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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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638 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Internally Catalyzed Hydrogen Atom Transfer (I-CHAT)—A New Class of Reactions in Combustion Chemistry

The current paradigm of low-T combustion and autoignition of hydrocarbons is based on the sequential two-step oxygenation of fuel radicals. The key chain-branching occurs when the second oxygenation adduct (OOQOOH) is isomerized releasing an OH radical and a key ketohydroperoxide (KHP) intermediate. The subsequent homolytic dissociation of relatively weak O–O bonds in KHP generates two more radicals in the oxidation chain leading to ignition. Based on the recently introduced intramolecular “catalytic hydrogen atom transfer” mechanism (J. Phys. Chem. 2024, 128, 2169), abbreviated here as I-CHAT, we have identified a novel unimolecular decomposition channel for KHPs to form their classical isomers—enol hydroperoxides (EHP). The uncertainty in the contribution of enols is typically due to the high computed barriers for conventional (“direct”) keto–enol tautomerization. Remarkably, the I-CHAT dramatically reduces such barriers. The novel mechanism can be regarded as an intramolecular version of the intermolecular relay transfer of H-atoms mediated by an external molecule following the general classification of such processes (Catal. Rev.-Sci. Eng. 2014, 56, 403). Here, we present a detailed mechanistic and kinetic analysis of the I-CHAT-facilitated pathways applied to n-hexane, n-heptane, and n-pentane models as prototype molecules for gasoline, diesel, and hybrid rocket fuels. We particularly examined the formation kinetics and subsequent dissociation of the γ-enol-hydroperoxide isomer of the most abundant pentane-derived isomer γ-C5-KHP observed experimentally. To gain molecular-level insight into the I-CHAT catalysis, we have also explored the role of the internal catalyst moieties using truncated models. All applied models demonstrated a significant reduction in the isomerization barriers, primarily due to the decreased ring strain in transition states. In addition, the longer-range and sequential H-migration processes were also identified and illustrated via a combined double keto–enol conversion of heptane-2,6-diketo-4-hydroperoxide as a potential chain-branching model. To assess the possible impact of the I-CHAT channels on global fuel combustion characteristics, we performed a detailed kinetic analysis of the isomerization and decomposition of γ-C5-KHP comparing I-CHAT with key alternative reactions—direct dissociation and Korcek channels. Calculated rate parameters were implemented into a modified version of the n-pentane kinetic model developed earlier using RMG automated model generation tools (ACS Omega, 2023, 8, 4908). Simulations of ignition delay times revealed the significant effect of the new pathways, suggesting an important role of the I-CHAT pathways in the low-T combustion of large alkanes.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Healable Coatings as a Mechanism to Repair Leading Edge Erosion in Wind Energy

Wind turbine blades are highly engineered structures designed to face temperature extremes and high winds. However, erosion of the blade's leading edge and subsequent repair remains a significant and costly challenge for the wind energy industry. Repair of these leading edges can lead to large amounts of downtime for the turbine and significant operational inefficiencies. In this work, the strength of adhesion and healing ability of a commercially available vitrimer (Mallinda's VITRIMAX) was compared to that of a thermoplastic resin, which has previously been demonstrated in wind energy applications (Arkema's Elium) to evaluate their efficacy as surface coatings for wind turbine blades, particularly their leading edges. Vitrimers are a class of inherently reprocessable thermosets, and it was theorized that vitrimer-based leading edge coatings could enable more robust and efficient wind turbine blades with decreased operational downtime and safer maintenance practices. It was found that the VITRIMAX adhered better to the wind blades' surfaces than both the manufacturer's paint and Elium, with increases in pull-off strength of adhesion ranging from 24% to 83% above that of the original paint. Furthermore, the VITRIMAX adhered strongly to the underlying composite of each blade with strength of adhesion values increasing in ranges from 42% to 97% above that of the original paint. Finally, the vitrimer coating showed an 88% decrease in surface roughness compared to end-of-life blade materials, and initial healing demonstrations in which coatings were manually scratched and subsequently healed exhibited an ~84.5% decrease in scratch depths.

