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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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At least 37 records · Page 2

Tailoring a 3D Covalent Organic Framework Toward Facile Functionalization

Three-dimensional covalent organic frameworks (3D COFs) are notably crystalline and stable, but their architectures and monomer structures make them difficult to functionalize. Here, a new strategy is presented to render COF-300 and other imine-linked frameworks amenable to facile functionalization in the last step of synthesis. By reducing the imine linkages to secondary amines and appending them with acetyl halide groups, the linkages are converted to electrophiles that can be readily reacted with nucleophilic guests. This route yields eight new COF-300 derivatives, bearing chloroacetyl, bromoacetyl, azide, cyano, amino, hydroxyl, methoxy, or thiomethyl groups appended to the inter-monomer linkages. The new materials are characterized through solid-state NMR, infrared spectroscopy, and powder X-ray diffraction, among other techniques, finding that the reported linkage transformations proceed to complete conversion while retaining the crystallinity of the materials. Microcrystal electron diffraction (microED) data are used to solve the evacuated structure of the amine-linked framework COF-300-AR for the first time, providing conclusive evidence of this framework's guest-induced phase change, along with the structure of the new framework COF-300-NH 2 . Finally, COF-300-NH 2 is shown to have significantly improved adsorption capacity for CO 2 and perfluoroalkyl substances (PFAS), highlighting the benefits of this synthetic strategy for the generation of customized adsorbents.

COF-300↗

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗

Correlation between microstructure and residual stress formation in friction stir welded armor steels characterized by neutron diffraction

Friction stir welding (FSW) is a solid-state joining process that minimizes the heat-affected zone (HAZ) compared with fusion-based arc welding, making it well suited for joining martensitic armor steels where hardness and ballistic resistance are critical. This study investigates residual stress formation in three defect-free FSW butt-joint configurations relevant to armored-vehicle fabrication: similar rolled homogeneous armor (RHA–RHA, Case 1), similar high-hardness armor (HHA–HHA, Case 2), and dissimilar HHA–RHA (Case 3) joints produced under temperature-controlled conditions (770 °C). Neutron diffraction was employed to quantify the magnitude and spatial distribution of residual stresses in the longitudinal, transverse, and normal directions and to correlate them with weld microstructure and hardness. Tensile residual stresses were concentrated in the softened HAZ, reaching approximately 300 MPa for Case 2 and 400 MPa for Case 1 (≈50–70 % of the base-metal yield strength; ∼581 MPa for RHA and ∼566 MPa for HHA), while compressive residual stresses dominated the stir zone. The spatial extent of tensile stresses scaled with the width of the softened HAZ, which was largest in the dissimilar HHA–RHA joint and smallest in the HHA–HHA joint. Full-width-at-half-maximum (FWHM) analysis revealed low microstrain in overtempered HAZ regions and high microstrain in the stir zone associated with severe plastic deformation and fresh martensite formation. This work demonstrates that residual stress evolution in FSW of martensitic armor steels is governed not primarily by peak temperature or thermal contraction, as inferred from fusion-welding analogies, but by the competition between transformation-induced volumetric expansion and tempering-induced stress relaxation. The relative dominance of these mechanisms is shown to depend on alloy hardenability and local thermal history, leading to more extensive HAZ softening and broader tensile stress regions in the lower-hardenability RHA steel. These findings establish a transferable mechanistic framework for optimizing solid-state joining strategies in high-strength steels and other transformation-hardening alloys beyond armor applications.

Friction stir welding↗

Scalable, low-cost ink-based processing of high-performance silver selenide thermoelectrics

The growing global energy demand and its accelerating contribution to climate change emphasize the urgent need for sustainable energy conversion/harvesting technologies. Thermoelectric (TE) devices offer a compelling route to directly convert waste heat into electricity and enable solid-state cooling without moving parts or harmful refrigerants. Achieving their full potential requires not only higher TE performance (zT) but also scalable, low-cost manufacturing processes. Here, we introduce a transformative ink-based processing approach for scalable manufacturing of high-performance silver selenide-based TE materials and devices. Using a simple, high-throughput ink-mixing and blade coating strategy, our Ag 2 Se-based materials under the optimized composition and processing conditions yield an ultrahigh room-temperature power factor of 2.8 mW m −1 K −2 , over 100% higher than baseline samples and a reproducible figure of merit zT of 1 at room temperature. A thermoelectric generator (TEG) achieves a very competitive power density of 112 mW cm −2 at a 90 °C temperature difference between the hot and cold sides of the device, which is among the highest reported for silver selenide-based TE devices to date. This facile, scalable ink-based processing establishes a practical pathway toward industrial-scale manufacturing and widespread adoption of thermoelectric devices, advancing sustainable energy technologies.

