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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Enhancing Crystallization in Hybrid Perovskite Solar Cells Using Thermally Conductive 2D Boron Nitride Nanosheet Additive

Controlling crystallization and grain growth is crucial for realizing highly efficient hybrid perovskite solar cells (PSCs). In this work, enhanced PSC photovoltaic performance and stability by accelerating perovskite crystallization and grain growth via 2D hexagonal boron nitride (hBN) nanosheet additives incorporated into the active perovskite layer are demonstrated. Specifically, in situ X-ray scattering and infrared thermal imaging during the perovskite annealing process revealed the highly thermally conductive hBN nanosheets promoted the phase conversion and grain growth in the perovskite layer by facilitating a more rapid and spatially uniform temperature rise within the perovskite film. Complementary structural, physicochemical, and electrical characterizations further showed that the hBN nanosheets formed a physical barrier at the perovskite grain boundaries and the interfaces with charge transport layers, passivating defects, and retarding ion migration. As a result, the power conversion efficiency of the PSC is improved from 17.4% to 19.8%, along with enhanced device stability, retaining ≈90% of the initial efficiency even after 500 h ambient air storage. Here, the results not only highlight 2D hBN as an effective additive for PSCs but also suggest enhanced thermal transport as one of the pathways for improved PSC performance by 2D material additives in general.

2D materials↗
DOE OSTI2023

Correlating Rate-Dependent Transition Metal Dissolution between Structure Degradation in Li-Rich Layered Oxides

Understanding the mechanism of the rate-dependent electrochemical performance degradation in cathodes is crucial to developing fast charging/discharging cathodes for Li-ion batteries. Here, in this work, taking Li-rich layered oxide Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 as the model cathode, the mechanisms of performance degradation at low and high rates are comparatively investigated from two aspects, the transition metal (TM) dissolution and the structure change. Quantitative analyses combining spatial-resolved synchrotron X-ray fluorescence (XRF) imaging, synchrotron X–ray diffraction (XRD) and transmission electron microscopy (TEM) techniques reveal that low-rate cycling leads to gradient TM dissolution and severe bulk structure degradation within the individual secondary particles, and especially the latter causes lots of microcracks within secondary particles, and becomes the main reason for the fast capacity and voltage decay. In contrast, high-rate cycling leads to more TM dissolution than low-rate cycling, which concentrates at the particle surface and directly induces the more severe surface structure degradation to the electrochemically inactive rock-salt phase, eventually causing a faster capacity and voltage decay than low-rate cycling. These findings highlight the protection of the surface structure for developing fast charging/discharging cathodes for Li-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Machine Learning‐Guided Discovery of High‐Entropy Perovskite Oxide Electrocatalysts via Oxygen Vacancy Engineering

Abstract High‐entropy perovskite oxides (HEPOs) have recently emerged as multifunctional catalysts. However, the HEPOs’ structural and compositional complexity hinders the easy and accurate extrapolation of activity indicators, which are essential for establishing structure‐property correlations. Here, OxiGraphX, is introduced as a novel graph neural network (GNN) model designed to capture the complex relationships among structure, composition, and atomic chemical environments for accurate prediction of oxygen vacancy formation energies (OVFEs) in HEPOs. By integrating machine learning (ML), density functional theory (DFT), and experimental validation, this work demonstrates an efficient framework for rapidly and accurately screening HEPO electrocatalysts for oxygen evolution reaction (OER). The OxiGraphX predicts OVFEs with a precision exceeding existing data, enabling the identification of compositions of higher oxygen vacancy content (OVC) and, thus, higher catalytic activity. Furthermore, the model explores latent spaces that translate effectively into experimental domains, bridging computational predictions with real‐world applications. This approach accelerates the discovery of high‐performance HEPO catalysts while providing deeper insights into their catalytic mechanisms.

Chemistry↗
DOE OSTI2024

Four–Terminal Perovskite–CdSeTe Tandem Solar Cells: From 25% toward 30% Power Conversion Efficiency and Beyond

Thin-film tandem photovoltaic (PV) technology has emerged as a promising avenue to enhance power conversion efficiency beyond the radiative efficiency limit of single-junction devices. Combining a tunable wide-bandgap perovskite cell with a commercially established narrow-bandgap cadmium selenium telluride (CdSeTe) cell in a comparatively easy-to-fabricate four-terminal (4-T) arrangement is a great step in that direction. Herein, the impact of the transparent back contact and the perovskite absorber bandgap on the performance of 4-T perovskite–CdSeTe tandem solar cells is investigated. 4-T perovskite–CdSeTe tandem device architecture with ≈25% efficiency is demonstrated and a feasible pathway is shown to improve the tandem efficiency to more than 30%. Furthermore, the results show that the integration of CdSeTe with perovskite in 4-T tandem PV configurations represents a significant advancement toward achieving higher efficiency and low-cost tandem PVs.

