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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Laser-Induced Enhancement of Acoustic Mode Quality Factor Revealed by Correlated Single-Particle Optical and Electron Microscopy

Acoustic modes in plasmonic nanostructures provide fundamental insights into their optomechanical behavior at the nanoscale, enabling emerging applications in plasmon-enhanced optomechanics, ultrasensitive sensing, and nanoscale energy transduction. Here we explore the modulation of acoustic phonon dynamics in lithographically fabricated gold nanodisks via laser-induced photothermal annealing. Using a correlated approach that utilizes both single-particle transient extinction spectroscopy and advanced electron microscopy, we directly link nanoscale structural transformations to changes in mechanical properties as probed through the coherence of the excited acoustic modes. Specifically, ultrafast pump–probe microscopy reveals an enhancement in the acoustic mode quality factor of annealed gold nanodisks, indicative of reduced damping and improved vibrational coherence. Structural characterization via scanning electron microscopy and electron backscatter diffraction confirms that photoinduced annealing results in smoother surface morphology and overall enhanced crystallinity. The improved crystalline order reduces defect and crystal boundary scattering, which we suggest as the reason underlying the lower quality factor before annealing. Furthermore, these findings demonstrate that targeted structural engineering at the nanoscale offers a powerful strategy for optimizing the optomechanical performance of plasmonic nanostructures, with broad implications for the design of next-generation nanophotonic and optomechanical systems.

Annealing (metallurgy)↗
DOE OSTI2020

Efficient Hot Electron Transfer from Small Au Nanoparticles

Many important chemical transformations enabled by plasmonic hot carrier photocatalysis have been reported, although their efficiencies are often too low for practical applications. Here, we examine how the efficiency of plasmon-induced hot electron transfer depends on the Au particle size in Au-tipped CdS nanorods. We show that with decreasing Au size, the plasmon width increases due to enhanced surface damping contributions. The excitation of Au nanoparticles leads to an instrument response time-limited ultrafast hot electron transfer process to CdS ($\ll$140 fs). The quantum efficiency of this process increases from ~1% to ~18% as the particle size decreases from 5.5 ± 1.1 to 1.6 ± 0.5 nm due to both enhanced hot electron generation and transfer efficiencies in small Au particles. Our finding suggests that decreasing plasmonic particle size is an effective approach for improving plasmon-induced hot carrier transfer efficiency and provides important insight for the rational improvement of plasmonic hot carrier-based devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Stabilization of Low Valent Zirconium Nitrides in Titanium Nitride via Plasma-Enhanced Atomic Layer Deposition and Assessment of Electrochemical Properties

The increasing awareness of metal nitrides as feasible electrocatalysts in numerous energy-relevant transformations motivates greater synthetic control of mixed metal nitride compositions and their valence states. We report plasma-enhanced atomic layer deposition of titanium zirconium nitride, with an emphasis on the experimental parameters that influence the valence states of the two metal ions. We further examined the consequence of various ratios of Ti and Zr on the electrochemically active surface areas (ECSAs). Films with a Zr-to-Ti ratio of 1:2 or 1:1 yielded the highest ECSA; deviation from these values led to a large fraction of electrically insulating or semiconducting titanium or zirconium oxynitrides/oxides. The systematic examination establishes a fundamental structure-property relationship critical to assessing the electrochemical/electrocatalytic properties of metal nitrides.

36 MATERIALS SCIENCE↗
DOE OSTI2023

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Interlaminar improvement of carbon fiber/epoxy composites via fluorine‐containing high‐epoxy‐value sizing agent

Abstract To improve the interfacial bonding effect of carbon fibers (CFs) and epoxy resins, we prepared a fluorine‐containing high‐epoxy‐value sizing agent (named TS) in this article. It is an emulsion with a more uniform particle size distribution and higher stability better than a commercial Takemoto sizing agent. In addition, sulfonic acid groups can improve the hydrophilicity of the TS, and the presence of epoxy groups enhances the wettability between CFs and the matrix. The properties of the sizing agents were examined by Fourier transform infrared spectroscopy, dynamic light scattering, and thermogravimetric analysis. The sized CFs were evaluated by scanning electron microscopy, x‐ray photoelectron spectroscopy, monofilament tensile test, and dynamic contact angle. Afterward, CF/epoxy composites were prepared, and their fracture morphology and interlaminar shear strength (ILSS) were examined. Results indicated that the TS sizing significantly increased the content of activated carbon on the surface of the CFs and improved the bonding effect between the fiber and the matrix. After TS was sized, the ILSS increased from 49.64 to 58.74 MPa, 18.34% higher than unsized CF/epoxy composites, showing the prominent interfacial reinforcement better than commercial Takemoto.