Bappy, Md. Omarsany [University of Notre Dame, IN ↗

Structure-guided utilization of lignocellulose for catalysis, energy, and biomaterials

As a complex composite of cellulose, hemicellulose, and lignin, plant lignocellulose has long served as a major resource for biomass conversion, materials engineering, and bio-based product development. High-resolution structural insights enabled by solid-state nuclear magnetic resonance (ssNMR) now allow the mapping of polymer interfaces, identification of functional group accessibility, and tracking of molecular organization during processing, all of which are critical factors for optimizing catalytic strategies. These insights could drive transformative progress in lignocellulose-based applications, including selective depolymerization, improved pretreatment design, and efficient upcycling of lignin into resins, plastics, and biomedical materials. In industry-relevant contexts, such as biofuel generation and renewable material manufacturing, understanding the hydration dynamics, cross-linking patterns, and structural heterogeneity is also essential. The ability to visualize these features in native biomass presents a unique opportunity to develop new strategies for sustainability and performance. As the structural toolbox continues to expand, it is becoming a central enabler for innovations in renewable energy, green chemistry, and advanced bioproducts.

bioproduct↗

Structural Propensities in Cs2MBiX6 (M=Na, Ag; X=Cl, Br) Bismuth Halide Double Perovskites

A previously unreported low-temperature phase transition in the bismuth halide double perovskite Cs2AgBiCl6 is reported, thereby establishing trends in the structural ground state across Cs2NaBiCl6, Cs2AgBiCl6, and Cs2AgBiBr6. Using the combined toolkit of variable-temperature synchrotron X-ray and neutron powder diffraction, Raman spectroscopy, and density-functional theory–based electronic structure modeling, we demonstrate a cubic Fm¯3m → tetragonal I4/m transition upon cooling with distinct onset temperatures. Neutron powder diffraction refinements permit the unambiguously assignment of the low-temperature phase of Cs2NaBiCl6 to I4/m, correcting prior reports of an I4/mmm ground state. Cs2AgBiCl6 is also found to transforms to a structure crystallizing in the I4/m space group at low temperatures. Temperaturedependent Raman data and density-functional theory-based modeling capture the softening and freezing of out-of-phase octahedral-tilt modes and quantify relative instabilities. Solid-state nuclear magnetic resonance spectroscopy at room temperature completes the characterization and helps underpin the subtle differences in covalency across the compounds. Trends in the phase transition temperature Ts and tilt magnitudes emerge from coupled effects of halide identity, M(I)–site bonding character, and a mismatch between interatomic distances. These results establish the structure– dynamics–bonding framework for tuning tilt-driven instabilities in halide double perovskites.

Tian, Haowen↗

Phase instability-coupled fracture behavior in garnet LLZO solid electrolytes: a machine learning-enabled atomistic study

Fracture in the garnet-type solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) poses a critical threat to both the performance and safety of solid-state batteries. To unravel the coupled chemomechanical processes that govern fracture in LLZO under external loading, we carry out large-scale molecular-dynamics simulations with a validated machine-learning force field. Our results demonstrate that triaxial stresses at crack flanks trigger a localized cubic-to-tetragonal phase transformation, which is accompanied by Li-ion rearrangement. The emergent tetragonal domains feature lattice contraction normal to the fracture plane, imposing coherent misfit strains that provide an additional driving force for further crack propagation. Crucially, introducing Li deficiencies stabilizes the cubic phase, postponing the phase transition and thereby delaying fracture initiation. These findings highlight the role of intrinsic phase instability in dictating LLZO's fracture resistance and its critical connection to local Li concentration. This chemomechanical coupling points toward targeted strategies to enhance the mechanical robustness of garnet electrolytes, including tuning Li content, ensuring dopant homogeneity, and refining processing protocols.

