented, so far, the most successful approach to unveil and explain the emergent electronic properties of MSHs. The scope of this review is to offer a broad perspective on the field of MSHs from an atomic-level investigation point-of-view. The focus is on discussing the link between the magnetic ground state hosted by the hybrid system and the corresponding emergent superconducting phase. This is done for MSHs with both one-dimensional (atomic chains) and two-dimensional (atomic lattices and thin films) magnetic systems proximitized to conventional s-wave superconductors. We present a systematic categorization of the experimentally investigated systems with respect to defined experimentally accessible criteria to verify or falsify the presence of topological superconductivity and Majorana edge modes. The discussion will start with an introduction to the physics of Yu–Shiba–Rusinov bound states at magnetic impurities on superconducting surfaces. This will be used as a base for the discussion of magnetic atomic chains on superconductors, distinguishing between ferromagnetic, antiferromagnetic and non-collinear magnetic ground states. A similar approach will be used for the discussion of magnetic thin film islands on superconductors. Given the vast number of publications on the topic, we limit ourselves to discuss works which are most relevant to the search for topological superconductivity.

Majorana states↗
DOE OSTI2020

Mixed Material Scintillator Systems Quarterly Report FY20Q4

This project aims to invent, model, and prototype architected multimaterial scintillator systems (AMSSs), a new class of radiation detectors that use heterogenous internal structures of different scintillating materials to detect additional properties of radiation. These internal structures can be produced using additive manufacture (AM, i.e. 3D printing) of scintillator, a currently emerging application of additive manufacture technology. AMSSs combine the low cost and complexity of conventional scintillation detectors with capabilities currently only available in more expensive and complex detectors. By identifying promising AMSS designs, this project will enable a new class of detectors to meet DNN’s mission needs for SNM detection. In past reporting, we have described this detector concept as “mixed material scintillator systems” (MMSS), but as part of preparing papers for publication we have concluded the term “architected multimaterial scintillator systems” (AMSS) better reflects the importance of structure in these detectors. We plan to use the AMSS acronym going forward. This quarter, we participated in an Independent Assessment of the work so far. The panelists on the review concluded that the AMSS concept has great potential and our work so far was effective at bringing that potential to light. They highly encouraged further work on this topic. The panelists also had several useful suggestions, which we took to heart. This review is described in more detail below. This quarter saw a resumption of work on the final task of this project, prototyping. In the first half of the quarter, this work focused on solving specific technical barriers to achieve 1x1x1 cm prints. In the second half, we focused on producing high-quality samples and making characterization measurements of those samples, with an eye on our deliverable report on the prototyping task. This report can be expected along with the end-of-year report on October 30. This project successfully spent the entirety of its remaining funds this quarter, except for $13k refunded to this project in the last days of the fiscal year due to LLNL cost adjustments. This project has captured the interest of many LLNL experts, and so we have been able to effectively use our budget to harness the available effort.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Preliminary HEA Solid Phase Processing Development Report

The development of high temperature fuel cladding materials to withstand a variety of extreme environments have received much attention. Several potential materials systems that have been identified for the fuel systems and core structural materials application in advanced reactor systems are ferritic/martensitic steel (e.g., HT9), austenitic stainless steels (e.g., 316 LN), oxide-dispersion strengthened steels (e.g., 12 YWT), Ni-based alloys and ceramic-based composites depending on the type of the reactors. Though these material systems have promising properties conducive for radiation-resistant performance, they suffer beyond the design-limit from one or more damage processes such as void swelling, radiation embrittlement, phase instability, corrosion, and limited creep life.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Polymorphic Metastability in Colloidal Semiconductor Nanocrystals

