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DOE OSTI2021

Davis Computational Spectroscopy Workflow—From Structure to Spectra

Here, we describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the atomic simulation environment (ASE) as an interface, we demonstrate the use of a selection of calculators, including density functional theory (DFT) and density functional tight binding (DFTB), to optimize the structures and calculate interatomic force constants. We present the use of our workflow to compute the phonon frequencies and eigenvectors, which are required to accurately simulate the INS spectra in crystalline solids like diamond and graphite as well as molecular solids like rubrene. We have also implemented a machine-learning force field based on Chebyshev polynomials called the Chebyshev interaction model for efficient simulation (ChIMES) to improve the accuracy of the DFTB simulations. We then explore the transferability of our DFTB/ChIMES models by comparing simulations derived from different training sets. We show that DFTB/ChIMES demonstrates ~100× reduction in computational expense while retaining most of the accuracy of DFT as well as yielding high accuracy for different materials outside of our training sets. The DFTB/ChIMES method within the workflow expands the possibilities to use simulations to accurately predict materials properties of increasingly complex structures that would be unfeasible with ab initio methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry

Machine learning interatomic potentials (MLIPs) have emerged as powerful tools for investigating atomistic systems with high accuracy and a relatively low computational cost. However, a common and unaddressed challenge with many current neural network (NN) MLIP models is their limited ability to accurately predict the relative energies of systems containing isolated or nearly isolated atoms, which appear in various reactive processes. To address this limitation, we present a mathematical technique for modifying any existing atom-centered NN architecture to account for the energies of isolated atoms. The result produces a consistent prediction of the atomization energy (AE) of a system using minimal constraints on the model. Using this technique, we build a model architecture that we call hierarchically interacting particle neural network (HIP-NN)-AE, an AE-constrained version of the HIP-NN, as well as ANI-AE, the AE-constrained version of the accurate NN engine for molecular energies (ANI). Our results demonstrate AE consistency of AE-constrained models, which drastically improves the AE predictions for the models. We compare the AE-constrained approach to unconstrained models as well as models from the literature in other scenarios, such as bond dissociation energies, bond dissociation pathways, and extensibility tests. These results show that the constraints improve the model performance in some of these tasks and do not negatively affect the performance on any tasks. The AE constraint approach thus offers a robust solution to the challenges posed by isolated atoms in energy prediction tasks.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Exploiting Machine Learning to Efficiently Predict Multidimensional Optical Spectra in Complex Environments

The excited-state dynamics of chromophores in complex environments determine a range of vital biological and energy capture processes. Time-resolved, multidimensional optical spectroscopies provide a key tool to investigate these processes. Although theory has the potential to decode these spectra in terms of the electronic and atomistic dynamics, the need for large numbers of excited-state electronic structure calculations severely limits first-principles predictions of multidimensional optical spectra for chromophores in the condensed phase. In this work, we leverage the locality of chromophore excitations to develop machine learning models to predict the excited-state energy gap of chromophores in complex environments for efficiently constructing linear and multidimensional optical spectra. By analyzing the performance of these models, which span a hierarchy of physical approximations, across a range of chromophore–environment interaction strengths, we provide strategies for the construction of machine learning models that greatly accelerate the calculation of multidimensional optical spectra from first principles.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Linear and Nonlinear X-ray Spectra of Chiral Molecules: X-ray Circular Dichroism, Sum- and Difference-Frequency Generation of Fenchone and Cysteine

Recent advancements in X-ray light sources enable element-sensitive nonlinear spectroscopies for probing molecular chirality. We simulate X-ray absorption spectroscopy, X-ray circular dichroism (XCD), and nonlinear optical/X-ray SFG and DFG (OX SFG/DFG) signals for two prototypical chiral molecules, fenchone and cysteine. Furthermore, our multireference simulations reproduce experimental data and reveal how novel X-ray spectroscopies exploit the site- and element-sensitivity of X-rays to uncover molecular asymmetry. The XCD spectra show strong asymmetries at chiral centers, while distant atoms contribute weaker signals. The OX SFG/DFG signals, under fixed resonant optical excitation, strongly depend on the core and valence excitations. This allows us to introduce two-dimensional (2D) chirality-sensitive valence-core spectroscopy, which provides insight into the overlap between valence orbitals and local molecular asymmetry. Finally, our estimates using realistic laser and X-ray pulse parameters demonstrate that such nonlinear experiments are feasible at XFELs, offering a promising tool for investigating chiral molecules.