Materials science↗

Leveraging High-resolution Molecular Composition of Soil Organic Matter to Enhance Carbon Cycling Modeling

Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.

54 ENVIRONMENTAL SCIENCES↗

Real-Space Local Dynamics in 1,2,3-Triazole Using Inelastic Neutron Scattering

Enhancing proton transport in polymer electrolytes is crucial for advancing next-generation solid-state batteries, yet our understanding of proton conductivity in nonaqueous environments remains limited due to a lack of atomic-scale insights. Here, in this study, we investigated the atomic-scale dynamics of 1,2,3-triazole, a small molecule capable of dynamic hydrogen bonding, as a model system for proton hopping in nonaqueous environments. Using the real-space correlation function determined by the double Fourier transformation of inelastic neutron scattering spectra, we identified that the self-motion of protons and intermolecular dynamics occur on comparable time scales. Furthermore, we observed that the activation energy associated with the intermolecular dynamics matches the energy barrier for molecular rotations determined through Density Functional Theory calculations. These findings underscore the importance of controlling molecular dynamics at the atomic scale to control proton transport. Additionally, we demonstrated that intermolecular dynamics in systems involving protons can be studied using inelastic neutron scattering even without deuteration, thereby providing a broader avenue for studying atomic-scale dynamics in soft matter systems.

Shinohara, Yuya [Oak Ridge National Laboratory (OR↗

Unraveling Anion-Specific Inhibition and Structural Modulation of Gibbsite Crystallization: Implications for Aluminum Mobility in Natural and Engineered Systems

Gibbsite (α-Al(OH) 3 , sometimes designated as γ-Al(OH) 3 ) plays a crucial role in the chemistry of aluminum in the environment and industry, yet its crystallization behavior under multianionic conditions is not well understood. Here, in this study, we investigate how six common anions─fluoride (F – ), chloride (Cl – ), bromide (Br – ), nitrate (NO 3 – ), sulfate (SO 4 2– ), and phosphate (PO 4 3– )─influence the mineralization, structure, and morphology of gibbsite at room temperature. The results show that PO 4 3– , SO 4 2– , and F – strongly inhibit gibbsite formation, stabilizing amorphous or alternative crystalline phases such as nordstrandite and cryolite. On the contrary, Cl – , Br – , and NO 3 – allow partial to complete crystallization of gibbsite without significant morphological changes. Solid-state 27 Al magic angle spinning nuclear magnetic resonance provides crucial insight into aluminum coordination environments in both crystalline and amorphous phases, distinguishing between octahedral, pentahedral, and tetrahedral Al species. The density functional theory calculations reveal a direct correlation between the Al–X bond strength and the inhibition of crystallization, following the order: PO 4 3– > SO 4 2– > F – > NO 3 – > Cl – > Br – . These findings offer molecular-scale insights into anion-specific effects on aluminum hydroxide nucleation and transformation, improving the understanding of gibbsite formation and aluminum cycling in soils, phosphate retention, contaminant immobilization, and waste treatment strategies in nuclear and industrial settings. These insights can also guide the controlled synthesis of aluminum hydroxide materials with tailored crystallinity and morphology via liquid-assisted methods.

Anions effect↗

Coupled Chemical and Mechanical Control of Phase Stability in Lanthanide-Substituted BiVO 4

Doping is widely used to enhance the photoelectrochemical performance of BiVO 4 , yet solubility limits and polymorphic stability constrain compositional tuning. Here, in this study, the role of trivalent cation substitution (Ln = La, Nd, Dy, Ho, Y) on pressure-induced phase transformations in Bi 1–x Ln x VO 4 (x ≤ 0.5) is described. Powder X-ray and neutron diffraction reveal that increasing Ln content stabilizes the tetragonal zircon-type polymorph under ambient conditions, while applied pressures of up to ∼5 GPa promote conversion to the monoclinic fergusonite-type polymorph. In-situ neutron diffraction on Bi 0.8 La 0.2 VO 4 shows a reversible monoclinic to tetragonal transition near 2–3 GPa with a bulk modulus of 147 GPa. The extent of conversion depends strongly on dopant identity, concentration, and synthetic route, with mixed-phase solid-state samples converting more efficiently than phase-pure coprecipitated materials. These results demonstrate pressure as a viable pathway to access metastable, doped BiVO 4 compositions beyond conventional solubility limits.

