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At least 757 records · Page 42

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DOE OSTI2026

Pedestal origin and extrapolation of high-density small edge-localised-modes peak parallel energy fluence in ITER and SPARC

Experimental analysis and simulations with the BOUT++ code show that small edge-localised modes (ELMs) in reactor-relevant high-density regimes originate in a region close to the separatrix and only marginally perturb the pedestal structure. The measured divertor peak parallel energy fluence (ε ∥,peak ) for a database of small ELM scenarios in DIII-D and ASDEX Upgrade can be reproduced, within 40 % accuracy on average, if an ad hoc modification of the Eich peak parallel ELM energy fluence model is applied to account for the small ELM pedestal birth location. This allows for first-order extrapolation of small-ELM divertor ε ∥,peak to ITER and SPARC, resulting in values that satisfy the nominal melting threshold of tungsten monoblocks of 12 MJ m −2 . The findings reported in this study, both via modelling and direct measurements, constitute a step forward in assessing small ELMs in high edge-collisionality scenarios as a viable plasma regime for the operation of next-generation fusion machines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Catalytic Promotion of Transition-Metal-Doped Graphene Cathodes in Li-CO 2 Batteries

The Li-CO 2 battery is a promising energy storage system with impressive theoretical specific energy and discharge capacity. Graphene-based single-atom catalysts (SACs) provide high surface area and long-term electrochemical reactivity and stability, making SACs among the most promising cathode catalysts for these batteries. However, current Li-CO 2 systems have high reaction barriers, slowing the reaction and greatly increasing the overpotential. Improvement of the discharge/charge energetics requires atomic-level innovations in cathode design, such as alterations to the catalyst chemical structure. In this paper, we propose enhancing the SAC by using a Ti metal center, which is found to deliver the highest electrochemical Li + CO 2 activity among 3d transition metal candidates. Furthermore, we propose cathode surface coating with ionic liquids, since these environments promote the formation of reaction intermediates in the electrochemical conversion process. Here, our work provides insights to optimize electrode design for high-performance Li-CO 2 batteries, which can open new avenues to recycle greenhouse gases and achieve enhanced renewable energy storage.

25 ENERGY STORAGE↗

DOE OSTI2020

Universal slow plasmons and giant field enhancement in atomically thin quasi-two-dimensional metals

Plasmons depend strongly on dimensionality: while plasmons in three-dimensional systems start with finite energy at wavevector q = 0, plasmons in traditional two-dimensional (2D) electron gas disperse as ω p ∼ q . However, besides graphene, plasmons in real, atomically thin quasi-2D materials were heretofore not well understood. Here we show that the plasmons in real quasi-2D metals are qualitatively different, being virtually dispersionless for wavevectors of typical experimental interest. This stems from a broken continuous translational symmetry which leads to interband screening; so, dispersionless plasmons are a universal intrinsic phenomenon in quasi-2D metals. Moreover, our ab initio calculations reveal that plasmons of monolayer metallic transition metal dichalcogenides are tunable, long lived, able to sustain field intensity enhancement exceeding 10 7 , and localizable in real space (within ~20 nm) with little spreading over practical measurement time. This opens the possibility of tracking plasmon wave packets in real time for novel imaging techniques in atomically thin materials.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Sparse expansions of multicomponent oxide configuration energy using coherency and redundancy

We report that compressed sensing has become a widely accepted paradigm to construct high dimensional cluster expansion models used for statistical mechanical studies of atomic configuration in complex multicomponent crystalline materials. However, strict sampling requirements necessary to obtain minimal coherence measurements for compressed sensing to guarantee accurate estimation of model parameters are difficult and in some cases impossible to satisfy due to the inability of physical systems to access certain configurations. Nevertheless, the dependence of energy on atomic configuration can still be adequately learned without these strict requirements by using compressed sensing by way of coherent measurements using redundant function sets known as frames. We develop a particular frame constructed from the union of all occupancy-based cluster expansion basis sets. We illustrate how using this highly redundant frame yields sparse expansions of the configuration energy of complex oxide materials that are competitive and often surpass the prediction accuracy and sparsity of models obtained from standard cluster expansions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Hydrogen irradiation-driven computational surface chemistry of lithium oxide and hydroxide