Metastable polymorphs of inorganic solids often possess material properties not present in the corresponding thermodynamic polymorphs, making them targets for the development of new functional materials. In contrast with isolating metastable bulk materials, syntheses of metastable polymorphs on the nanoscale are aided by fast non-equilibrium reaction kinetics and the favorable thermodynamic influence of surface energies, giving rise to greater ease of access to metastable high-temperature polymorphs and, in some cases, new polymorphs that do not exist in the bulk. The syntheses of metastable semiconductor nanocrystals are of interest for their potentially unique optoelectronic and physicochemical properties. However, in many material systems, synthesizing nanocrystalline products away from thermodynamic equilibrium in a predictable manner remains an outstanding challenge. This review outlines direct synthetic methodologies that have been developed to enable control over the nucleation and growth of metastable polymorphs of semiconductor nanocrystals by tailoring reaction conditions, precursor kinetics, ligand and surface effects, and other synthetic levers. The case studies reviewed herein expound on the direct syntheses of metastable ZnSe, Cu 2 SnSe 3 , CuInSe 2 , Ag 2 Se, and AgInSe 2 nanocrystals, and although there remain numerous examples of metastable nanocrystal syntheses outside of these metal chalcogenide systems, the concepts discussed are of general utility to the field of metastable nanocrystal syntheses as a whole. Explicit examples in which new functional properties are afforded by metastable polymorphs of the aforementioned material systems are presented within the context of applications for solar cells, photonics, and optical sensing. Finally, the factors that affect the kinetic persistence of metastable nanocrystalline polymorphs are discussed at length for these material systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Material Characterization for Large Scale Additive Manufacturing (AM)

The objective of this project was to enable prediction of residual stresses and warpage for extrusion deposition additive manufacturing (EDAM) fabricated carbon fiber thermoplastic matrix parts with three different materials systems produced by Techmer. The materials selected include Polyphenylene sulfide reinforced with 50% by weight of carbon fiber (CF-PPS), Polyethersulfone reinforced with 25% by weight of carbon fiber (CF-PESU), Polysulfone reinforced with 25% by weight of carbon fiber (CF-PSU). ADDITIVE3D © , a physics-based simulation workflow for EDAM, provided the simulation capabilities required for this project. Simulation predictions were validated against measurements carried out during and after the printing process carried out in the CAMRI and LSAM systems . Predictions for temperature, degree of crystallinity and deformation were carried out for the three material systems and two different geometries. Predictions for temperature were correlated very well with the experimental measurements for the two geometries printed using the three-material systems. The crystallinity level was verified for CF-PPS. The predictions for part deformation were in good agreement with the experimental measurements. In the best-case, predictions were within 8% of the maximum displacement observed in the 3-direction whereas predictions were within 14% for the worst-case. The adoption of this technology in commercial large-scale EDAM production processes would dramatically reduce the costs associated with producing articles by that process. Many thousands of dollars in materials, energy, and machine time could be saved by utilizing this simulation technology to develop articles rather than iterative printings to arrive at the optimal or correct design. The avoidance of a single failed print has the possibility of saving tens of thousands of dollars involved in the cost of material, machine and operators’ time.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Designs and Modeling of Architect Multi-material Scintillator System

We present a new conceptual radiation detector, the Architected Multimaterial Scintillator System, that utilizes a scintillator composed of multiple materials arranged in architected structures to enable new capabilities. By structuring differently-dyed materials, the wavelength of the scintillation light encodes additional information in radiation measurements. These structures can be realized through additive manufacture (3D-printing). Two classes of this concept are described and modelled using Monte Carlo simulations to evaluate their performance. The first detector design uses dye microstructures to encode particle tracking information, allowing for directional neutron detection and gamma/neutron discrimination. The second design uses a dye gradient to indicate the position of radiation along the gradient. The simulation results indicate this new concept in radiation detection can achieve strong performance in a variety of capabilities including particle identification, directionality and spectroscopy measurements, and particle position reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

An Overview of Nano Multilayers as Model Systems for Developing Nanoscale Microstructures

The microstructural transformations of binary nanometallic multilayers (NMMs) to equiaxed nanostructured materials were explored by characterizing a variety of nanoscale multilayer films. Four material systems of multilayer films, Hf-Ti, Ta-Hf, W-Cr, and Mo-Au, were synthesized by magnetron sputtering, heat treated at 1000 °C, and subsequently characterized by transmission electron microscopy. Binary systems were selected based on thermodynamic models predicting stable nanograin formation with similar global compositions around 20–30 at.%. All NMMs maintained nanocrystalline grain sizes after evolution into an equiaxed structure, where the systems with highly mobile incoherent interfaces or higher energy interfaces showed a more significant increase in grain size. Furthermore, varying segregation behaviors were observed, including grain boundary (GB) segregation, precipitation, and intermetallic formation depending on the material system selected. The pathway to tailored microstructures was found to be governed by key mechanisms and factors as determined by a film’s initial characteristics, including global and local composition, interface energy, layer structure, and material selection. This work presents a global evaluation of NMM systems and demonstrates their utility as foundation materials to promote tailored nanomaterials.