Hubbard, Amber [ORNL]↗
DOE OSTI2026

Thermodynamics of Tritium Trapping by Point Defects at Interfacial Cr-based Phases of the Al Coating

Density functional theory (DFT) simulations have been carried out to evaluate the potential for tritium trapping by metal vacancies in four phases Cr-containing phases (i.e., Cr3Si, Al0.3Cr0.7, Al8Cr5-HT, and Al8Cr5) identified near the interface between the Al coating and 316 stainless steel (316 SS) cladding. In addition, an ab initio thermodynamics approach has been employed to predict the temperature and T2-partial pressure dependence on the thermodynamics of singly tritiated defects. Key results in this work suggest that metal vacancies in the four phases have the potential to favorably trap tritium species, especially Si vacancies in Cr3Si phase. This overall thermodynamic trend can be correlated to the energy cost of having an interstitial tritium in the lattice, which has been calculated to range from 0.17 eV in Al8Cr5-HT to 0.89 eV in Cr3Si. A comparison of the results from this study with previous theoretical works investigating tritium behavior in other Fe-Al phases identified in the aluminide coating, suggests that metal vacancies are generally able to trap tritium in various Fe-Al aluminide phases. Especially, it was found that Si and Al vacancies would be the most efficient to trap for tritium, followed by Cr vacancies, then Fe and Ni vacancies. In the four Cr-based material phases investigated in this work, it is interesting to note that, in the absences of Fe or Ni species, strong interactions between tritium and the metal vacancies are always occurring by the formation of preferential Cr—T bonds (i.e., no Si—T or Al—T bonds were formed).

Sassi, Michel J.↗
DOE OSTI2026

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗
DOE OSTI2026

Enhanced matter power spectrum from axion kination after Big Bang nucleosynthesis

Despite stringent constraints from Big Bang Nucleosynthesis (BBN) and cosmic microwave background (CMB) observations, it is still possible for well-motivated particle physics models to substantially alter the cosmic expansion history between BBN and recombination. In this work we consider two different axion models that can realize a period of first matter domination, then kination, in this epoch. We perform fits to both primordial element abundances as well as CMB data and determine that up to a decade of late axion domination is allowed by these probes of the early universe. We establish the implications of late axion domination for the matter power spectrum on the scales 1/Mpc ≲ k ≲ 10 3 /Mpc. Our 'log' model predicts a relatively modest bump-like feature together with a small suppression relative to the standard ΛCDM predictions on either side of the enhancement. Our 'two-field' model predicts a larger, plateau-like feature that realizes enhancements to the matter power spectrum of up to two orders of magnitude. These features have interesting implications for structure formation at the forefront of current detection capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Recent Progress in the Electroweak Structure of Light Nuclei Using Quantum Monte Carlo Methods

Nuclei will play a prominent role in searches for physics beyond the Standard Model as the active material in experiments. In order to reliably interpret new physics signals, one needs an accurate model of the underlying nuclear dynamics. In this review, we discuss recent progress made with quantum Monte Carlo approaches for calculating the electroweak structure of light nuclei. We place particular emphasis on recent β decay, muon capture, neutrinoless double β decay, and electron scattering results.

Physics↗
DOE OSTI2026

Impacts of Multidimensional Progenitor Perturbations on Core-collapse Supernova Explosions

Numerical studies of core-collapse supernovae have demonstrated the importance of nonradial motions in precollapse progenitors on the explosion outcome. We use the Chimera neutrino radiation hydrodynamics code running seven two-dimensional simulations of 15 M⊙ progenitors with different progenitor structures introduced by different one- and two-dimensional precollapse stellar evolution environments to examine the impacts of stellar structure and nonspherical motion in the precollapse progenitor on the development of explosions. We compare the explosion evolution of these models in terms of shock dynamics, diagnostic energy, neutrino heating, accretion, explosion geometry, nuclear abundances, and turbulent convection. We also analyze how stochastic variation impacts our simulations. Contrary to results reported in prior studies examining the impacts of multidimensional progenitors, we observe similar shock revival times and explosion development in our simulations despite differences in initial compositions and structures. We find no discernible impact from the accretion of nonradial perturbations from a multi-D progenitor onto the stalled shock in the revival and strength of explosion, as fully developed neutrino-driven convection behind the stalled shock is similar for all our models. For models with physically sourced noise in the iron core, a strong oscillation of the shock occurs after bounce and deflects infall laterally, and accelerates the saturation of the lateral turbulent kinetic energy. An examination of model stochasticity shows that any prior expected impacts on explosive outcome due to convection-related perturbations lie below the detectable threshold of numerical variation.