We have investigated, using molecular dynamics, the surface chemistry of hydrogen incident on the amorphous and crystalline lithium oxide and lithium hydroxide surfaces upon being slowed down by a collision cascade and retained in the amorphous surface of either Li 2 O or LiOH. We looked for the bonding of H to the resident structures in the surface to understand a possible chain of chemical reactions that can lead to surface transformation upon H atom impact. Our findings, using Density-Functional Theory (DFT) trained ReaxFF force field/electronegativity equalization method potentials, stress the importance of inclusion of polarization in the dynamics of a Li–O–H system, which is also illustrated by DFT energy minimization and quantum–classical molecular dynamics using tight binding DFT. The resulting polar-covalent chemistry of the studied systems is complex and very sensitive to the instantaneous positions of all atoms as well as the ratio of concentrations of various resident atoms in the surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Development of Automated Atom Probe Tomography capability to study the influence of applied voltage and laser power on the final apparent composition of the analyzed specimen

This study presents the development and implementation of an autonomous Bayesian optimization (BO) framework for controlling and optimizing experimental parameters in Atom Probe Tomography (APT). Using commercial silicon needle samples as a benchmark system, we demonstrate that BO can efficiently navigate the complex parameter space of voltage and laser power to achieve target charge state ratios (specifically Si + /(Si + +Si 2+ )) with minimal experimental evaluations. Our implementation integrates Gaussian Process modeling with the CAMECA atom probe control framework, enabling autonomous adjustment of experimental conditions in real-time. Results show that the algorithm successfully converges to target ratios under different scenarios: maintaining a reference ratio, increasing the ratio (favoring Si 1+ ), and decreasing the ratio (favoring Si 2+ ). The system adapts to specimen evolution during analysis, compensating for changes in apex geometry while maintaining optimization targets. This work establishes a proof of concept for AI-driven optimization in APT, addressing the traditional challenges of manual parameter tuning and paving the way for applications to more complex materials where compositional accuracy is critical.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Toward implementing autonomous adaptive data acquisition for scanning hyperspectral imaging of biological systems

Autonomous experimentation is an emerging area of research, primarily related to autonomous vehicles, scientific combinatorial discovery approaches in materials science and drug discovery, and iterative research loops of planning, experimentation, and analysis. However, autonomous approaches developed in these contexts are difficult to apply to high-dimensional mapping technologies, such as scanning hyperspectral imaging of biological systems, due to sample complexity and heterogeneity. We briefly cover the history of adaptive sampling algorithms and surrogate modeling in order to define autonomous adaptive data acquisition as an objective-based, flexible building block for future biological imaging experimentation driven by intelligent infrastructure. We subsequently summarize the recent implementations of autonomous adaptive data acquisition (AADA) for scanning hyperspectral imaging, assess how these address the difficulties of autonomous approaches in hyperspectral imaging, and highlight the AADA design variation from a goal-oriented perspective. Finally, we present a modular AADA architecture that embeds AADA-driven flexible building blocks to address the challenge of time resolution for high-dimensional scanning hyperspectral imaging of nonequilibrium dynamical systems. In our example research-driven experimental design case, we propose an AADA infrastructure for time-resolved, noninvasive, and label-free scanning hyperspectral imaging of living biological systems. This AADA infrastructure can accurately target the correct state of the system for experimental workflows that utilize subsequent expensive, high-information-content analytical techniques.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Metallene-related materials for electrocatalysis and energy conversion

As a member of graphene analogs, metallenes are a class of two-dimensional materials with atomic thickness and well-controlled surface atomic arrangement made of metals or alloys. When utilized as catalysts, metallenes exhibit distinctive physicochemical properties endowed from the under-coordinated metal atoms on the surface, making them highly competitive candidates for energy-related electrocatalysis and energy conversion systems. Significantly, their catalytic activity can be precisely tuned through the chemical modification of their surface and subsurface atoms for efficient catalyst engineering. Here, this minireview summarizes the recent progress in the synthesis and characterization of metallenes, together with their use as electrocatalysts toward reactions for energy conversion. In the Synthesis section, we pay particular attention to the strategies designed to tune their exposed facets, composition, and surface strain, as well as the porosity/cavity, defects, and crystallinity on the surface. We then discuss the electrocatalytic properties of metallenes in terms of oxygen reduction, hydrogen evolution, alcohol and acid oxidation, carbon dioxide reduction, and nitrogen reduction reaction, with a small extension regarding photocatalysis. At the end, we offer perspectives on the challenges and opportunities with respect to the synthesis, characterization, modeling, and application of metallenes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Photonic analog of Mollow triplet with on-chip photon-pair generation in dressed modes

Making analogy with atomic physics is a powerful tool for photonic technology, witnessed by the recent development in topological photonics and non-Hermitian photonics based on parity–time symmetry. The Mollow triplet is a prominent atomic effect with both fundamental and technological importance. Here we demonstrate the analog of the Mollow triplet with quantum photonic systems. Photonic entanglement is generated with spontaneous nonlinear processes in dressed photonic modes, which are introduced through coherent multimode coupling. We further demonstrate the possibility of the photonic system to realize different configurations of dressed states, leading to modification of the Mollow triplet. Our work would enable the investigation of complex atomic processes and the realization of unique quantum functionalities based on photonic systems.

