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At least 127 records · Page 7

Unsupervised atomic data mining via multi-kernel graph autoencoders for machine learning force fields

Constructing a chemically diverse dataset while avoiding sampling bias is critical to training efficient and generalizable force fields. However, in computational chemistry and materials science, many common dataset generation techniques are prone to oversampling regions of the potential energy surface. Furthermore, these regions can be difficult to identify and isolate from each other or may not align well with human intuition, making it challenging to systematically remove bias in the dataset. While traditional clustering and pruning (down-sampling) approaches can be useful for this, they can often lead to information loss or a failure to properly identify distinct regions of the potential energy surface due to difficulties associated with the high dimensionality of atomic descriptors. In this work, we introduce the Multi-kernel Edge Attention-based Graph Autoencoder (MEAGraph) model, an unsupervised approach for analyzing atomic datasets. MEAGraph combines multiple linear kernel transformations with attention-based message passing to capture geometric sensitivity and enable effective dataset pruning without relying on labels or extensive training. Demonstrated applications on niobium, tantalum, and iron datasets show that MEAGraph efficiently groups similar atomic environments, allowing for the use of basic pruning techniques for removing sampling bias. This approach provides an effective method for representation learning and clustering that can be used for data analysis, outlier detection, and dataset optimization.

Materials science↗

Etching-Chemistry-Driven Ruthenium Doping on Ti 3 C 2 T x MXene for Optimizing Electrochemical Performance

We demonstrate that the etching chemistry used during MXene synthesis from Ti 3 AlC 2 MAX phase significantly influences surface functionalization and structural vacancies, which in turn affect ruthenium (Ru) ion interactions. Using hydrofluoric acid (HF) and ammonium bifluoride (NH 4 HF 2 ) as etchants, we obtained MXene surfaces with distinct functional groups and Ti vacancies that impact Ru ion interactions and electrochemical performance. Both MXene variants (labeled MX(H) and MX(N), respectively) exhibited negative zeta potentials in their pristine state, but upon the addition of Ru the zeta potential for MX(H) reached 12.9 mV while that for MX(N) remained negative at −6.4 mV. This adsorption resulted in a 14.4-fold increase in the specific capacitance of MX(H)/Ru compared to pristine MX(H), whereas MX(N)/Ru exhibited only a 4.4-fold increase over its pristine counterpart. X-ray diffraction analysis identified the formation of ammonium titanium oxide fluoride, (NH 4 ) 3 TiOF 5 , on MX(N), which likely contributed to its reduced Ru adsorption. X-ray photoelectron spectroscopy suggested the presence of Ti vacancies in both MXene variants; however, their behavior toward Ru accommodation differed markedly, with MX(H) showing the most obvious shift in the Ti 2p peak in the XPS survey spectrum, while MX(N) showed the most obvious shift in the C 1s peak. Electron paramagnetic resonance spectroscopy further demonstrated a distinct alteration in the spectral signatures of MX(H) upon Ru addition, in contrast to the negligible changes in MX(N), indicating effective passivation of the Ti defect sites in MX(H) via vacancy-assisted Ru doping. Cyclic voltammetry showed that Ru-incorporated MX(H) nanocomposites exhibit more efficient redox-active sites, as reflected in their higher capacitance values. These findings highlight the pivotal role of MXene surface chemistry in controlling cation adsorption, providing valuable insights for the rational design of high-performance electrodes.

2D surface engineering↗

Advances and perspectives of hard carbon anode modulated by defect/hetero elemental engineering for sodium ion batteries

Sodium-ion batteries (SIBs) serve as a promising complement to lithium-ion batteries for large-scale energy storage, leveraging the abundance of sodium resources and notable safety advantages. The key advancement in SIB industrialization hinges on identifying a cost-effective and high-performance anode material, similar to the graphite anode in lithium-ion batteries. Hard carbon emerges as prime anode materials for SIBs, boasting high specific capacity, low sodium storage potential, and wide availability. However, practical applications of hard carbon encounters challenges such as low initial Coulombic efficiency (ICE), inadequate long-term cycling stability, and poor rate performance. Recent research has focused on the optimization of hard carbon electrodes through functional design. In this comprehensive review, we have meticulously examined the progress in enhancing sodium storage performance through microstructural modulation within hard carbon, encompassing four pivotal aspects: heteroatom doping, incorporation of oxygen functional groups, surface coating, and intrinsic defect engineering. Progress in implementing these strategies is scrutinized, while the merits and challenges of each defect engineering approach are discussed. In conclusion, this review also looks into forthcoming opportunities and challenges in the practical application process of hard carbon electrodes in SIBs.

