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DOE OSTI2026

Ternary Phosphides Ba M 2 P 2 : Tailoring Crystal and Electronic Structures Enables Highly Efficient HER Electrocatalysis

Binary transition metal phosphides and their solid solutions have emerged as promising hydrogen evolution reaction (HER) catalysts. Although many research endeavors have adopted strategies to vary compositions to optimize catalytic performance, they mainly focus on binary structures, which represent only a small fraction of the abundant phase space of structure types among transition metal phosphides. Here, the largely unexplored class of ternary and multinary ordered phosphides in catalysis comprises two or more metals with quite different chemical nature, concealing the structure–property relationships essential for advancing catalyst design. Here, we explored phosphides crystallizing in one of the most abundant ordered intermetallic structure types, —the ThCr 2 Si 2 type, —where square nets of 3d transition metal M and P atoms are separated by layers of electropositive Ba cations. Four ternary BaM 2 P 2 (M = Fe, Fe/Cu, Fe/Ni, Ni) catalysts were synthesized and characterized. BaNi 2 P 2 showed high HER activity in acidic electrolyte, which required an overpotential, η 10 , of only 62 mV to drive current density j = –10 mA/cm 2 and high stability with a potential drop rate of 0.25 mV/h. BaNi 2 P 2 outperformed other Ni-based catalysts, such as Ni 2 P and Ni 5 P 4 . Notably, at current densities above –170 mA/cm 2 , BaNi 2 P 2 outperformed the standard Pt electrode measured under identical conditions. Electronic structure analysis revealed a volcano-type activity trend among the four BaM 2 P 2 catalysts based on their d-band center positions, highlighting the role of electropositive Ba cations in shifting the Ni-3d orbitals into an optimal position.

BaNi2P2↗

DOE OSTI2025

Harnessing Nanobodies for Precision Targeting of Proteoforms: Opportunities and Challenges in Therapeutics and Diagnostics

Proteoforms are biologically distinct yet structurally similar proteins that play key roles in driving disease progression but are rarely accounted for in the development of therapeutics and diagnostics. Nanobodies (Nbs) have emerged as a therapeutic and diagnostic “silver bullet” as they possess unique structural and functional attributes that offer advantages over traditional antibodies. One of the most profound advantages of Nbs is the heightened sensitivity and ability to distinguish subtle changes in the conformation of a given protein. Thus, Nbs have significant potential as therapeutic and diagnostic agents that can identify and distinguish specific pathological proteoforms that underlie a given disease. However, there remain significant challenges in obtaining sufficient quantities and purities of specific proteoform antigens that are required for engineering proteoform-specific Nbs. Recent advancements in chemical biology tools for precision proteoform synthesis have made this task feasible for the first time. In this perspective, we discuss the advantages and challenges associated with developing proteoform-specific Nbs and how success in this endeavor will significantly advance the fields of therapeutics and diagnostics.

Antigens↗

DOE OSTI2025

From Pure to Seawater Electrolysis: Unveiling the Impact of Ionic Species and Contaminants on Electrocatalysis

Water electrolysis, including seawater splitting to produce hydrogen and oxygen, stands as a promising approach for the efficient storage of intermittent energy. However, the half-reactions of water splitting, the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), are known to be very sensitive toward the quality of water employed and are susceptible to contaminants originating from various sources, including the electrolyte or the electrodes. Those contaminants have a profound impact on the activity of these reactions of water splitting by modifying the electronic and physical structures of electrocatalysts as well as electrode–electrolyte interfaces. For seawater electrolysis, the unintentional presence of impurities, such as anions, cations, and organic compounds, affects the catalyst stability, selectivity, and activity. Despite the existence of numerous comprehensive reviews that delve into various aspects of catalysts and their structure–property relationships for several electrocatalytic reactions, the impact of contaminants has often been ignored. This critical review endeavors to address this issue by providing an overview of the diverse sources of contaminants influencing electrocatalytic water splitting and seawater splitting reactions, delineating the trends in electrochemical parameters and detailing different characterization methods for elucidating the physical and electronic changes of the electrode and electrolyte.