Cui, Chaohan↗

DOE OSTI2020

Cold Spray Deposition of 304L Stainless Steel to Mitigate Chloride-Induced Stress Corrosion Cracking in Canisters for Used Nuclear Fuel Storage

A feasibility study of the cold spray deposition process of 304L stainless steel on 304L stainless steel substrates as a mitigation method for chloride-induced stress corrosion cracking (CISCC) has been investigated under various substrate conditions. The study is aimed at the application of this technology to mitigate CISCC that may potentially occur in or nearthe fusion welded regions of stainless steel canisters in Dry Cask Storage System (DCSS) for used nuclear fuels. Spherical gas-atomized 304L stainless steel powder, in the size range of 25 µm to 44 µm, was used as a feedstock powder for the cold spray process. The powder was deposited on four types of 304L substrates with various surface conditions: as-polished, oxidized, cold-rolled, plates with prototypical CISCC. The effects of cold spray parameters on quality of cold spray coatings were investigated. Thickness, porosity, and phases in the as-deposited materials were evaluated using scanning electron microscopy (SEM) and X-ray diffraction (XRD), and correlated with microhardness and adhesion strength measured via micro-indentation and ASTM C633 pulling test, respectively. XRD analysis of the coatings was also conducted to examine the effects of cold spray condition on residual stress state in the coating. Detailed cross-sectional examination of coating/substrate interfaces was performed with transmission electron microscopy (TEM) equipped with energy dispersive spectroscopy (EDS). Dense and continuous coatings with good adhesion strength and hardness were produced for the various substrate conditions by adjusting cold spray parameters. The results demonstrate that cold spray stainless steel coating is a viable option to provide a physical barrier against CISCC in fusion weld regions of stainless steel in corrosive chloride salt-bearing environments.

Dry Cask Storage Systems, cold spray, 304L stainle↗

DOE OSTI2022

High entropy alloys with hexagonal close-packed structure derived from thin film combinatorial approach

A thin film combinatorial synthesis approach was utilized to develop a compositional and structural library for the OsRuWCo alloy system. The survey of this alloy space produced 24 unique compositions and their corresponding crystal structures, which represent a phase map where amorphous and single-phase hexagonal close-packed alloys were identified. Based on the identification of a promising candidate film region, a new high entropy alloy based on OsRuWCo, but with non-equiatomic composition, was synthesized in bulk form. The alloy exhibited a single-phase hexagonal close-packed structure in the as-cast state. Three derivatives from this system were also developed by considering the heat of mixing, atomic size, and binary solubility. These new alloys are based on OsRuWCoIr and OsRuWCoFe, both of which exhibit single-phase hexagonal close-packed as-cast structures, as determined by X-ray diffraction and electron microscopy. Additionally, this large compositional space was utilized to evaluate conventional parameters that describe high entropy alloys (ΔS mix , ΔH mix , Ω, δ, and VEC), and these were found to elucidate the criteria for solid solution formation in this system. Additionally, trends illustrating the evolution from amorphous to crystalline phases are demonstrated and discussed. It is concluded that in this particular case, the dominant factors promoting crystallinity are thermodynamic or electronic, rather than geometric.

36 MATERIALS SCIENCE↗

DOE OSTI2023

State Preparation in the Heisenberg Model through Adiabatic Spiraling

An adiabatic state preparation technique, called the adiabatic spiral, is proposed for the Heisenberg model. This technique is suitable for implementation on a number of quantum simulation platforms such as Rydberg atoms, trapped ions, or superconducting qubits. Classical simulations of small systems suggest that it can be successfully implemented in the near future. A comparison to Trotterized time evolution is performed and it is shown that the adiabatic spiral is able to outperform Trotterized adiabatics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Accurate prediction of global-density-dependent range-separation parameters based on machine learning

In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0−1 and only five systems (0.07%) with an absolute error larger than 0.01 a0−1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.