Qiu, Zhijie↗
DOE OSTI2022

Hierarchically structured MoO 2 /dopamine-derived carbon spheres as intercalation electrodes for lithium-ion batteries

A hydrogen peroxide initiated sol-gel process involving molybdenum transformation in the presence of dopamine (Dopa) hydrochloride excess produced the metastable precipitate composed of polydopamine (PDopa) spheres coated with Dopa preintercalated molybdenum oxide, (Dopa) x MoO y @PDopa. The hydrothermal treatment (HT) of the (Dopa) x MoO y @PDopa precursor resulted in the simultaneous carbonization of Dopa and molybdenum reduction generating MoO 2 nanoplatelets distributed and confined on the surface of the Dopa-derived carbon matrix (HT-MoO 2 /C). The consecutive annealing (An) of the HT-MoO 2 /C sample at 600 °C under Ar atmosphere led to the formation of MoO 2 with increased Mo oxidation state and improved structural stability (AnHT-MoO 2 /C). Annealing had also further facilitated interaction between the molybdenum-derived and Dopa-derived components resulting in the modification of the carbon matrix confirmed by Raman spectroscopy. Morphology of both materials is best described as Dopa-derived carbon spheres decorated with MoO 2 nanoplatelets. These integrated metal oxide and carbon structures were tested as electrodes for lithium-ion batteries in the potential window that corresponds to the intercalation mechanism of charge storage. The AnHT-MoO 2 /C electrode showed enhanced electrochemical activity, with an initial specific discharge capacity of 260 mAh/g and capacity retention of 67% after 50 cycles, compared to the HT-MoO 2 /C electrode which exhibited an initial specific discharge capacity of 235 mAh g –1 and capacity retention of 47% after 50 cycles. The rate capability experiments revealed that the capacity of 93 mAh/g and 120 mAh/g was delivered by the HT-MoO 2 /C and AnHT-MoO 2 /C electrodes, respectively, when the current density was increased to 100 mA/g. Here, the improved specific capacity, electrochemical stability, and rate capability achieved after annealing were attributed to higher crystallinity of MoO 2 , increased oxidation state of Mo, and formation of the tighter MoO 2 /carbon contact accompanied by the annealing assisted interaction between MoO 2 and Dopa-derived carbon.

25 ENERGY STORAGE↗
DOE OSTI2022

Intensity Modulated Fiber Optic Sensor: A Novel Grid Measurement Unit

This paper presents a novel approach to physical displacement-based power grid measuring via an Intensity Modulated Fiber Optic Sensor (IMFOS). An IMFOS utilizes one fiber to transmit the intensity modulation light from its Electro-Optic controller to a fiber optic probe. The power grid voltage and current can induce physical displacements in transducers via the piezoelectric effect and the Lorentz law, respectively, which then result in a distance change between the optical probe and the reflective surface of the transducers. In parallel, multiple fibers are used to collect the reflective light for electro-optic conversion. Furthermore, a National Instruments-based characterization platform is set up for performance evaluation. Here, the testing result demonstrates that the IMFOS is immune to the inherent DC and low-frequency saturation issues prevalent in conventional potential and current transformers. Finally, the IMFOS is implemented in a Universal Grid Analyzer to illustrate its applicability for phasor estimation in actual power grids.

42 ENGINEERING↗
DOE OSTI2026

Advanced LiFSI-LiPF6 Electrolyte for Wide-Temperature and Thermally Stable Lithium-Ion Batteries

A new optimized LiFSI–LiPF6 dual-salt controlled-solvation electrolyte (E-DS) is demonstrated to enable practical graphite||LiNi0.8Mn0.1Co0.1O2 cells (˜4.0 mAh cm?²) to achieve exceptional performance and safety under extreme conditions. By optimizing anion coordination with the smaller, more dissociating FSI? anion, the E-DS forms ultrathin, dense, and inorganic-rich electrode/electrolyte interphases that dramatically suppress solvent decomposition, transition-metal dissolution, and surface reconstruction compared to the conventional LiPF6/carbonate electrolyte. Consequently, E-DS cells deliver >78% capacity retention after 300 cycles at 60 °C, retain fast discharging capacity at 30 °C, and operate effectively at -20 °C. Most strikingly, fully charged full cells with E-DS, even under overcharging to 4.8 V, show a lower heat evolution in stable formulations — transforming a traditionally unstable high-voltage/high-temperature configuration into an intrinsically safe state. This work establishes a new benchmark for carbonate-containing electrolytes, simultaneously achieving high energy density, fast-discharging capability, wide-temperature operation (-20 to 60 °C), and outstanding thermal safety in nickel-rich lithium-ion batteries.