HER↗

DOE OSTI2023

A Suite of Constitutive Promoters for Tuning Gene Expression in Plants

The need for convenient tools to express transgenes over a large dynamic range is pervasive throughout plant synthetic biology; however, current efforts are largely limited by the heavy reliance on a small set of strong promoters, precluding more nuanced and refined engineering endeavors in planta . To address this technical gap, we characterize a suite of constitutive promoters that span a wide range of transcriptional levels and develop a GoldenGate-based plasmid toolkit named PCONS, optimized for versatile cloning and rapid testing of transgene expression at varying strengths. We demonstrate how easy access to a stepwise gradient of expression levels can be used for optimizing synthetic transcriptional systems and the production of small molecules in planta . We also systematically investigate the potential of using PCONS as an internal standard in plant biology experimental design, establishing the best practices for signal normalization in experiments. Although our library has primarily been developed for optimizing expression in N. benthamiana , we demonstrate the translatability of our promoters across distantly related species using a multiplexed reporter assay with barcoded transcripts. In conclusion, our findings showcase the advantages of the PCONS library as an invaluable toolkit for plant synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Vision and Development of a Design, Implementation, and Verification Automation (DIVA) Software Platform for DNA Construction

Abstract DNA construction, while a prerequisite to many biological endeavors, is often a time-consuming distraction from an individual’s primary research objectives. We envisioned that with the right software infrastructure and cultural mindset, a single person could execute in parallel the batched DNA construction tasks of an entire research institute, at scales realizing efficiency gains through process and laboratory automation. In pursuit of this vision, we developed the Design, Implementation, and Verification Automation (DIVA) software platform. DIVA’s web interface enables researchers to design DNA constructs (using visual biological computer-aided design tools and biological parts repositories), submit designs for construction to dedicated staff, and track DNA construction as it progresses. DIVA supports the dedicated staff through the DNA construction process and records both successful and unsuccessful attempts toward improving the overall process. The platform is publicly available at public-diva.jbei.org and its open-source code through github.com/JBEI/DIVA.

Plahar, Hector [DOE Agile BioFoundry , , ,; DOE Jo↗

DOE OSTI2025

Shake-Down Spectroscopy as State- and Site-Specific Probe of Ultrafast Chemical Dynamics

Tracking the multifarious ultrafast electronic and structural changes occurring in a molecule during a photochemical transformation is a challenging endeavor that benefits from recent experimental and computational progress in time-resolved techniques. Measurements of valence electronic states, which provide a global picture of the bonding structure of the molecule, and core electronic states, which provide insight into the local environment, traditionally require different approaches and are often studied separately. Here, we demonstrate that X-ray pulses from a seeded free-electron laser (FEL) enable the measurement of high-resolution, time-resolved X-ray photoelectron spectra (XPS) that capture weak satellite states resulting from shake-down processes in a valence-excited molecule. This approach effectively combines the advantages of both valence- and core-state investigations. We applied this method to investigate photoexcited CS2 molecules, where the role of internal conversion (IC) and intersystem crossing (ISC) in determining the predissociation dynamics is controversial. We present XPS spectra from photoexcited CS2, obtained at the FERMI FEL. High-resolution measurements, compared to the corresponding spectra obtained from accurate multireference quantum chemical calculations, reveal that shake-down satellite channels are highly sensitive to both valence electronic and geometric changes. Previous studies of the predissociation dynamics have led to uncertain assignments of the branching between singlet and triplet excited states. We derive a propensity rule that demonstrates the spin-selectivity of the shake-downs. This selectivity allows us to unequivocally assign contributions from the bright and dark singlet excited states, with populations tracked along the predissociation dynamic pathway.