Appleget, Chelsea D.↗
DOE OSTI2026

Models and Algorithms for Equilibrium Analysis of Mixed-Material Nucleic Acid Systems

Dynamic programming algorithms within the NUPACK software suite enable analysis of equilibrium base-pairing properties for complex and test tube ensembles containing arbitrary numbers of interacting nucleic acid strands. Currently, calculations are limited to single-material systems that are either all-RNA or all-DNA. Here, to enable analysis of mixed-material systems that are critical for modern applications in vitro, in situ, and in vivo, we develop physical models and dynamic programming algorithms that allow the material of the system to be specified at nucleotide resolution. Free energy parameter sets are constructed for both RNA/DNA and RNA/2'OMe-RNA mixed-material systems by combining available empirical mixed-material parameters with single-material parameter sets to enable treatment of the full complex and test tube ensembles. New dynamic programming recursions account for the material of each nucleotide throughout the recursive process. For a complex with N nucleotides, the mixed-material dynamic programming algorithms maintain the O(N 3 ) time complexity of the single-material algorithms, enabling efficient calculation of diverse physical quantities over complex and test tube ensembles (e.g., complex partition function, equilibrium complex concentrations, equilibrium base-pairing probabilities, minimum free energy secondary structure(s), and Boltzmann-sampled secondary structures) at a cost increase of roughly 2.0-3.5×. The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems. Accuracy is significantly enhanced using mixed-material models and algorithms to predict RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures from the experimental literature as well as RNA/DNA melt profiles from new experiments. In conclusion, mixed-material analyses can be performed online using the NUPACK web app (www.nupack.org) or locally using the NUPACK Python module.

2′OMe-RNA↗
DOE OSTI2023

An ICME Modeling Framework for Metal Matrix Composites Focusing on Ultrahigh Temperature Matrix Material and Tungsten Carbide Reinforcement Particulate (Final CRADA Report)

Ultra High Temperature Metal Matrix Composites (UHT-MMCs) are of interest to the due to their potential defense and aerospace applications. These materials consist of a metal matrix reinforced with a stiff ceramic or cermet. Based on a preliminary literature survey, this project will focused on a pure titanium (Ti) matrix reinforced with tungsten carbide-cobalt (WC-Co). UHT-MMC technology is still at a nascent stage of development and requires extensive experimental work to optimize the structure and resulting material properties of a particular UHT-MMC material system. An accurate and complete high-performance computing (HPC) model of the Ti/WC-Co material system could greatly accelerate the development and deployment Ti/WC-Co materials by connecting processing parameters to material properties. This type of model could then be used in an integrated computational materials engineering approach to optimize the material structure to achieve a targeted level of performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Implications of doping on microstructure, processing, and thermoelectric performance: The case of PbSe

Abstract In this work, we highlight the often-overlooked effects of doping on the microstructure and performance of bulk thermoelectric materials to offer a broader perspective on how dopants interact with their parent material. Using PbSe doped with Na, Ag, and K as a model material system, we combine original computational, experimental, and microscopy data with established trends in material behavior, to provide an in-depth discussion of the relationship between dopants, processing, and microstructure, and their effects on thermoelectric efficiency and thermal stability. Notable observations include differences in the microstructure and mass loss of thermally treated samples of Na- and Ag-doped PbSe, as well as findings that Na and K cations exist predominantly as substitutional point defects while Ag also occupies interstitial sites and exhibits lower solubility. We discuss how these differences in point defect populations are known to affect a dopants’ ability to alter carrier concentration and how they may affect the mechanical properties of PbSe during processing. Graphic Abstract