25 ENERGY STORAGE↗

DEVELOPMENT OF INEXPENSIVE HIGH TEMPERATURE NITI-BASED SHAPE MEMORY ALLOYS FOR POWDER BED ADDITIVE MANUFACTURING

NiTi and NiTi-based Shape Memory Alloys (SMA) exhibit a reversible solid-state phase transformation from martensite to austenite driven by thermal energy. High temperature (Mf>100°C) SMAs are martensite at room temperature and can be fabricated into solid-state actuators that return to a pre-programmed shape against a designed load after heating to transformation threshold. Reactive as-fabricated additively manufactured parts (4-D printing) is the current state of the art in manufacturing of SMAs but requires compositions compliant to rapid solidification. Existing actuator designs are developed from commercially available, highly investigated material compositions. However, existing high temperature high performance (high actuation strain, low thermal hysteresis) shape memory alloys contain significant (>10% at.) portions of high-cost Platinum Group Metals (PGMs). It is of significant scientific interest to investigate material compositions that are peer performing or superior to PGMs whose constituent elements represent a significant cost savings. Shape memory alloy properties vary significantly with small (0.1% at.) compositional changes making robust investigative sample sets very large. Computational material design can be deployed to shrink the compositional space of possible alloy combinations and reduce the experimental load in material discovery. Investigating shape memory effect (SME) and validating process additive process parameters for a single novel composition is cost intensive in both time and consumed materials. Additionally, sub-optimal processing, oxygen, or solidification rate sensitivity could render additively manufacturing specimens without micro, macro cracks, or significant chemical variance impossible. Unfortunately, such failure susceptibility cannot be simulated. Therefore, a research pathway to validate novel shape memory alloy compositions for powder bed fusion additive manufacturing without the need for powdered feedstock is also proposed. This research investigates novel high temperature shape memory alloys for actuators without platinum group alloying elements to discover one that could be commercially viable as an additive manufacturing feedstock.

Sundermann, Tayler↗

The ENDF/B Nuclear Data Library and Its Impact on Reactor Simulations

The ENDF/B library, which is developed, maintained, and distributed by the Cross Section Evaluation Working Group, is the main source of nuclear data for analyses and computational simulations in nuclear applications, like different nuclear reactors concepts, radiation shielding, medical applications, astrophysics, etc. The library is constantly being improved and updated, with each release bringing an optimal representation of nuclear interactions as they are understood in their time. The most recent release, ENDF/B-VIII.1, represents a significant improvement in terms of the performance and consistency of the measured differential data relative to previous versions, as it combines the most recent experimental differential data and advanced theoretical nuclear models. As one of the many highlights, ENDF/B-VIII.1 restores a high-burnup depletion performance, comparable to ENDF/B-VII.1, that had been degraded in ENDF/B-VIII.0, while further improving the performance in criticality benchmarks, such as those in the Mosteller’s suite. Additionally noteworthy is the improved performance of ENDF/B-VIII.1 in radiation shielding and thick-target leakage spectrum integral experiments, which are also important for fusion and reactor applications. In this work we present in a very summarized way the main updates implemented in the ENDF/B-VIII.1 release and its main impacts, and also begin to delineate the path forward as to what to expect in the future for the next ENDF/B release, which, based on the timeline of the past few releases, is estimated to happen around 5 years from now. We emphasize that the ENDF/B-VIII.1 release was the product of an enormous collaborative effort among many authors and that for a complete detailed picture, the reader is strongly encouraged to refer to the article accompanying the release, which is currently in the publication process, but available as preprint [G. P. A. Nobre et al. arXiv Preprint arXiv: 2511.03564 (2025)].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cooperative Automated Cohort Driving on Connected Infrastructure, Arterial Roadways, and Highways: Final Project Demonstration and System-of-Systems Model Correlation

This project seeks to synergize vehicle automated driving and connectivity data to improve mobility and energy efficiency of groups of mixed vehicles operating in close proximity (vehicle cohort) on various infrastructure. A custom cellular communication network links vehicles operating as a cohort with infrastructure to a centralized system-of-systems digital twin with an AI-based optimal behavior planner. The data contained in this set are from final testing and technology demonstrations to U.S. Department of Energy staff at the American Center for Mobility. The data contain single-lane, single-light scenarios; multi-lane, multi-light arterial scenarios; and limited-access highway scenarios. All test cases were derived from simulations and replicated on the test track. The project employed two and four light-duty vehicles with connectivity and drive automation for the testing. The baseline scenario without connectivity was run under the control of the system-of-systems centralized planner but operating each vehicle with an intelligent driver model controlling the velocity, lane utilization, and vehicle gap. This was to ensure the highest compatibility with the simulation in terms of dynamic behavior. The connected cohort case utilized AI optimization to perform coordinated and cooperative control for energy, as well as safe, comfortable behavior for the cohort. The dataset is appropriately named with unconnected and connected designations, with comparisons sharing the same run index number. The included PowerPoint and PDF files describe the test setup and provide an overview of results from the project. ![image](de-EE0009209_March_2023_Data_Arterial_Scenario_Results.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗

Engineering acid-base active sites on an N-doped biochar catalyst for microwave-assisted biodiesel production from waste cooking oil

Acid-base bifunctional catalysts play a crucial role in converting high-free fatty acid (FFA) feedstocks into biodiesel by enabling the simultaneous esterification and transesterification of triglycerides in a single step, thereby minimizing saponification and streamlining the process. In this study, we report the design and development of a novel N-doped acid-base bifunctional biochar catalyst synthesized from renewable biomass precursors- glucose and chitosan. The catalyst’s acidic sites were introduced via surface functionalization with o-sulfobenzoic acid cyclic anhydride, grafting -SO₃H groups onto the carbon framework, while basic sites were generated from amine functionalities (-NH) derived from chitosan, yielding a robust and truly bifunctional surface. The catalyst was characterized and used for the microwave-assisted transesterification of waste cooking oil, and process optimization using response surface methodology (RSM-CCD) yielding a maximum biodiesel yield of 98.8 ± 0.4% under optimal conditions (methanol-to-oil molar ratio 20:1, catalyst loading 5.7 wt%, temperature 99 °C, and reaction time 46.6 min). The catalyst demonstrated good stability, maintaining a yield of 92.2 ± 0.4% after eight reuse cycles. A Life Cycle Assessment (LCA) conducted for 1 kg of biodiesel production revealed a global warming potential of 0.85 kg CO 2 eq and human toxicity potential of 1.59 kg 1,4-DB eq, with the largest environmental contributions arising from catalyst preparation and reuse. In conclusion, this work highlights a green and circular approach to biodiesel production, combining renewable catalyst design, waste feedstock utilization, and quantitative sustainability assessment to guide future developments in sustainable catalysis and biofuel engineering.

Bifunctional catalyst↗

Novel Organosulfur-Based Electrolytes for Safe Operation of High Voltage Li-ion Batteries over a Wide Operating Temperature

This project addresses the failure of conventional electrolytes and enables high-voltage operation of lithium-ion batteries (LIBs) by developing a novel organosulfur-based electrolyte system. To achieve this goal, we first designed and synthesized new organosulfur solvents that functionalized with strong electron-withdrawing groups such as fluoroalkyl and cyano substituents. Through regio-specific molecular engineering, supported by theoretical calculations, we lowered the highest occupied molecular orbital (HOMO) energy levels of these molecules to increase their anodic stability for high-voltage operation. We then optimized the formulation of the organosulfur-based electrolyte with additives, co-solvents and salts tailored to the newly synthesized solvent molecules. In parallel, we utilized advanced spectroscopic techniques—including in situ FTIR, EIS, and DEMS—to thoroughly elucidate the mechanisms of interaction between the electrolyte and electrode materials. Finally, we evaluated 2 Ah pouch cells under both normal and extreme conditions. Pouch cells with the newly developed electrolyte system demonstrated >90% capacity retention after 500 cycles under 4.5 V operating voltage, >80% capacity retention after 1000 cycles in coin cell level. In addition, the cells exhibited high safety and reliable operation capability over a wide temperature range from −30 °C to +45 °C.

25 ENERGY STORAGE↗

Fluorinated Glyme Solvents to Extend Lithium-Sulfur Battery Life (Final Technical Report, Unlimited)