Thompson, Henry J. [Univ. of Southampton (United K↗

DOE OSTI2022

Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Abstract This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman, et al., 2021b, https://doi.org/10.1029/2021EO153180 ) in Earth and Space Science Informatics (ESSI) and includes discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, cyberinfrastructure, and data sharing; (Section 3) Machine learning for multiscale modeling; (Section 4) Aerial and satellite remote sensing for advancing Earth system model development by integrating field and ancillary data. ESSI addresses data management practices, computation and analysis, and hardware and software infrastructure. Our role in ICON science therefore involves collaborative work to assess, design, implement, and promote practices and tools that enable effective data management, discovery, integration, and reuse for interdisciplinary work in Earth and space science disciplines. Networks of diverse people with expertise across Earth, space, and data science disciplines are essential for efficient and ethical exchanges of findable, accessible, interoperable, and reusable (FAIR) research products and practices. Our challenge is then to coordinate the development of standards, curation practices, and tools that enable integrating and reusing multiple data types, software, multi‐scale models, and machine learning approaches across disciplines in a way that is as open and/or FAIR as ethically possible. This is a major endeavor that could greatly increase the pace and potential of interdisciplinary scientific discovery.

58 GEOSCIENCES↗

DOE OSTI2022

Natural Hazards Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is about the state of ICON principles Goldman et al. (2021), https://doi.org/10.1029/2021EO153180 in natural hazards and a discussion on the opportunities and challenges of adopting them. Natural hazards pose risks to society, infrastructure, and the environment. Hazard interactions and their cascading phenomena in space and time can further intensify the impacts. Natural hazards’ risks are expected to increase in the future due to environmental, demographic, and socioeconomic changes. It is important to quantify and effectively communicate risks to inform the design and implementation of risk mitigation and adaptation strategies. Multihazard multisector risk management poses several nontrivial challenges, including: (a) integrated risk assessment, (b) Earth system data-model fusion, (c) uncertainty quantification and communication, and (d) crossing traditional disciplinary boundaries. Here, we review these challenges, highlight current research and operational endeavors, and underscore diverse research opportunities. We emphasize the need for integrated approaches, coordinated processes, open science, and networked efforts (ICON) for multihazard multisector risk management.

58 GEOSCIENCES↗

DOE OSTI2020

A reflection on lithium-ion battery cathode chemistry

Abstract Lithium-ion batteries have aided the portable electronics revolution for nearly three decades. They are now enabling vehicle electrification and beginning to enter the utility industry. The emergence and dominance of lithium-ion batteries are due to their higher energy density compared to other rechargeable battery systems, enabled by the design and development of high-energy density electrode materials. Basic science research, involving solid-state chemistry and physics, has been at the center of this endeavor, particularly during the 1970s and 1980s. With the award of the 2019 Nobel Prize in Chemistry to the development of lithium-ion batteries, it is enlightening to look back at the evolution of the cathode chemistry that made the modern lithium-ion technology feasible. This review article provides a reflection on how fundamental studies have facilitated the discovery, optimization, and rational design of three major categories of oxide cathodes for lithium-ion batteries, and a personal perspective on the future of this important area.

Science & Technology - Other Topics↗

DOE OSTI2022

Filming movies of attosecond charge migration in single molecules with high harmonic spectroscopy

Electron migration in molecules is the progenitor of chemical reactions and biological functions after light-matter interaction. Following this ultrafast dynamics, however, has been an enduring endeavor. Here we demonstrate that, by using machine learning algorithm to analyze high-order harmonics generated by two-color laser pulses, we are able to retrieve the complex amplitudes and phases of harmonics of single fixed-in-space molecules. These complex dipoles enable us to construct movies of laser-driven electron migration after tunnel ionization of N 2 and CO 2 molecules at time steps of 50 attoseconds. Moreover, the angular dependence of the migration dynamics is fully resolved. By examining the movies, we observe that electron holes do not just migrate along the laser polarization direction, but may swirl around the atom centers. Our result establishes a general scheme for studying ultrafast electron dynamics in molecules, paving a way for further advance in tracing and controlling photochemical reactions by femtosecond lasers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Lightweight single-phase Al-based complex concentrated alloy with high specific strength