Grovogui, Jann A. (ORCID:0000000200481049)↗
DOE OSTI2022

Materials properties characterization in the most extreme environments

Abstract There is an ever-increasing need for material systems to operate in the most extreme environments encountered in space exploration, energy production, and propulsion systems. To effectively design materials to reliably operate in extreme environments, we need an array of tools to both sustain lab-scale extreme conditions and then probe the materials properties across a variety of length and time scales. Within this article, we examine the state-of-the-art experimental systems for testing materials under extreme environments and highlight the limitations of these approaches. We focus on three areas: (1) extreme temperatures, (2) extreme mechanical testing, and (3) chemically hostile environments. Within these areas, we identify six opportunities for instrument and technique development that are poised to dramatically impact the further understanding and development of next-generation materials for extreme environments. Graphical abstract

Schreiber, Daniel K.↗
DOE OSTI2021

Quantum Engineering With Hybrid Magnonic Systems and Materials (Invited Paper)

Quantum technology has made tremendous strides over the past two decades with remarkable advances in materials engineering, circuit design and dynamic operation. In particular, the integration of different quantum modules has benefited from hybrid quantum systems, which provide an important pathway for harnessing the different natural advantages of complementary quantum systems and for engineering new functionalities. This review focuses on the current frontiers with respect to utilizing magnetic excitations or magnons for novel quantum functionality. Magnons are the fundamental excitations of magnetically ordered solid-state materials and provide great tunability and exibility for interacting with various quantum modules for integration in diverse quantum systems. The concomitant rich variety of physics and material selections enable exploration of novel quantum phenomena in materials science and engineering. In addition, the relative ease of generating strong coupling and forming hybrid dynamic systems with other excitations makes hybrid magnonics a unique platform for quantum engineering. We start our discussion with circuit-based hybrid magnonic systems, which are coupled with microwave photons and acoustic phonons. Subsequently, we are focusing on the recent progress of magnon-magnon coupling within confined magnetic systems. Next we highlight new opportunities for understanding the interactions between magnons and nitrogen-vacancy centers for quantum sensing and implementing quantum interconnects. Lastly, we focus on the spin excitations and magnon spectra of novel quantum materials investigated with advanced optical characterization.

42 ENGINEERING↗
DOE OSTI2025

Time-domain thermoreflectance

Time-domain thermoreflectance (TDTR) has been instrumental in measuring the heat transfer properties of bulk and nanostructured materials over the past two decades. In this Primer, we describe the optical and thermal aspects of TDTR, with an in-depth discussion on the theory, apparatus design and implementation. We present examples that illustrate the ability of TDTR to measure thermal conductivity tensors, thermal conductance across material interfaces, and volumetric heat capacity of thin films, 2D materials and bulk materials. The ability of TDTR to spatially resolve thermal properties is useful for studying heterogeneous material systems, such as materials processed in or subjected to extreme environments. We consider current limitations of pump–probe metrologies and discuss recent advancements of TDTR, such as time-resolved magneto-optic Kerr effect (TR-MOKE), beam-offset TDTR/TR-MOKE, steady-state thermoreflectance, frequency-domain thermoreflectance and laser-flash TDTR. Lastly, we present an outlook on anticipated technological developments to further expand the ability of TDTR to measure nanoscale thermal properties.

42 ENGINEERING↗
DOE OSTI2021

The spin selectivity effect in chiral materials

We overview experiments performed on the chiral induced spin selectivity (CISS) effect using various materials and experimental configurations. Through this survey of different material systems that manifest the CISS effect, we identify several attributes that are common to all the systems. Among these are the ability to observe spin selectivity for two point contact configurations, when one of the electrodes is magnetic, and the correlation between the optical activity of the chiral systems and a material’s spin filtering properties. In addition, recent experiments show that spin selectivity does not require pure coherent charge transport and the electron spin polarization persists over hundreds of nanometers in an ordered medium. Finally, we point to several issues that still have to be explored regarding the CISS mechanism. Among them is the role of phonons and electron–electron interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