Sypkes, Kathryn I. [University of Sydney, NSW (Aus↗

Gas-mediated defect engineering in earth-abundant Mn-rich layered oxides for non-aqueous sodium-based batteries

Gases are often by-products of battery materials during cell formation and degradation, affecting the cycle life and safety of rechargeable batteries. However, understanding gas-mediated (electro)-chemical reactions and nanoscale structural transformations during the synthesis of battery electrode materials remains challenging because of the lack of suitable characterization routes and the complexity of the interplay between thermodynamics and kinetics. Here, in this study, we use operando synchrotron X-ray diffraction, in situ transmission X-ray microscopy and multiscale modelling to elucidate the reaction pathways and microstructural defect development of earth-abundant Mn-rich layered oxides as positive electrode materials for sodium-based batteries. In particular, we demonstrate the dominant role of CO 2 over O 2 and H 2 O (g) in modulating the competition between entropy and enthalpy during solid-state synthesis. Using Ni 0.25 Mn 0.75 CO 3 as a model precursor, we reveal that CO 2 generation favours the formation of entropy-driven metastable intermediates, suppresses closed pore/nanovoids formation and decreases chemical heterogeneity and residual lattice strain of Mn-rich layered oxides during the synthesis. This result motivates a fast-sintering strategy to promote CO 2 release, which ultimately leads to improved chemo-mechanical and electrochemical stability of the Mn-rich positive electrodes when tested in non-aqueous Na metal coin cells.

36 MATERIALS SCIENCE↗

Formation of Non-Doped Cubic Lithium Lanthanum Zirconium Oxide Nanofibers: Insights from In Situ Synchrotron X-Ray Scattering

This study investigates the formation mechanism of non-doped cubic lithium lanthanum zirconium oxide (c-LLZO) nanofibers using in situ synchrotron X-ray scattering techniques. Electrospun polymer precursor nanofibers were annealed at temperatures up to 800 °C, enabling real-time tracking of phase transitions via simultaneous small-angle X-ray scattering (SAXS), wide-angle X-ray scattering (WAXS), and evolved CO 2 gas analysis. The results reveal a three-step transformation pathway: polymer decomposition, formation of La 2 Zr 2 O 7 (LZO), and direct conversion of LZO to c-LLZO without intermediate tetragonal phases detected within the sensitivity of our in situ WAXS measurement. Cryo-electron energy loss spectroscopy (EELS) further elucidates the role of lithium diffusion, showing Li enrichment at fiber surfaces and Li deficiency in the interior, which stabilizes the cubic phase. This Li segregation effect in nanostructured LLZO materials extends beyond the previously reported size effect. This work advances the understanding of c-LLZO formation mechanisms and provides practical insights for optimizing synthesis routes to achieve phase-pure c-LLZO for solid-state battery applications.

LLZO phase stability↗

Polymer connectivity governs electrophotocatalytic activity in the solid state

The reductive functionalization of inert substrates such as chloroarenes is a critical yet challenging transformation relevant to both environmental remediation and organic synthesis. Combining electricity and light is an emerging strategy to access the deeply reducing potentials required for single electron transfer to chloroarenes, yet this approach is limited by poor stability and mechanistic ambiguity. Here, in this work, we demonstrate heterogeneous electrophotocatalysis using redox-active rylene diimide polymers for the reduction of chloroarenes. We find that the electrophotocatalytic activity varies dramatically as a function of the rylene diimide and the redox-inactive polymer backbone. In particular, a flexible, non-conjugated perylenediimide polymer outperforms all other tested electrophotocatalysts. Transient absorption spectroscopy reveals that precomplexation between the doubly reduced perylenediimide and the haloarene substrate is key to productive catalysis. Overall, this work highlights heterogeneous electrophotocatalysis using insoluble redox-active organic materials and provides critical structure–property insights into solid-state electrophotocatalytic activity, informing the development of next-generation materials for sustainable synthesis.