electrode/electrolyte interphase↗
DOE OSTI2021

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Unraveling the adsorption-limited hydrogen oxidation reaction at palladium surface via in situ electron microscopy

Palladium (Pd) catalysts have been extensively studied for the direct synthesis of H 2 O through the hydrogen oxidation reaction at ambient conditions. This heterogeneous catalytic reaction not only holds considerable practical significance but also serves as a classical model for investigating fundamental mechanisms, including adsorption and reactions between adsorbates. Nonetheless, the governing mechanisms and kinetics of its intermediate reaction stages under varying gas conditions remain elusive. This is attributed to the intricate interplay between adsorption, atomic diffusion, and concurrent phase transformation of catalyst. Herein, the Pd-catalyzed, water-forming hydrogen oxidation is studied in situ, to investigate intermediate reaction stages via gas cell transmission electron microscopy. The dynamic behaviors of water generation, associated with reversible palladium hydride formation, are captured in real time with a nanoscale spatial resolution. Our findings suggest that the hydrogen oxidation rate catalyzed by Pd is significantly affected by the sequence in which gases are introduced. Through direct evidence of electron diffraction and density functional theory calculation, we demonstrate that the hydrogen oxidation rate is limited by precursors’ adsorption. These nanoscale insights help identify the optimal reaction conditions for Pd-catalyzed hydrogen oxidation, which has substantial implications for water production technologies. The developed understanding also advocates a broader exploration of analogous mechanisms in other metal-catalyzed reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Influence of Water, Vacuum, and Temperature on Surface Conditions of a Zeolite‐based Molecular Sieve

Molecular sieves such as zeolite-based materials are ubiquitous in industrial separation processes. However, there is a significant gap in understanding the surface properties and adsorption mechanisms for commercial zeolites, as most research focuses on pure zeolite powders rather than industrially relevant forms. Here, this work addresses this gap in understanding by employing advanced characterization techniques, including positron annihilation spectroscopy, X-ray diffraction, scanning electron microscopy, X-ray fluorescence spectroscopy, X-ray photoelectron spectroscopy, liquid nitrogen sorption, and Fourier-transform infrared spectroscopy, to investigate the adsorption and desorption behavior of water in commercial zeolite 13X. Our research reveals insights into the pore-filling mechanisms, the impact of material binders on adsorption properties, and the dynamics of hydration and drying processes for zeolites. Monitoring changes on a minute scale allowed the distinction between fast and slow processes leading to sample drying. The identification of positronium bound to Na + ions indicated that water molecules remain in the vicinity of Na + ions after air-drying zeolite 13X. These findings highlight the importance of various environmental conditions in restoring zeolite properties to baseline after hydration, with significant implications for optimizing industrial processes. This work sets the direction for further research aimed at developing more efficient and robust separation techniques.

Beads Binder↗
DOE OSTI2020

High-throughput synthesis and corrosion behavior of sputter-deposited nanocrystalline Al x (CoCrFeNi) 100-x combinatorial high-entropy alloys

High-entropy alloys (HEAs) are inherently complex and potentially span a vast composition space, making their research and discovery challenging. In the present study, high-throughput synthesis of an Al x (CoCrFeNi) 100-x combinatorial material library covering x = 4.5–40 atomic percent Al is achieved, using magnetron cosputtering. The effects of Al on the microstructure and corrosion behavior are investigated. With the increased amount of Al, crystal-structures of thin films transform from face-centered cubic (FCC) to body-centered cubic (BCC). Both the FCC and BCC thin films demonstrate a uniform elemental distribution. Corrosion characteristics of combinatorial samples immersed in the 3.5 wt% (wt%) NaCl solution are evaluated via electrochemical tests. Complementary X-ray photoelectron spectroscopy analysis reveals the compositional variation of passivated films formed on the sample surface after immersion. The results show that the Al x (CoCrFeNi) 100-x HEA thin films possess outstanding corrosion-resistant properties, but the resistance diminishes with the increasing Al content. The decreased corrosion resistance is revealed to be directly related to the constituents of passivated films.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Arsenic stabilization performance of a novel starch-modified Fe-Mn binary oxide colloid