Developing light yet strong aluminum (Al)-based alloys has been attracting unremitting efforts due to the soaring demand for energy-efficient structural materials. However, this endeavor is impeded by the limited solubility of other lighter components in Al. Here, we propose to surmount this challenge by converting multiple brittle phases into a ductile solid solution in Al-based complex concentrated alloys (CCA) by applying high pressure and temperature. We successfully develop a face-centered cubic single-phase Al-based CCA, Al 55 Mg 35 Li 5 Zn 5 , with a low density of 2.40 g/cm 3 and a high specific yield strength of 344×10 3 N·m/kg (typically ~ 200×10 3 N·m/kg in conventional Al-based alloys). Our analysis reveals that formation of the single-phase CCA can be attributed to the decreased difference in atomic size and electronegativity between the solute elements and Al under high pressure, as well as the synergistic high entropy effect caused by high temperature and high pressure. The increase in strength originates mainly from high solid solution and nanoscale chemical fluctuations. Our findings could offer a viable route to explore lightweight single-phase CCAs in a vast composition-temperature-pressure space with enhanced mechanical properties.

42 ENGINEERING↗

DOE OSTI2024

Hund’s coupling mediated multi-channel quantum phase transition of a single magnetic impurity in Fe(Se, Te)

Understanding the interplay between individual magnetic impurities and superconductivity is crucial for bottom-up construction of novel phases of matter. Sub-gap bound states that are used in this endeavor are typically considered as independent entities that each result from the exchange scattering between the respective impurity orbitals and electrons of the superconducting condensate. Here we present experimental evidence of individual multi-spin impurities where the sub-gap states are not independent. Specifically, we find that by tuning the energy of the state closest to zero through zero, all other sub-gap states change particle-hole asymmetry as well. We show that this can be understood by including Hund’s coupling, which favors high-spin configurations, into a multi-orbital Anderson model. Unlike for the case of independent spins, the transition we observe signals the simultaneous departure of more than one quasiparticle from the impurity, while the parity of the ground state may remain unchanged. Our results show that Hund’s coupling is not only crucial in generating high-spin impurities, but also to understand the transition between two distinct ground states, and should therefore be taken into account for e.g. impurity-based band-structure engineering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗

DOE OSTI2024

Candidate ferroelectrics via ab initio high-throughput screening of polar materials

Ferroelectrics are a class of polar and switchable functional materials with diverse applications, from microelectronics to energy conversion. Computational searches for new ferroelectric materials have been constrained by accurate prediction of the polarization and switchability with electric field, properties that, in principle, require a comparison with a nonpolar phase whose atomic-scale unit cell is continuously deformable from the polar ground state. For most polar materials, such a higher-symmetry nonpolar phase does not exist or is unknown. Here, we introduce a general high-throughput workflow that screens polar materials as potential ferroelectrics. We demonstrate our workflow on 1978 polar structures in the Materials Project database, for which we automatically generate a nonpolar reference structure using pseudosymmetries, and then compute the polarization difference and energy barrier between polar and nonpolar phases, comparing the predicted values to known ferroelectrics. Focusing on a subset of 182 potential ferroelectrics, we implement a systematic ranking strategy that prioritizes candidates with large polarization and small polar-nonpolar energy differences. To assess stability and synthesizability, we combine information including the computed formation energy above the convex hull, the Inorganic Crystal Structure Database id number, a previously reported machine learning-based synthesizability score, and ab initio phonon band structures. To distinguish between previously reported ferroelectrics, materials known for alternative applications, and lesser-known materials, we combine this ranking with a survey of the existing literature on these candidates through Google Scholar and Scopus databases, revealing ~130 promising materials uninvestigated as ferroelectric. Our workflow and large-scale high-throughput screening lays the groundwork for the discovery of novel ferroelectrics, revealing numerous candidates materials for future experimental and theoretical endeavors.

