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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Thermomechanical Analysis of Polysulfone-Nanodiamond Mixed Matrix Membranes

Idaho National Laboratory is developing a polymer membrane designed to concentrate oxygen from air to assist in cleaner coal combustion and other gasification processes. These membranes were formed by adding nanodiamond particles to enhance their transport properties. This study focuses on the thermomechanical analysis (TMA) of these membranes to probe the behavior between the nanodiamond particles and the polymer.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Additive Manufacturing of Thermal Energy Storage Composites with Microencapsulated Phase Change Materials Supported in a Multipolymer Matrix

Additive manufacturing (AM) techniques to directly integrate phase change materials (PCMs) are of interest for efficient thermal energy storage (TES) architectures. Complex, high surface-to-volume ratio composites embedded with PCM can improve thermal management with reduced material waste for customizable device fabrication. Reducing feature sizes of TES-integrated heat exchangers using AM can increase heat transfer without thermal conductivity enhancement. Here, composite AM materials containing 60 wt% microencapsulated phase change materials (MEPCM) are fabricated using off-the-shelf printers at common speeds and resolutions. High MEPCM loading in filaments is achieved with powder extrusion using two polymers, thermoplastic-polyurethane (TPU) and polycaprolactone (PCL), that mediate flexibility and rigidity for effective extrusion and printing without filament fracture or buckling. Furthermore, with PCL and TPU at 20 wt% each and 60 wt% MEPCM (P 20 T 20 M 60 ), smooth, form-stable filaments are consistently printed. Powder-based extrusion displays negligible damaging effects on the MEPCM. Printed P 20 T 20 M 60 demonstrates 105 J/g of energy storage with no degradation through 250 thermal cycles, within 5% of the theoretical storage enthalpy. Combining PCL/TPU shows good interfacial adhesion between print layers and produces high surface area objects, like 15% gyroids, and dense, 100% infilled pucks. Prints are also scalable to a 900 cm 3 honeycomb heat exchanger with an estimated 9 Wh energy storage.

25 ENERGY STORAGE↗
DOE OSTI2023

Stretchable and Self‐Healable Semiconductive Composites Based on Hydrogen Bonding Cross‐linked Elastomeric Matrix

Abstract Semiconductors with both high stretchability and self‐healing capability are highly desirable for various wearable devices. Much progress has been achieved in designing highly stretchable semiconductive polymers or composites. The demonstration of self‐healable semiconductive composite is still rare. Here, an extremely soft, highly stretchable, and self‐healable hydrogen bonding cross‐linked elastomer, amide functionalized‐polyisobutylene (PIB‐amide) is developed, to enable a self‐healable semiconductive composite through compounding with a high‐performance conjugated diketopyrrolopyrrole (DPP‐T) polymer. The composite, consisting of 20% DPP‐T and 80% PIB‐amide, shows record high crack‐onset strain (COS ≈1500%), extremely low elastic modulus (E≈1.6 MPa), and unique ability to spontaneously self‐heal atroom temperature within 5 min. Unlike previous works, these unique composite materials also show strain‐independent charge mobility. An in‐depth morphological study based on multi‐model techniques indicate that all composites show blending ratio‐ and stretching‐independent fibril‐like aggregation due to the strong hydrogen bond in elastomer to enable the unique stable charge mobility. This study provides a new direction to develop highly healable and electronically stable semiconductive composite and will enable new applications of stretchable electronics.

Chemistry↗
DOE OSTI2022

A Polymer Canvas with the Stiffness of the Bone Matrix to Study and Control Mesenchymal Stem Cell Response

Reproducing in vitro the complex multiscale physical features of human tissues creates novel biomedical opportunities and fundamental understanding of cell–environment interfaces and interactions. While stiffness has been recognized as a key driver of cell behavior, systematic studies on the role of stiffness have been limited to values in the KPa–MPa range, significantly below the stiffness of bone. Here, in this work, a platform enabling the tuning of the stiffness of a biocompatible polymeric interface up to values characteristic of human bone is reported, which are in the GPa range, by using extremely thin polymer films on glass and cross-linking the films using ultraviolet (UV) light irradiation. It is shown that a higher stiffness is related to better adhesion, proliferation, and osteogenic differentiation, and that it is possible to switch on/off cell attachment and growth by solely tuning the stiffness of the interface, without any surface chemistry or topography modification. Since the stiffness is tuned directly by UV irradiation, this platform is ideal for rapid and simple fabrication of stiffness patterns and gradients, thus representing an innovative tool for combinatorial studies of the synergistic effect of tissue environmental cues on cell behavior, and creates new opportunities for next-generation biosensors, single-cell patterning, and lab-on-a-chip devices.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Rotation of Crystal Seed During Early Stages of Growth Reveals the Anisotropy of Glass Matrix

Glass-ceramics are a highly valuable class of materials that are needed for realizing many high-tech as well as consumer products. They are made by controlling crystallization of glass. Theoretical atomistic insights obtained using molecular dynamics simulations in this work reveal that crystal seeds can spontaneously rotate within glass at high temperatures due to anisotropic forces at the glass-crystal interface. This rotation challenges the long‐held view of glass as isotropic solid, and highlights how atomic‐scale inhomogeneities influence crystal growth and microstructure, hence the physical properties glass‐ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Statistical learning for predicting density–matrix-based electron dynamics