Arsenic (As) is an environmentally hazardous contaminant and can be a serious threat to human health. In China, remediation needs for a large number of As-contaminated sites renders a strong demand for efficient remedial reagents and cost effective approaches. In this study, a novel starch-modified Fe-Mn binary oxide (SFM), an amorphous colloidal material, has been synthesized as a remedial reagent and its As stabilization performance has been evaluated. A set of laboratory batch experiments were carried out by directly adding SFM of different dosages into three contaminated soils. Results demonstrated that SFM could transform As in soil from non-specifically and specifically sorbed fractions to the more stable form bounded to amorphous iron hydrous oxides, thus reducing the As concentration in TCLP leachates by 42.0-93.2%. Results from adsorption tests and microscopic analysis indicated that the interactions between SFM and As are mainly controlled by adsorption, oxidation, and precipitation processes. SFM has abundant surface hydroxyl groups, with excellent adsorption properties for both As(V) and As(III), with the maximum adsorption capacities of 160.63 and 284.64 mg/g respectively at pH 7.0. The adsorption process closely fitted pseudo second-order kinetics and Freundlich isotherm model. SFM could increase soil Eh and oxidize As(III) to As(V), which facilitated the As stabilization in soilColloidal iron-based material directly used for stabilization in As contaminated soils is reported here for the first time. Starch modification improves both the reactivity and mobility of SFM in soil. Our findings propose an efficient and convenient reagent for As remediation in soil.

Yan, Xiulan↗
DOE OSTI2025

Discovering Ni/Cu Single-Atom Alloy as a Highly Active and Selective Catalyst for Direct Methane Conversion to Ethylene: A First-Principles Kinetic Study

Direct methane conversion to liquid fuels or value-added chemicals is a promising technology to utilize natural resources without resorting to further petroleum extraction. However, discovering efficient catalysts for this reaction is challenging due to either coke formation or unfavorable C-H bond activation. Herein, we design single-atom alloy (SAA) catalysts to simultaneously eliminate the above two bottlenecks based on mechanism-guided strategies: (1) the active single atom enables favorable C-H bond breaking and (2) the less reactive host metal facilitates C-C coupling and thus avoids strong binding of carbonaceous species. Employing electronic structure theory calculations, we screened the stability of multiple SAAs with 3d-5d transition metals atomically dispersed on a copper surface in terms of avoiding dopant aggregation and segregation. We then evaluated reactivities of the stable SAAs as catalysts for direct methane conversion to C2 products, including methane dehydrogenation and C-C coupling mechanisms. Combining selectivity analysis with kinetic modeling, we predicted that nickel dispersed on copper, i.e., Ni/Cu SAA, is a highly active and selective catalyst that can efficiently transform methane to ethylene. This work designs efficient SAA catalysts for direct methane activation and provides chemical insights into engineering compositions of SAAs to tune their catalytic performances.

Kothakonda, Manish↗
DOE OSTI2021

Creation and observation of Hopfions in magnetic multilayer systems

Among topological solitons, magnetic skyrmions are two-dimensional particle-like objects with a continuous winding of the magnetization, and magnetic Hopfions are three-dimensional objects that can be formed from a closed loop of twisted skyrmion strings. Theoretical models suggest that magnetic Hopfions can be stabilized in frustrated or chiral magnetic systems, and target skymions can be transformed into Hopfions by adapting their perpendicular magnetic anisotropy, but their experimental verification has been elusive so far. Here, we present an experimental study of magnetic Hopfions that are created in Ir/Co/Pt multilayers shaped into nanoscale disks, known to host target skyrmions. To characterize three-dimensional spin textures that distinguish Hopfions from target skyrmions magnetic images are recorded with surface-sensitive X-ray photoemission electron microscopy and bulk-sensitive soft X-ray transmission microscopy using element-specific X-ray magnetic circular dichroism effects as magnetic contrast. These results could stimulate further investigations of Hopfions and their potential application in three-dimensional spintronics devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transient superconductivity at nano- and meso-scales