Circular dichroism spectroscopy↗

DOE OSTI2020

High-Throughput Exploration of Lithium-Alloy Protection Layers for High-Performance Lithium-Metal Batteries

To realize high specific capacity Li-metal batteries, a protection layer for the Li-metal anode is needed. We are carrying out combinatorial screening of Li-alloy thin films as the protection layer which can undergo significant lithiation with minimum change in volume and crystal structure. In this paper, we have fabricated lithium-free binary alloy thin film composition spreads of Co 1–x Sn x on Cu layers on Si substrates. The crystallinity of the thin films was tuned by varying the deposition temperature followed by electrochemical lithiation to form Li-alloy ternary thin films. Synchrotron diffraction is used as the main tool to investigate the crystallinity of the films before and after lithiation. Co 3 Sn 2 alloy thin films are found to exhibit significant lithium uptake capacity while maintaining its structural integrity, and are thus a good candidate of the Li-metal protection layer.

25 ENERGY STORAGE↗

DOE OSTI2025

Coarse-Grained Modeling Elucidates Differential Metabolism of Saccharomyces cerevisiae under Varied Nutrient Limitations

Microorganisms such as Saccharomyces cerevisiae have a native ability to adapt their metabolism to varying nutrient conditions. Understanding their responses to nutrient limitations is critical for decoding cellular physiology and designing strategies for metabolic engineering. While the influence of carbon availability on yeast metabolism has been extensively studied, the role of nitrogen availability remains relatively underexplored. In this study, we utilized a coarse-grained kinetic model to systematically analyze and compare the effects of carbon and nitrogen limitations on yeast metabolism. Our model successfully revealed the differential metabolic characteristics of S. cerevisiae under carbon- and nitrogen-limited chemostat conditions. It also highlighted the significance of protein activity regulation at varying carbon-to-nitrogen ratios, and elucidated distinct strategies employed to maintain ATP homeostasis. Furthermore, this study provides a computational tool for investigating yeast physiology under nutrient limitations and offers quantitative and mechanistic insights into yeast metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Strong Local Evaporative Cooling Over Land Due to Atmospheric Aerosols

Abstract Aerosols can enhance terrestrial productivity through increased absorption of solar radiation by the shaded portion of the plant canopy—the diffuse radiation fertilization effect. Although this process can, in principle, alter surface evaporation due to the coupling between plant water loss and carbon uptake, with the potential to change the surface temperature, aerosol‐climate interactions have been traditionally viewed in light of the radiative effects within the atmosphere. Here, we develop a modeling framework that combines global atmosphere and land model simulations with a conceptual diagnostic tool to investigate these interactions from a surface energy budget perspective. Aerosols increase the terrestrial evaporative fraction, or the portion of net incoming energy consumed by evaporation, by over 4% globally and as much as ∼40% regionally. The main mechanism for this is the increase in energy allocation from sensible to latent heat due to global dimming (reduction in global shortwave radiation) and slightly augmented by diffuse radiation fertilization. In regions with moderately dense vegetation (leaf area index >2), the local surface cooling response to aerosols is dominated by this evaporative pathway, not the reduction in incident radiation. Diffuse radiation fertilization alone has a stronger impact on gross primary productivity (+2.18 Pg C y −1 or +1.8%) than on land evaporation (+0.18 W m −2 or +0.48%) and surface temperature (−0.01 K). Our results suggest that it is important for land surface models to distinguish between quantity (change in total magnitude) and quality (change in diffuse fraction) of radiative forcing for properly simulating surface climate.