14 SOLAR ENERGY↗
DOE OSTI2023

High‐Nickel Heterostructured Cathodes with Local Stoichiometry Control for High‐Voltage Operation

The growing demand for lithium‐ion batteries to power electric vehicles and other energy‐dense devices continues to fuel the need for cathodes of increasingly higher nickel in cathodes. The relentless pursuit of high Ni content, however, raises concerns on compromising cell lifetime and safety, especially under high‐voltage operation. Alternative to the traditional design of uniform or core–shell composition, we report a rational control of local stoichiometry in high‐Ni cathodes, enabling their high thermal and cycling stabilities—up to 258 °C at the fully charged state and 91.4% capacity retention for 100 cycles between 2.7 and 4.4 V. Multimodal synchrotron X‐ray characterization unveils the heterostructure of secondary particles, featuring a high‐Ni core (LiNi 0.90 Mn 0.05 Co 0.05 O 2 ) covered by a thin Ni‐gradient layer that remains stable over prolonged cycling due to suppressed oxygen release and structural deterioration. This work underlines, the intricate interplay between local stoichiometry and redox reactions in stabilizing high‐Ni cathodes for high‐voltage operation while ensuring safety.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Backbone Stiffness‐Dependent Photoluminescence of Pendant Fluorophores in Organic Nanoparticles

Fluorescent organic nanoparticles (FoNPs) with backbone stiffness‐dependent photoluminescence were synthesized via microemulsion atom transfer radical polymerization (ATRP) of 2‐(2‐bromoisobutyryloxy)ethyl methacrylate (BiBEM), ethylene glycol dimethacrylate (EGDMA), and methacrylate monomers bearing pendant fluorophores, 1‐pyrenemethyl methacrylate (PyMMA), or 4‐(1,2,2‐triphenylethenyl)benzenemethyl methacrylate (TPEMMA). The crosslinking density precisely tuned the intraparticle rigidity, enabling systematic control over emission mechanisms. Pyrene‐containing FoNPs exhibited a rigidity‐dependent transition from excimer‐dominated to monomer‐dominated fluorescence, whereas TPE‐based FoNPs displayed aggregation‐induced emission (AIE) enhancement as intramolecular motion was restricted. Solvent‐dependent studies revealed that increased polarity and viscosity, particularly in benzyl alcohol and DMSO, promoted cooperative rigidification and enhanced emission intensity through specific polymer–solvent interactions. Furthermore, the retained alkyl bromide chain ends on FoNPs enabled dual roles as initiators and crosslinkers in UV‐induced polymerization of poly(ethylene glycol) acrylates, forming luminescent FoNP–OEG hybrid gels with improved mechanical robustness. This work establishes a versatile platform for integrating tunable optical and mechanical properties into a single polymeric nanoparticle framework, offering new design principles for multifunctional soft materials and providing a platform for future sensing, imaging, and photonic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC

ynchrotron light sources are routinely used to perform imaging experiments. In this paper, we review the relevant computational stages, identify bottlenecks, and highlight future opportunities to streamline data acquisition for experimental microscopy workflows. We demonstrate our preliminary exploration with an end-to-end scientific workflow on Summit based on micro-computed tomography data. Computational elements include: 1) reconstruction of volumetric image data; 2) denoising with deep neural networks; and 3) non-local means based segmentation and quantitative analysis.

Mcclure, James↗
DOE OSTI2020

Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics

The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their as- sociated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

Parete-Koon, Suzanne↗
DOE OSTI2023

Toward an Autonomous Workflow for Single Crystal Neutron Diffraction

The operation of the neutron facility relies heavily on beamline scientists. Some experiments can take one or two days with experts making decisions along the way. Leveraging the computing power of HPC platforms and AI advances in image analyses, here we demonstrate an autonomous workflow for the single-crystal neutron diffraction experiments. The workflow consists of three components: an inference service that provides real-time AI segmentation on the image stream from the experiments conducted at the neutron facility, a continuous integration service that launches distributed training jobs on Summit to update the AI model on newly collected images, and a frontend web service to display the AI tagged images to the expert. Ultimately, the feedback can be directly fed to the equipment at the edge in deciding the next-step experiment without requiring an expert in the loop. With the analyses of the requirements and benchmarks of the performance for each component, this effort serves as the first step toward an autonomous workflow for real-time experiment steering at ORNL neutron facilities.

Yin, Junqi↗
DOE OSTI2023

Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials

The investigation of finite temperature properties using Monte-Carlo (MC) methods requires a large number of evaluations of the system’s Hamiltonian to sample the phase space needed to obtain physical observables as function of temperature. DFT calculations can provide accurate evaluations of the energies, but they are too computationally expensive for routine simulations. To circumvent this problem, machine-learning (ML) based surrogate models have been developed and implemented on high-performance computing (HPC) architectures. In this paper, we describe two ML methods (linear mixing model and HydraGNN) as surrogates for first principles density functional theory (DFT) calculations with classical MC simulations. These two surrogate models are used to learn the dependence of target physical properties from complex compositions and interactions of their constituents. We present the predictive performance of these two surrogate models with respect to their complexity while avoiding the danger of overfitting the model. An important aspect of our approach is the periodic retraining with newly generated first principles data based on the progressive exploration of the system’s phase space by the MC simulation. The numerical results show that HydraGNN model attains superior predictive performance compared to the linear mixing model for magnetic alloy materials.