Chen, Chien-Hui [North Carolina State University]↗
DOE OSTI2024

User-Centric Communication With Aerial Network for 6G: A Reinforcement Learning Approach

Meeting the diverse needs of user verticals requires innovative cellular architectures that can offer additional degrees of freedom to provide on-demand services. The terrestrial user-centric radio access network (UC-RAN) stands out as an excellent choice for this purpose. However, a drawback of UC-RAN is its tendency to prioritize high-priority verticals, often resulting in a subpar quality of experience for low-priority verticals. This issue is particularly exacerbated in hotspot areas. Here, to address this problem, we introduce an aerial network integrated with terrestrial UC-RAN to provide coverage to users which are not served by the terrestrial network. Furthermore, we analyze the impact of key configuration and optimization parameters (COPs), such as location, transmit power, altitude, and beamwidth of aerial base stations (ABSs) on system key performance indicators (KPIs), such as coverage, latency satisfaction, average spectral efficiency, and energy efficiency. We formulate a robust multiobjective function to maximize these KPIs without biasing toward any specific KPI(s). Finally, we propose a deep reinforcement learning optimization framework based on the state-of-the-art soft actor-critic algorithm to control ABS COPs and optimize system KPIs. Experimental evaluations demonstrate that the proposed optimization framework can converge to near-optimal solutions derived from the pseudo brute force in a few thousand epochs.

6G↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2026

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)↗
DOE OSTI2026

An Automated Probabilistic Asteroid Prediscovery Pipeline

We present an automated and probabilistic method to make prediscovery detections of near-Earth asteroids (NEAs) in archival survey images, with the goal of reducing orbital uncertainty immediately after discovery. We refit the Minor Planet Center's astrometry and propagate the full six-parameter covariance to survey epochs to define search regions. We build low-threshold source catalogs for viable images and evaluate every detected source in a search region as a candidate prediscovery. We eliminate false positives by refitting a new orbit to each candidate and probabilistically linking detections across images using a likelihood ratio. Applied to the Zwicky Transient Facility's (ZTF) imaging, we identify approximately 3000 recently discovered NEAs with prediscovery potential, including a doubling of the observational arc for about 500. We use archival ZTF imaging to make prediscovery detections of the potentially hazardous asteroid 2021 DG1, extending its arc by 2.5 yr and reducing future apparition sky plane uncertainty from many degrees to arcseconds. We also recover 2025 FU24 nearly 7 yr before its first known observation, when its sky plane uncertainty covers hundreds of square degrees across thousands of ZTF images. The method is survey agnostic and scalable, enabling rapid orbit refinement for new discoveries from Rubin, NEO Surveyor, and NEOMIR.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A comparison of wrought and powder metallurgical FeCrAl claddings under simulated LWR accident transients

Iron-chromium-aluminum (FeCrAl) alloys are potential accident tolerant fuel (ATF) cladding candidates for light-water reactors but are difficult to fabricate as thin-walled tubes via conventional cast-and-wrought routes. Powder metallurgy (PM) offers a manufacturing alternative with improved compositional control, but its transient accident performance has not been directly benchmarked against wrought variants. This study evaluates the burst behavior of commercially developed PM-processed FeCrAl alloys, PM-C26M (Fe-12Cr-6Al-2Mo) and the high precipitate density FA-SMT (Fe-22Cr-5Al-3Mo), under simulated light-water reactor accident transient conditions. Burst testing was conducted using the Severe Accident Test Station with heating rates of 5 °C/s and 50 °C/s and internal pressures ranging from 25 MPa to 100 MPa. PM-C26M reproduced wrought C26M burst behavior within 7–37 °C across the stress range, indicating that PM processing does not compromise transient strength. FA-SMT exhibited markedly higher burst temperatures and reduced heating-rate sensitivity, consistent with its engineered precipitate strengthening. FA-SMT rupture exhibited axial "unzipping" rather than the lateral tearing characteristic of PM- and wrought C26M. Post-test EBSD and fractography indicate that this behavior is strongly correlated with strain-gated intergranular void nucleation associated with the dense precipitate architecture of FA-SMT, a response absent in the comparatively clean PM-C26M matrix and consistent with rupture morphologies reported for oxide-dispersion strengthened (ODS) FeCrAl of similar base-matrix chemistry to PM-C26M. These findings highlight the potential of powder metallurgy as a viable fabrication route for ATF claddings from an accident performance standpoint.