Chakraborty, TC↗

DOE OSTI2023

Ultrafast terahertz emission from emerging symmetry-broken materials

Abstract Nonlinear optical spectroscopies are powerful tools for investigating both static material properties and light-induced dynamics. Terahertz (THz) emission spectroscopy has emerged in the past several decades as a versatile method for directly tracking the ultrafast evolution of physical properties, quasiparticle distributions, and order parameters within bulk materials and nanoscale interfaces. Ultrafast optically-induced THz radiation is often analyzed mechanistically in terms of relative contributions from nonlinear polarization, magnetization, and various transient free charge currents. While this offers material-specific insights, more fundamental symmetry considerations enable the generalization of measured nonlinear tensors to much broader classes of systems. We thus frame the present discussion in terms of underlying broken symmetries, which enable THz emission by defining a system directionality in space and/or time, as well as more detailed point group symmetries that determine the nonlinear response tensors. Within this framework, we survey a selection of recent studies that utilize THz emission spectroscopy to uncover basic properties and complex behaviors of emerging materials, including strongly correlated, magnetic, multiferroic, and topological systems. We then turn to low-dimensional systems to explore the role of designer nanoscale structuring and corresponding symmetries that enable or enhance THz emission. This serves as a promising route for probing nanoscale physics and ultrafast light-matter interactions, as well as facilitating advances in integrated THz systems. Furthermore, the interplay between intrinsic and extrinsic material symmetries, in addition to hybrid structuring, may stimulate the discovery of exotic properties and phenomena beyond existing material paradigms.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Bacterial response to spatial gradients of algal-derived nutrients in a porous microplate

Abstract Photosynthetic microalgae are responsible for 50% of the global atmospheric CO2 fixation into organic matter and hold potential as a renewable bioenergy source. Their metabolic interactions with the surrounding microbial community (the algal microbiome) play critical roles in carbon cycling, but due to methodological limitations, it has been challenging to examine how community development is influenced by spatial proximity to their algal host. Here we introduce a copolymer-based porous microplate to co-culture algae and bacteria, where metabolites are constantly exchanged between the microorganisms while maintaining physical separation. In the microplate, we found that the diatom Phaeodactylum tricornutum accumulated to cell abundances ~20 fold higher than under normal batch conditions due to constant replenishment of nutrients through the porous structure. We also demonstrate that algal-associated bacteria, both single isolates and complex communities, responded to inorganic nutrients away from their host as well as organic nutrients originating from the algae in a spatially predictable manner. These experimental findings coupled with a mathematical model suggest that host proximity and algal culture growth phase impact bacterial community development in a taxon-specific manner through organic and inorganic nutrient availability. Our novel system presents a useful tool to investigate universal metabolic interactions between microbes in aquatic ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Multi-functional genome-wide CRISPR system for high throughput genotype–phenotype mapping

Abstract Genome-scale engineering is an indispensable tool to understand genome functions due to our limited knowledge of cellular networks. Unfortunately, most existing methods for genome-wide genotype–phenotype mapping are limited to a single mode of genomic alteration, i.e. overexpression, repression, or deletion. Here we report a multi-functional genome-wide CRISPR (MAGIC) system to precisely control the expression level of defined genes to desired levels throughout the whole genome. By combining the tri-functional CRISPR system and array-synthesized oligo pools, MAGIC is used to create, to the best of our knowledge, one of the most comprehensive and diversified genomic libraries in yeast ever reported. The power of MAGIC is demonstrated by the identification of previously uncharacterized genetic determinants of complex phenotypes, particularly those having synergistic interactions when perturbed to different expression levels. MAGIC represents a powerful synthetic biology tool to investigate fundamental biological questions as well as engineer complex phenotypes for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation

Abstract Nonequilibrium dynamics governed by electron–phonon ( e -ph) interactions plays a key role in electronic devices and spectroscopies and is central to understanding electronic excitations in materials. The real-time Boltzmann transport equation (rt-BTE) with collision processes computed from first principles can describe the coupled dynamics of electrons and atomic vibrations (phonons). Yet, a bottleneck of these simulations is the calculation of e –ph scattering integrals on dense momentum grids at each time step. Here we show a data-driven approach based on dynamic mode decomposition (DMD) that can accelerate the time propagation of the rt-BTE and identify dominant electronic processes. We apply this approach to two case studies, high-field charge transport and ultrafast excited electron relaxation. In both cases, simulating only a short time window of ~10% of the dynamics suffices to predict the dynamics from initial excitation to steady state using DMD extrapolation. Analysis of the momentum-space modes extracted from DMD sheds light on the microscopic mechanisms governing electron relaxation to a steady state or equilibrium. The combination of accuracy and efficiency makes our DMD-based method a valuable tool for investigating ultrafast dynamics in a wide range of materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Magnon spectroscopy in the electron microscope