High-T c superconductivity is surpassed by few, if any, other unsolved problems in contemporary physics in terms of its richness, complexity, impact on other fields, and potential technological importance in energy applications. Recent discoveries reveal that the highest transition temperatures emerge under extraordinary experimental conditions such as the strong perturbation of a single atomic layer material by the underlying substrate, application of ~200 GPa pressure or ~MV/cm static electric fields, or irradiation by intense femtosecond optical fields. Research in superconductivity under extreme experimental conditions is challenging and requires the development of novel experimental methods and new theoretical tools suitable to tackle the problem. Our team has approached the challenges of transient superconductivity under intense optical fields by rethinking the types of experimental observables that are best suited to elucidate the physics of light-induced effects. This exercise has identified the need for: i) ultra-fast spatio-temporal probes enabling access to plasmonic properties and also nano-scale inhomogeneities that are ubiquitous in unconventional superconductors; ii) meso-scale structures and hybrid meta-surfaces imperative for strong enhancement of optical fields and iii) theoretical approaches suitable to explain and predict the response of superconductors under ultra-fast photo-excitation. Co-PIs have already made major advances with developing capabilities i)-iii). Therefore, our team is poised to make significant progress in transient superconductivity by exploring novel spatio-temporal effects that currently remain unattainable. Co-investigators will search for light-induced superconductivity in the high-T c cuprates to build upon spectacular recent results still lacking independent confirmations. Novel data acquisition methods combined with nano-plasmonic imaging will allow our team to test the hypothesis of photo-induced superconducting pairing. Spatio-temporal experiments will provide insights into the interplay between superconductivity and competing orders in the cuprates. Co-PIs will also investigate strong light-matter interaction and superconductivity in FeSe monolayers. Finally, we will study spatio-temporal electrodynamics of planar Josephson junctions. This latter direction will allow our team to thoroughly characterize one of the most fundamental examples of inhomogeneity in all of unconventional superconductivity. The proposed experiments in combination with theoretical analysis will provide information that is difficult to obtain using alternative methods. Basov and Averitt will carry out pump-probe spectroscopy and nano-imaging experiments. Averitt and Hone will design and fabricate state-of-the-art meta-surfaces. Theoretical and computational studies of ultrafast transient phenomena will be carried out by Millis and Fogler. Modeling of time-resolved nano-optical effects will be done by Fogler. The bulk of the requested budget will be used to support graduate students at Columbia & UCSD that will be co-supervised by co-PIs. The proposed program is transformative, since it will enable an entire suite of experiments previously either impossible or technically implausible. It will deliver critically important insights not only into mechanisms of unconventional superconductivity but also to many other correlated quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multiplexed Inertial Coalescence Filters for High-Rate Liquid-Gas Chemistry

The aim of this project is to support the development of a disruptive method for deploying liquids in liquid-gas chemical processes to transform carbon dioxide capture from flue gas and ambient air streams. The proposed project is based on the development of a novel filtration method called the Helix MICRA™ (Multiplexed Inertial Coalescence Refining Apparatus) filters. Helix MICRA™ filters are a novel, patented filter that enable high efficiency, low-pressure drop capture of droplet streams. Liquid droplets have a large net-surface area per unit volume and have correspondingly rapid mass transfer rates. By effectively capturing these droplets after deployment, we enable high-rate carbon dioxide capture from air streams unlike any other technology. This project aims at using Helix MICRA™ filters to create efficient and compact carbon dioxide capture systems that would dramatically reduce system size and capital costs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Accelerated Sequence Design of Star Block Copolymers: An Unbiased Exploration Strategy via Fusion of Molecular Dynamics Simulations and Machine Learning

Star block copolymers (s-BCPs) have potential applications as novel surfactants or amphiphiles for emulsification, compatibilization, chemical transformations, and separations. s-BCPs have chain architectures where three or more linear diblock copolymer arms comprised of two chemically distinct linear polymers, e.g., solvophobic and solvophilic chains, are covalently joined at one point. The chemical composition of each of the subunit polymer chains comprising the arms, their molecular weights, and the number of arms can be varied to tailor the surface and interfacial activity of these architecturally unique molecules. Further, this makes identification of the optimal s-BCP design nontrivial as the total number of plausible s-BCP architectures is experimentally or computationally intractable. In this work, we use molecular dynamics (MD) simulations coupled with a reinforcement learning-based Monte Carlo tree search (MCTS) to identify s-BCP designs that minimize the interfacial tension between polar and nonpolar solvents. We first validate the MCTS approach for the design of small- and medium-sized s-BCPs and then use it to efficiently identify sequences of copolymer blocks for large-sized s-BCPs. The structural origins of interfacial tension in these systems are also identified by using the configurations obtained from MD simulations. Chemical insights into the arrangement of copolymer blocks that promote lower interfacial tension were mined using machine learning (ML) techniques. Overall, this work provides an efficient approach to solve design problems via fusion of simulations and ML and provides important groundwork for future experimental investigation of s-BCPs for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