Bell, Sam [ORNL] (ORCID:0000000251905657)↗
DOE OSTI2025

Charm and bottom hadrons in hot hadronic matter

Heavy quarks, and the hadrons containing them, are excellent probes of the QCD medium formed in high-energy heavy-ion collisions, as they provide essential information on the transport properties of the medium and how quarks color-neutralize into hadrons. Large theoretical and phenomenological efforts have been dedicated thus far to assess the diffusion of charm and bottom quarks in the quark–gluon plasma and their subsequent hadronization into heavy-flavor (HF) hadrons. However, the fireball formed in heavy-ion collisions also features an extended hadronic phase, and therefore any quantitative analysis of experimental observables needs to account for the rescattering of charm and bottom hadrons. This is further reinforced by the presence of a QCD cross-over transition and the notion that the interaction strength is maximal in the vicinity of the pseudo-critical temperature. We review existing approaches for evaluating the interactions of open HF hadrons in a hadronic heat bath and the pertinent results for scattering amplitudes, spectral functions and transport coefficients. While most of the work to date has focused on D -mesons, we also discuss excited states as well as HF baryons and the bottom sector. Both the HF hadro-chemistry and bottom observables will play a key role in future experimental measurements. We also conduct a survey of transport calculations in heavy-ion collisions that have included effects of hadronic HF diffusion and assess its impact on various observables.

effective field theories↗
DOE OSTI2025

Effect of Fe on Co-Based SiO2Al2O3 Mixed Support Catalyst for Fischer–Tropsch Synthesis in 3D-Printed SS Microchannel Microreactor

This research explores the effect of a composite support of SiO2 and Al2O3 with Fe and Co incorporated as catalysts for Fischer–Tropsch synthesis (FTS) using a 3D-printed stainless steel (SS) microchannel microreactor. Two mesoporous catalysts, FeCo/SiO2Al2O3 and Co/SiO2Al2O3, were synthesized via a one-pot (OP) method and extensively characterized using N2 physisorption, XRD, SEM, TEM, H2-TPR, TGA-DSC, FTIR, and XPS. H2-TPR results revealed that the synthesis method significantly affected the reducibility of metal oxides, thereby influencing the formation of active FTS sites. SEM-EDS and TEM further revealed a well-defined hexagonal matrix with a porous surface morphology and uniform metal ion distribution. FTS reactions, carried out in the 200–350 °C temperature range at 20 bar with a H2/CO molar ratio of 2:1, exhibited the highest activity for FeCo/SiO2Al2O3, with up to 80% CO conversion. Long-term stability was evaluated by monitoring the catalyst performance for 30 h on stream at 320 °C under identical reaction conditions. The catalyst was initially active for the methanation reaction for up to 15 h, after which the selectivity for CH4 declined. Correspondingly, the C4+ selectivity increased after 15 h of time-on-stream, indicating a shift in the product distribution toward longer-chain hydrocarbons. This trend suggests that the catalyst undergoes gradual activation or restructuring under reaction conditions, which enhances chain growth over time. The increase in C4+ products may be attributed to the stabilization of the active sites and suppression of methane or light hydrocarbon formation.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Physics basis for the reference flat-top plasma scenario in the ST–E1 fusion power plant

As part of the U.S. Department of Energy’s Milestone-Based Fusion Energy Development Program, Tokamak Energy has completed the pre-concept design of the ST–E1 fusion power plant. ST–E1 is envisaged to operate in two phases: a pilot plant phase, targeting sustained net power production of 300 - 500 MWe for a duration >1 hr, followed by a commercial power plant phase targeting steady-state operations and a normalised overnight capital cost of ⩽12 000 $\$$/kWe. The design process adopted was highly iterative, integrating all major plant systems and progressing in a phased fidelity approach. At the pre-conceptual stage, the emphasis has been on exploring the design space, identifying the main system-level trade-offs, and making the key decisions that define the overall plant concept, rather than optimising a single operating point. This paper, part of a focused collection detailing the ST–E1 pre-concept design, addresses the development of a series of reference flat-top plasma operating points for the pilot plant phase. A modelling workflow was established to develop and assess candidate plasma design points and explore key dependencies. The workflow includes integrated core plasma modelling, magnetohydrodynamic (MHD) stability assessment, equilibrium generation, scrape-off-layer and exhaust modelling, heating & current drive design and optimisation, and turbulent transport modelling. Using this framework, the impact of several key parameters on the flat-top operating space was investigated, including the density limit, core radiation fraction and divertor power loading, level of external heating and curent drive power and assumed pedestal characteristics. The MHD stability, controllability and micro-stability characteristics of these plasmas were also analysed. These investigations informed the definition of a set of fully non-inductive, flat-top reference operating points that satisfy the high-level ST–E1 mission, including a low and high density case, a case that is stable to resistive wall modes and a case with reduced divertor power loading.