Abstract The miniaturization of transistors is approaching its limits owing to challenges in heat management and information transfer speed 1 . To overcome these obstacles, emerging technologies such as spintronics 2 are being developed, which make use of the electron’s spin as well as its charge. Local phenomena at interfaces or structural defects will greatly influence the efficiency of spin-based devices, making the ability to study spin-wave propagation at the nanoscale and atomic scale a key challenge 3,4 . The development of high-spatial-resolution tools to investigate spin waves, also called magnons, at relevant length scales is thus essential to understand how their properties are affected by local features. Here we detect bulk THz magnons at the nanoscale using scanning transmission electron microscopy (STEM). By using high-resolution electron energy-loss spectroscopy with hybrid-pixel electron detectors, we overcome the challenges posed by weak signals to map THz magnon excitations in a thin NiO nanocrystal. Advanced inelastic electron scattering simulations corroborate our findings. These results open new avenues for detecting magnons and exploring their dispersions and their modifications arising from nanoscale structural or chemical defects. This marks a milestone in magnonics and presents exciting opportunities for the development of spintronic devices.

Science & Technology - Other Topics↗

DOE OSTI2025

All hard X-ray transient grating spectroscopy

Optical-domain transient grating (TG) spectroscopy is the ideal tool to investigate transport phenomena in gases, liquids and solids, but it is limited to typically micron-size grating periods. Extreme-Ultraviolet TG has represented a major leap forward to access the mesoscopic scales. Hard X-ray TGs open access in principle to the nanoscale. Hard X-ray TGs were recently generated using the Talbot effect and probed by optical pulses, but these hinder exploiting the advantages of the nanoscale gratings. Here, we present an all-X-ray TG study, in which few-femtosecond hard X-ray pulses are used both for excitation and probing. Our experiment was performed on an amorphous film of an FeGd alloy and on a thin silicon single crystal. The results show a manifestation of the TG induced by the X-ray pump and probe pulses in the form of Talbot carpets, as well as temporal evolution of the grating in crystalline silicon showing coherent optical phonons. Ultrafast all-X-ray TG spectroscopy has the potential to study fundamental excitations with femtosecond time resolution and nanometer spatial sensitivity.

Ferrari, Eugenio [Deutsches Elektronen-Synchrotron↗

DOE OSTI2025

Kelvin probe force microscopy under ambient conditions

Kelvin probe force microscopy (KPFM) is a technique derived from atomic force microscopy that provides maps of surface potential or work function differences across material systems, with nanometre-scale resolution. KPFM is a useful tool for investigating electrical phenomena such as dipole orientation, interfacial charge transfer, charge accumulation, band bending and doping levels. This Primer aims to provide an overview of typical ambient-condition KPFM measurements, covering their underlying principles, experimental implementations and wide-ranging applications. Key KPFM variants, including amplitude and frequency modulation, heterodyne detection schemes and innovative open loop and pulsed force techniques, are discussed, with practical guidance on optimizing signal acquisition and reducing errors. Specialized approaches, such as time-resolved KPFM and multimodal KPFM, are discussed for their ability to capture dynamic charge processes and chemical information, respectively. Here, we highlight recent advances in KPFM applications, spanning metal alloys, soft matter, ferroelectrics, photovoltaics and 2D materials, showcasing its versatility across research domains. By addressing current limitations and identifying future opportunities, this Primer underscores the transformative potential of KPFM in advancing the understanding of nanoscale electrical phenomena.