36 MATERIALS SCIENCE↗

DOE OSTI2024

RNA-Puzzles Round V: blind predictions of 23 RNA structures

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson–Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Ultra-Fast High-Precision Metallic Nanoparticle Synthesis using Laser-Accelerated Protons

Laser-driven proton acceleration, as produced during the interaction of a high-intensity (I > 1 × 10 18 W/cm 2 ), short pulse (<1 ps) laser with a solid target, is a prosperous field of endeavor for manifold applications in different domains, including astrophysics, biomedicine and materials science. These emerging applications benefit from the unique features of the laser-accelerated particles such as short duration, intense flux and energy versatility, which allow obtaining unprecedented temperature and pressure conditions. In this paper, we show that laser-driven protons are perfectly suited for producing, in a single sub-ns laser pulse, metallic nanocrystals with tunable diameter ranging from tens to hundreds of nm and very high precision. Our method relies on the intense and very quick proton energy deposition, which induces in a bulk material an explosive boiling and produces nanocrystals that aggregate in a plasma plume composed by atoms detached from the proton-irradiated surface. The properties of the obtained particles depend on the deposited proton energy and on the duration of the thermodynamical process. Suitably controlling the irradiated dose allows fabricating nanocrystals of a specific size with low polydispersity that can easily be isolated in order to obtain a monodisperse nanocrystal solution. Molecular Dynamics simulations confirm our experimental results.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Absolute contrast estimation for soft X-ray photon fluctuation spectroscopy using a variational droplet model

Abstract X-ray photon fluctuation spectroscopy using a two-pulse mode at the Linac Coherent Light Source has great potential for the study of quantum fluctuations in materials as it allows for exploration of low-energy physics. However, the complexity of the data analysis and interpretation still prevent recovering real-time results during an experiment, and can even complicate post-analysis processes. This is particularly true for high-spatial resolution applications using CCDs with small pixels, which can decrease the photon mapping accuracy resulting from the large electron cloud generation at the detector. Droplet algorithms endeavor to restore accurate photon maps, but the results can be altered by their hyper-parameters. We present numerical modeling tools through extensive simulations that mimic previous x-ray photon fluctuation spectroscopy experiments. By modification of a fast droplet algorithm, our results demonstrate how to optimize the precise parameters that lift the intrinsic counting degeneracy impeding accuracy in extracting the speckle contrast. These results allow for an absolute determination of the summed contrast from multi-pulse x-ray speckle diffraction, the modus operandi by which the correlation time for spontaneous fluctuations can be measured.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Tracking blobs in the turbulent edge plasma of a tokamak fusion device

Abstract The analysis of turbulence in plasmas is fundamental in fusion research. Despite extensive progress in theoretical modeling in the past 15 years, we still lack a complete and consistent understanding of turbulence in magnetic confinement devices, such as tokamaks. Experimental studies are challenging due to the diverse processes that drive the high-speed dynamics of turbulent phenomena. This work presents a novel application of motion tracking to identify and track turbulent filaments in fusion plasmas, called blobs, in a high-frequency video obtained from Gas Puff Imaging diagnostics. We compare four baseline methods (RAFT, Mask R-CNN, GMA, and Flow Walk) trained on synthetic data and then test on synthetic and real-world data obtained from plasmas in the Tokamak à Configuration Variable (TCV). The blob regime identified from an analysis of blob trajectories agrees with state-of-the-art conditional averaging methods for each of the baseline methods employed, giving confidence in the accuracy of these techniques. By making a dataset and benchmark publicly available, we aim to lower the entry barrier to tokamak plasma research, thereby greatly broadening the community of scientists and engineers who might apply their talents to this endeavor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