Chemistry↗

DOE OSTI2026

Local Spin Density Approximation Strongly Improved by a Better-Informed Local Scaling of Its Self-Interaction Correction

The Perdew−Zunger self-interaction correction (PZSIC) makes density functional approximations (DFAs) exact for all one-electron densities. However, it overcorrects in manyelectron regions, introducing errors for the uniform-density limit, where uncorrected DFAs are exact. The locally scaled PZSIC (LSIC), based on the iso-orbital indicator zσ [which distinguishes single-orbital and slowly varying density regions and is used with the local spin density approximation (LSDA)], restores the uniform-density limit and significantly improves results for many properties, including chemical reaction barrier heights, atomization energies, and ionization potentials. Yet, LSIC performs poorly for weakly bonded systems, leaving many unbound, due to limitations of its iso-orbital indicator. To correct this, in this work we propose a new local scaling, LSIC-α, based on the iso-orbital indicator ασ (which additionally identifies regions of overlapping density tails). A two-parameter scaling function of ασ is fitted to a subset of the nonbonded appropriate norms for the SCAN and r2SCAN meta- GGAs, and tested on many properties of main-group atoms, molecules, and molecular complexes. LSIC-α greatly improves the interaction energies of weakly bonded systems in the S22 data set while retaining LSIC’s accuracy for other properties. This work shows that the errors of LSDA (and presumably of higher-level DFAs) can be largely but not entirely repaired by a proper “do no harm” self-interaction correction.

Approximation↗

DOE OSTI2026

Tomography of Atomic Nuclei

We carry out continuum quantum Monte Carlo calculations of the quantum-mechanical Wigner distribution functions of selected nuclei, up to $^{16}$O. These distributions provide a form of quantum tomography of the spatial and momentum structure of the system. They also help identify the location of high-momentum regions in atomic nuclei and provide insight into the onset of alpha clustering. Besides their intrinsic interest, these distributions will be useful for neutrino event generators, as they correlate the positions and momenta of nucleons in the initial target state. To facilitate their application, we address the need to store them compactly by developing an accurate Gaussian Process emulator that automatically preserves their normalization.

Rocco, Noemi [Valencia U., IFIC; Fermilab]↗

DOE OSTI2023

Ultra-fast interpretable machine-learning potentials

Abstract All-atom dynamics simulations are an indispensable quantitative tool in physics, chemistry, and materials science, but large systems and long simulation times remain challenging due to the trade-off between computational efficiency and predictive accuracy. To address this challenge, we combine effective two- and three-body potentials in a cubic B-spline basis with regularized linear regression to obtain machine-learning potentials that are physically interpretable, sufficiently accurate for applications, as fast as the fastest traditional empirical potentials, and two to four orders of magnitude faster than state-of-the-art machine-learning potentials. For data from empirical potentials, we demonstrate the exact retrieval of the potential. For data from density functional theory, the predicted energies, forces, and derived properties, including phonon spectra, elastic constants, and melting points, closely match those of the reference method. The introduced potentials might contribute towards accurate all-atom dynamics simulations of large atomistic systems over long-time scales.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Vacancy-mediated complex phase selection in high entropy alloys

Phase selection in Ti-Zr-Hf-Al high-entropy alloys was investigated by in-situ high-energy x-ray diffraction, single-crystal x-ray diffraction, and KKR-CPA electronic-structure methods that address disorder and vacancies, predicting formation enthalpy and chemical short-range order (SRO). Samples with varying Al content were synthesized, characterized, and computationally assessed to ascertain the composition-dependent phase selection, as increased Al content often acts as a stabilizer of a body-centered-cubic structure. Equiatomic TiZrHfAl was especially interesting due to its observed bcc superstructure – a variant of γ-brass with 4 vacancies per cell (not 2 as in γ-brass). We highlight how vacancy ordering mediates selection of this variant of γ-brass, which is driven by vacancy-atom SRO that dramatically suppress all atomic SRO. As vacancies are inherent in processing refractory systems, we expect that similar discoveries await in other high entropy alloys or in revisiting older experimental data.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Effect of laser melt schedule on the microstructure of additively manufactured IN718 Superalloy

Laser powder bed fusion (L-PBF) has enabled the fabrication of geometrically complex metallic structures and components that are challenging to producing using conventional manufacturing approaches. The site-specific and far from equilibrium thermal conditions of L-PBF offer the potential to facilitate multi-length scale design of structure and properties across the atomic-through macro-levels. However, L-PBF systems face scalability challenges due to throughput constraints. Laser rotary powder bed fusion (L-RPBF) systems are being investigated as a solution to enhance the deposition rates compared to conventional L-PBF. Rotary systems also offer additional flexibility for controlling the time structure of melting through laser interleaving on alternating layers. Here, in this study, IN718 test samples were printed using single-laser or interleaved dual-laser configuration in a L-RPBF system to investigates the effect of process settings and melt-interleaving on as-fabricated microstructure. The microstructural evolution, such as grain size and crystallographic texture, was assessed by determining variations in the melt-pool shapes. Laser interleaving leads to a reduction in average grain size compared to single laser by ∼ 40 % at high power (400 W) and by ∼36 % at medium power (370 W). Results presented here identify key challenge for obtaining uniform microstructures and barriers for the broader adoption of high-deposition rate L-RPBF.

Dual-laser↗