Zahmatkeshsaredorahi, Amirhossein [Lehigh Univ., B↗

DOE OSTI2020

Nanobodies against the metal binding domains of ATP7B as tools to study copper transport in the cell

Abstract Nanobodies are genetically engineered single domain antibodies derived from the unusual heavy-chain only antibodies found in llamas and camels. The small size of the nanobodies and flexible selection schemes make them uniquely versatile tools for protein biochemistry and cell biology. We have developed a panel of nanobodies against the metal binding domains of the human copper transporter ATP7B, a multidomain membrane protein with a complex regulation of enzymatic activity and intracellular localization. To enable the use of the nanobodies as tools to investigate copper transport in the cell, we characterized their binding sites and affinity by isothermal titration calorimetry and NMR. We have identified nanobodies against each of the first four metal binding domains of ATP7B, with a wide affinity range, as evidenced by dissociation constants from below 10−9 to 10−6 M. We found both the inhibitory and activating nanobodies among those tested. The diverse properties of the nanobodies make the panel useful for the structural studies of ATP7B, immunoaffinity purification of the protein, modulation of its activity in the cell, protein dynamics studies, and as mimics of copper chaperone ATOX1, the natural interaction partner of ATP7B.

Uhlemann, Eva-Maria E.↗

DOE OSTI2022

A finite-volume scheme for modeling compressible magnetohydrodynamic flows at low Mach numbers in stellar interiors

Fully compressible magnetohydrodynamic (MHD) simulations are a fundamental tool for investigating the role of dynamo amplification in the generation of magnetic fields in deep convective layers of stars. The flows that arise in such environments are characterized by low (sonic) Mach numbers ($\mathscr{M}$ son ≲ 10 –2 ). In these regimes, conventional MHD codes typically show excessive dissipation and tend to be inefficient as the Courant–Friedrichs–Lewy (CFL) constraint on the time step becomes too strict. In this work we present a new method for efficiently simulating MHD flows at low Mach numbers in a space-dependent gravitational potential while still retaining all effects of compressibility. The proposed scheme is implemented in the finite-volume SEVEN-LEAGUE HYDRO (SLH) code, and it makes use of a low-Mach version of the five-wave Harten–Lax–van Leer discontinuities (HLLD) solver to reduce numerical dissipation, an implicit–explicit time discretization technique based on Strang splitting to overcome the overly strict CFL constraint, and a well-balancing method that dramatically reduces the magnitude of spatial discretization errors in strongly stratified setups. The solenoidal constraint on the magnetic field is enforced by using a constrained transport method on a staggered grid. We carry out five verification tests, including the simulation of a small-scale dynamo in a star-like environment at $\mathscr{M}$ son ~ 10 –3 . We demonstrate that the proposed scheme can be used to accurately simulate compressible MHD flows in regimes of low Mach numbers and strongly stratified setups even with moderately coarse grids.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Simulations of the IR and Raman spectra of water confined in amorphous silica slit pores

Water in nano-scale confining environments is a key element in many biological, material, and geological systems. The structure and dynamics of the liquid can be dramatically modified under these conditions. Probing these changes can be challenging, but vibrational spectroscopy has emerged as a powerful tool for investigating their behavior. A critical, evolving component of this approach is a detailed understanding of the connection between spectroscopic features and molecular-level details. In this paper, this issue is addressed by using molecular dynamics simulations to simulate the linear infrared (IR) and Raman spectra for isotopically dilute HOD in D 2 O confined in hydroxylated amorphous silica slit pores. The effect of slit-pore width and hydroxyl density on the silica surface on the vibrational spectra is also investigated. The primary effect of confinement is a blueshift in the frequency of OH groups donating a hydrogen bond to the silica surface. This appears as a slight shift in the total (measurable) spectra but is clearly seen in the distance-based IR and Raman spectra. Analysis indicates that these changes upon confinement are associated with the weaker hydrogen-bond accepting properties of silica oxygens compared to water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Electrical and optical characterizations of spin-orbit torque

To further reduce the energy consumption in spin–orbit torque devices, it is crucial to precisely quantify the spin–orbit torque (SOT) in different materials and structures. In this work, heavy metal/ferromagnet and heavy metal/ferrimagnet heterostructures are employed as the model systems to compare the electrical and optical methods for the SOT characterization, which are based on the anomalous Hall effect and the magneto-optical Kerr effect, respectively. It is found that both methods yield the consistent SOT strength for the current-driven magnetization switching measurements and the harmonic measurements. Our results suggest that the optical method is a feasible and reliable tool to investigate SOT, which is a powerful way to develop insulator-based magnetic systems in the future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