electrocatalysis↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Structural, Electronic, and Photophysical Insights into a Few Atom Copper-Sulfur Cluster in the Solid and Solution States

Coinage-metal chalcogenide clusters are widely studied for their attractive photoluminescence properties. Copper chalcogenides are especially promising, but are often confined to solid-state investigations due to their limited solution stability and the difficulty of synthesizing stable, well-defined clusters. Here, we investigate copper–sulfur clusters incorporating a small number of Cu atoms to elucidate fundamental atomic interactions, ground- and excited-state characteristics, and photophysical behavior in both solid and solution. We have synthesized the Cu6(4,6-dimethyl-2-mercaptopyrimidine)6 cluster in both neutral and charged states, Cu6 and Cu6-2H2+, respectively, by selective ligand protonation. The molecular structures are determined using single-crystal X-ray diffraction, while Cu K-edge X-ray absorption spectroscopy is used to probe Cu electronic structure differences arising from the ligand modification. Steady-state and pump-probe optical spectroscopy is used to investigate photophysical properties, interpreted using density functional theory methods. Both clusters exhibit good stability in the solid state and in solution and show characteristic near-infrared emission with microsecond lifetimes. Overall, the Cu6S6 clusters display favorable charge–transfer characteristics and show potential for further use in driving photochemical transformations.

Copper-sulfur clusters↗

Effects of Synthesis Conditions on the Structure and Conductivity of Hydrogen-Substituted Graphdiyne

This study investigates how synthesis conditions influence the structure and conductivity of hydrogen-substituted graphdiyne (HsGDY). By varying the reaction temperature and solvent, we find that small changes in conditions markedly affect triple-bond retention and electronic continuity. Solid-state 13 C NMR and Raman spectroscopy reveal that elevated temperatures drive alkyne loss and partial graphitization, with N,N-dimethylformamide (DMF) promoting faster degradation than pyridine. The resulting decline in alkyne content directly correlates with reduced conductivity, indicating that preserving conjugation is essential for charge transport. These findings clarify how the synthetic environment governs the structural and electronic evolution of graphdiyne frameworks, providing insight into the controlled preparation of conjugated carbon networks.

alkyne retention↗

Enhanced Catalytic Dechlorination of Polyvinyl Chloride (PVC) and H2 Production Enabled by Synergistic Gaδ+/Ga0 Active Sites in Liquid Metal Particles

Polyvinyl chloride (PVC) is ubiquitous yet challenging to recycle due to its tendency to thermally decompose above 250 °C, releasing toxic, corrosive chlorinated compounds, and its inability to melt. Here, we report a catalytic strategy for PVC upcycling at 160 °C using gallium liquid metal particles (Ga-LMP) featuring a dynamic Ga-GaOOH core–shell architecture. These catalysts enable concurrent dechlorination and hydrogen evolution, yielding up to 7% H2 (based on initial hydrogen atoms in PVC) along with a highly dechlorinated (>95%) carbonaceous solid and aqueous HCl. Mechanistic investigations combining X-ray photoelectron spectroscopy, infrared spectroscopy, solid-state NMR, inelastic neutron scattering, and ab initio molecular dynamics reveal a synergistic interplay between Gaδ+ sites in the GaOOH shell and metallic Ga0 in the core. Cationic Ga initiates C–Cl bond activation and HCl formation, while progressive reduction of the shell exposes Ga0 sites that promote C–H activation and H2 evolution. Control experiments with a Ga salt and bulk Ga liquid metal confirmed that neither oxidation state alone can achieve both transformations efficiently. This work establishes a dynamic dual-site paradigm for liquid metal catalysis, in which the in situ evolution and coexistence of oxidized and metallic species enable sequential and cooperative bond activation pathways. These findings provide a general design principle for novel liquid metal catalysts that target challenging polymer transformations under mild conditions.

Zingg, Benjamin [ORNL] (ORCID:0009000914530153)↗