ST–E1↗
DOE OSTI2026

MARVEL Reactor Digital Engineering Developments

The MARVEL reactor project has served to introduce a new generation of engineers to the processes required to transform a reactor design from simply an idea on paper into what will be an approved, constructed, and operational nuclear power system. Much as there have been advances in materials, analysis, and evaluation methodologies over the 50 years since the last reactor was built at INL, so too has the technology for managing the engineering process itself advanced. Digital Engineering tools and methods provide improved coordination between previously siloed engineering disciplines, reduced burdens of non-value-added data transcription processes and bring forward insights and improvements that might otherwise fall later in the design stage, where changes are much more costly. While the tools and techniques to support the full digital engineering vision are not yet complete, the MARVEL design processes provide valuable demonstrations and validations of key aspects and illuminate further areas for implementation by subsequent projects.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials

Using knowledge from statistical thermodynamics and crystallography, we develop an image–image translation model, called SorbIIT, that uses three-dimensional grids of adsorbate–adsorbent interaction energies as input to predict the spatially resolved loading surface of nanoporous materials over a broad range of temperatures and pressures. SorbIIT consists of a closed-form differential model for loading-surface prediction and a U-Net to generate spatial differential distributions from the energy grids. SorbIIT is trained using the energy grids and adsorbate distributions (obtained from high-throughput simulations) of 50 synthesized and 70 hypothetical zeolites and applied for predicting the adsorption of carbon dioxide, hydrogen sulfide, n-butane, 2-methylpropane, krypton, and xenon in other zeolites from 256 to 400 K. In conclusion, employing a quadratic isotherm model for the local differentiation, SorbIIT yields mean R 2 values of 0.998 for total adsorption and 0.6904 for local adsorption with a resolution of 0.2 Å, and a value of 0.721 for the structural similarity of the local loading distribution.

Sun, Yangzesheng [Univ. of Minnesota, Minneapolis,↗
DOE OSTI2026

Adsorption of hydroxamic acid ligands for improved extraction of rare earth elements from monazite ores

Efficient separation of rare earth element (REE) ores via froth flotation requires the development of novel ligands with enhanced adsorption capacity and selectivity. To realize these advances, understanding the mechanisms underlying interactions between the ligand and mineral surfaces is essential. This study systematically evaluates the adsorption behavior of alkyl- and aromatic alkyl-substituted hydroxamic acid ligands on monazite surfaces using complementary spectroscopic techniques, including UV–visible (UV–vis) spectroscopy, Raman spectroscopy, infrared spectroscopy, and vibrational sum frequency generation (SFG) spectroscopy, together with the ab initio molecular dynamics (AIMD) simulations. Among the studied ligands, octanohydroxamic acid (OHA) and 4-ethoxy-N,2-dihydroxybenzamide (EDHBA) exhibit high adsorption capacity under basic pH (8–10) by forming multilayers on the surface. OHA has a higher equilibrium adsorption capacity compared to EDHBA, but it forms a less stable multilayer susceptible to disruption in the presence of interfering ions. AIMD results show that OHA adopts a single stable chelating geometry, while EDHBA exhibits multiple binding modes involving distinct interactions with La surface atoms and phosphate-bound oxygens, resulting in more complex adsorption kinetics. The variations in surface binding and intermolecular interactions observed between alkyl and aromatic molecules influence the differences in adsorption kinetics, equilibrium adsorption capacities on the mineral surface, and their flotation performance. This work provides valuable insight into the adsorption mechanism of ligands at mineral interfaces, which is crucial for guiding the design of new ligands with enhanced separation performance.

Zhou, Muchu [ORNL] (ORCID:0000000182650215)↗