Eisenbach, Markus↗
DOE OSTI2023

Exact quantization and analytic continuation

In this paper we give a streamlined derivation of the exact quantization condition (EQC) on the quantum periods of the Schrödinger problem in one dimension with a general polynomial potential, based on Wronskian relations. We further generalize the EQC to potentials with a regular singularity, describing spherical symmetric quantum mechanical systems in a given angular momentum sector. We show that the thermodynamic Bethe ansatz (TBA) equations that govern the quantum periods undergo nontrivial monodromies as the angular momentum is analytically continued between integer values in the complex plane. The TBA equations together with the EQC are checked numerically against Hamiltonian truncation at real angular momenta and couplings, and are used to explore the analytic continuation of the spectrum on the complex angular momentum plane in examples.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

On the equivalence between SRS and PCO formulations of superstring perturbation theory

We establish the equivalence between two formulations of superstring perturbation theory, one based on integration over the supermoduli space of super Riemann surfaces (SRS), the other based on integration over the bosonic moduli space with insertions of picture changing operators (PCO) on the worldsheet and the vertical integration prescription, by showing how the latter arises from a specific construction of the supermoduli integration contour.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Thermal bootstrap of matrix quantum mechanics

We implement a bootstrap method that combines stationary state conditions, thermal inequalities, and semidefinite relaxations of matrix logarithm in the ungauged one-matrix quantum mechanics, at finite rank N as well as in the large N limit, and determine finite temperature observables that interpolate between available analytic results in the low and high temperature limits respectively. We also obtain bootstrap bounds on thermal phase transition as well as preliminary results in the ungauged two-matrix quantum mechanics.

1/N Expansion↗
DOE OSTI2022

Scaling and adiabaticity in a rapidly expanding gluon plasma

In this work we aim to gain qualitative insight on the far-from-equilibrium behavior of the gluon plasma produced in the early stages of a heavy-ion collision. It was recently discovered [1] that the distribution functions of quarks and gluons in QCD effective kinetic theory (EKT) exhibit self-similar “scaling” evolution with time-dependent scaling exponents long before those exponents reach their pre-hydrodynamic fixed-point values. In this work we shed light on the origin of this time-dependent scaling phenomenon in the small-angle approximation to the Boltzmann equation. We first solve the Boltzmann equation numerically and find that time-dependent scaling is a feature of this kinetic theory, and that it captures key qualitative features of the scaling of hard gluons in QCD EKT. We then proceed to study scaling analytically and semi-analytically in this equation. We find that an appropriate momentum rescaling allows the scaling distribution to be identified as the instantaneous ground state of the operator describing the evolution of the distribution function, and the approach to the scaling function is described by the decay of the excited states. That is to say, there is a frame in which the system evolves adiabatically. Furthermore, from the conditions for adiabaticity we can derive evolution equations for the time-dependent scaling exponents. In addition to the known free-streaming and BMSS fixed points, we identify a new “dilute” fixed point when the number density becomes small before hydrodynamization. Corrections to the fixed point exponents in the small-angle approximation agree quantitatively with those found previously in QCD EKT and arise from the evolution of the ratio between hard and soft scales.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

ZZ instantons and the non-perturbative dual of $c$ = 1 string theory

We study the effect of ZZ instantons in c = 1 string theory, and demonstrate that they give rise to non-perturbative corrections to scattering amplitudes that do not saturate unitarity within the closed string sector. Beyond the leading non-perturbative order, logarithmic divergences are canceled between worldsheet diagrams of different topologies, due to the Fischler-Susskind-Polchinski mechanism. We propose that the closed string vacuum in c = 1 string theory is non-perturbatively dual to a state of the matrix quantum mechanics in which all scattering states up to a given energy with no incoming flux from the “other side” of the potential are occupied by free fermions. Under such a proposal, we find detailed agreement of non-perturbative corrections to closed string amplitudes in the worldsheet description and in the dual matrix model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Multi-instanton calculus in $c$ = 1 string theory

We formulate a strategy for computing the complete set of non-perturbative corrections to closed string scattering in c = 1 string theory from the worldsheet per spective. This requires taking into account the effect of multiple ZZ-instantons, including higher instantons constructed from ZZ boundary conditions of type (m, 1), with a careful treatment of the measure and contour in the integration over the instanton moduli space. The only a priori ambiguity in our prescription is a normalization constant $\mathcal{N}_m$ that ap pears in the integration measure for the (m, 1)-type ZZ instanton, at each positive integer m. We investigate leading corrections to the closed string reflection amplitude at the n instanton level, i.e. of order e -n/g s , and find striking agreement with our recent proposal on the non-perturbative completion of the dual matrix quantum mechanics, which in turn fixes $\mathcal{N}_m$ for all m.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