In this study, we consider the problem of learning density-dependent molecular Hamiltonian matrices from time series of electron density matrices, all in the context of Hartree–Fock theory. Prior work developed a solution to this problem for small molecular systems with density and Hamiltonian matrices of size at most 6 × 6. Here, using a battery of techniques, we scale prior methods to larger molecular systems with, for example, 29 × 29 matrices. This includes systems that either have more electrons or are expressed in large basis sets such as 6-311++G**. Scaling the method to larger systems enhances its relevance for realistic applications in chemistry and physics. To achieve this scaling, we apply dimensionality reduction, ridge regression and analytic computation of Hessians. Through the combination of these techniques, we are able to learn Hamiltonians by minimizing an objective function that encodes local propagation error. Importantly, these learned Hamiltonians can then be used to predict electron dynamics for thousands of steps: When we use our learned Hamiltonians to numerically solve the time-dependent Hartree–Fock equation, we obtain predicted dynamics that are in close quantitative agreement with ground truth dynamics. This includes field-off trajectories similar to the training data and field-on trajectories outside of the training data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

MatRIS: Addressing the Challenges for Portability and Heterogeneity Using Tasking for Matrix Decomposition (Cholesky)

The ubiquitous in-node heterogeneity of HPC and cloud computing platforms makes software portability and performance optimization extremely challenging. Described here, the MatRIS multilevel math library abstraction framework employs tasking to alleviate these difficulties. MatRIS includes the IRIS task-based runtime on the bottom level and exposes different layers of abstraction to render algorithms architecturally agnostic. MatRIS ensures the decomposition and creation of tasks that represent the necessary encapsulation of the optimized kernels from both vendor and open-source math libraries. Once built, MatRIS can select different combinations of accelerators at runtime, making it portable even on diverse heterogeneous architectures. By leveraging the IRIS runtime’s features for managing heterogeneity, MatRIS deploys algorithms that remove the need to specify orchestration and data transfer. This study describes how the serial task abstraction of a tiled Cholesky factorization is made portable and scalable in the case of multi-device and multi-vendor heterogeneity on a node with NVIDIA and AMD GPUs by using MatRIS. First, we demonstrate that Cholesky in MatRIS provides multi-GPU scalability that offers competitive performance versus cuSolverMG. Then, we present the challenges and opportunities for heterogeneous execution.

Monil, M. A. H.↗
DOE OSTI2020

The O(N) S-matrix monolith

We consider the scattering matrices of massive quantum field theories with no bound states and a global O(N) symmetry in two spacetime dimensions. In particular we explore the space of two-to-two S-matrices of particles of mass m transforming in the vector representation as restricted by the general conditions of unitarity, crossing, analyticity and O(N) symmetry. We found a rich structure in that space by using convex maximization and in particular its convex dual minimization problem. At the boundary of the allowed space special geometric points such as vertices were found to correspond to integrable models. The dual convex minimization problem provides a novel and useful approach to the problem allowing, for example, to prove that generically the S-matrices so obtained saturate unitarity and, insome cases, that they are at vertices of the allowed space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Quantum dynamics of cosmological particle production: interacting quantum field theories with matrix product states

Understanding real-time dynamics of interacting quantum fields in curved space-time remains a major theoretical challenge. We employ tensor network methods to study such dynamics using interacting scalar and gauge theories in 1+1 spacetime dimensions, subject to a quench modeling a homogeneously expanding gravitational background. The models considered are the scalar λϕ 4 theory and the Schwinger model, i.e. a Dirac fermion coupled to a U(1) gauge field which is equivalent via bosonization to a scalar field with a cosine self-interaction. In the free scalar limit, both theories reproduce known analytical results, providing a nontrivial numerical validation of bosonization in curved spacetime for the Schwinger model. Our central finding is that self-interactions lead to a suppression of gravitational particle production compared to the free-field case, as evidenced by two-point functions and the spectra of produced particles. We further examine the behavior of entanglement generation and find that interactions suppress entanglement growth in the λϕ 4 theory, while in the Schwinger model, the interplay between suppressed particle production and enhanced inter-particle correlations leads to more complex entanglement behavior. Our results pave the way for further explorations of nonperturbative quantum real-time dynamics of interacting scalar and gauge theories in arbitrary gravitational backgrounds.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Corners and islands in the S-matrix bootstrap of the open superstring

We bootstrap the Veneziano superstring amplitude in 10 dimensions from the bottom-up. Starting with the most general maximally supersymmetric Yang-Mills EFT, we input information about the lowest-lying massive states, which we assume contribute via tree-level exchanges to the 4-point amplitude. We show the following: (1) if there is only a single state at the lowest mass, it must be a scalar. (2) Assuming a string-inspired gap between the mass of this scalar and any other massive states, the allowed region of Wilson coefficients has a new sharp corner where the Veneziano amplitude is located. (3) Upon fixing the next massive state to be a vector, the EFT bounds have a one-parameter family of corners; these would correspond to models with linear Regge trajectories of varying slopes, one of which is the open superstring. (4) When the ratio between the massive scalar coupling and the tr F 4 coefficient is fixed to its string value, the spin and mass of the second massive state is determined by the bootstrap and the Veneziano amplitude is isolated on a small island in parameter space. Finally, we compare with other recent bootstraps approaches, both the pion model and imposing Regge-inspired maximal spin constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