This project investigated a number of partially fluorinated glymes (PFGs) as electrolyte cosolvents to improve the performance of lithium-sulfur (Li-S) batteries. A major issue in Li-S cells is the electrochemical reaction of sulfur in the cathode to form lithium polysulfides (LPS) that dissolve in the electrolyte. Those LPS are electrochemically and chemically reactive at the lithium anode, resulting in lithium sulfide deposition on the anode and also electrochemical reaction at both the anode and cathode, leading to a “polysulfide shuttle” and reduced coulombic efficiency (CE) and self-discharge of the cell. PFGs reduce the solubility of LPS while maintaining good solubility of lithium salts such as LiTFSI. By adjusting the amount of PFG as cosolvent in the electrolyte, we showed that the solubility of LPS in the electrolyte can be tuned. (It is not desirable to completely eliminate LPS in the electrolyte, as they facilitate electrochemical reaction of the electrically insulating S 8 and Li 2 S within the cathode by shuttling charge between them and the conductive carbon.) Another issue in Li-S cells is degradation of the Li anode over many cycles of stripping (discharge) and plating (charge). We showed that PFGs have a beneficial effect on the physical morphology of the Li anode, SEI formation, and the CE of a Li-Li cell. Among the many PFGs tested, we found the best performance from PFGs designated PFG2 and PFG5, and these two PFGs were thoroughly studied. A systematic coin-cell study of electrolyte solvents of 90:10, 80:20, or 70:30 DME:PFG (DME = 1,2-dimethoxyethane) revealed some systematic trends: a higher percentage of PFG solvent led to substantially longer cycle life, but at the same time reduced specific capacity (mAh/g(S)) and cell capacity at higher rates. These studies used LiFSI as the electrolyte salt, as it was found to extend cycle life compared to LiTFSI. Finally, the addition of a small amount of 1,3-dioxolane (DOL) to the electrolyte was found to be beneficial. The overall optimal electrolyte solution was found to be 0.6 M LiFSI + 0.5 M LiNO 3 in 75:5:20 DME/DOL/PFG (either PFG2 or PFG5).

25 ENERGY STORAGE↗

Optimizing iodine adsorption in functionalized metal-organic frameworks via an unprecedented positional isomerism strategy

Porous metal–organic frameworks (MOFs) have emerged as highly promising adsorbents for capturing radioiodine, a predominant fission product released during nuclear fuel reprocessing. However, systematic investigations into the correlation between MOF structure and iodine uptake capacity remain scarce. Here, we present a novel approach to enhance the iodine adsorption capacity of MOFs by optimizing linker functionalization. Using ligand-functionalized thorium-based MOFs as a structural platform, we demonstrate that ortho-amino-substitution near the node of the dicarboxylate linker significantly increases iodine adsorption capacity compared to meta-amino-substitution, where the amino groups are directed away from the node. Specifically, ortho-substituted Th-UiO-68-3,3”-(NH 2 ) 2 exhibits higher iodine uptake capacities than the meta-substituted Th-UiO-68-2,2”-(NH 2 ) 2 via both vapor diffusion-based (2.042 vs. 1.087 g/g) and solution-based (0.841 vs. 0.784 g/g) processes. Notably, the I 2 vapor adsorption capacity (2.042 g/g) of Th-UiO-68-3,3”-(NH 2 ) 2 represents the second highest among all reported Th-MOFs. Pair distribution function (PDF) studies reveal that the superior iodine uptake performance of ortho-functionalized MOFs can be attributed to the reduced steric hindrance of the amino groups compared with the meta-substituted variants. Finally, this research highlights how positional isomerism and its subtle alterations can significantly influence host–guest interactions, extending beyond simple structural considerations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Performance AEM LTE with Advanced Membranes, Ionomers and PGM-Free Electrodes

Alkaline low temperature electrolysis (LTE) systems enjoy several potential advantages over acid-based LTE systems including facile oxygen evolution reaction (OER) kinetics and electrodes that can use little to no platinum group metals (PGM). The polymer membranes and membrane electrode assembly (MEA) structures going into alkaline electrochemical systems have seen significant advances in recent years. The objective of this project is to combine state-of-the-art alkaline polymer electrolyzer components into one optimized membrane electrode assembly (MEA) system to achieve DOE low temperature electrolysis (LTE) goals. The benefit of individual component advances cannot be fully appreciated until all aspects and components of the MEA are working at an equally high level of performance. New electrode fabrication methods were developed where solvent cast catalyst/ionomer solutions were used in place of insoluble ionomers to significantly improve adhesion. The membranes were improved in terms of durability and mechanical properties. The OER and HER catalysts were improved and made more durable.

08 HYDROGEN↗

Roadmap to Advance Heliostat Technologies for High Temperature Solar-Thermal Systems

Since its establishment, the Heliostat Consortium (HelioCon) has made substantial progress toward closing many of the gaps in concentrating solar power (CSP) research. Numerous techno-economic studies have been performed, investigating topics ranging from the trade-off between size and temperature for industrial process heat applications to optimization of the heliostat design itself for various applications. Significant improvements have been made in optical metrology techniques, with first steps toward in situ measurement of heliostat fields. Several standards have been, and continue to be, developed with the coordination of an international group of CSP industry participants. Training programs have been developed, with universities including CSP in their engineering curricula, and many public webinars have been held to provide broad access to the latest CSP research. Improved CSP components such as mirror facets and wireless communication systems have been developed, and the solar tower at Sandia National Laboratories has been upgraded with a testbed for closed-loop controls research and development. Field deployment challenges involving heliostat foundations and sensitive wildlife habitats have been explored, with progress made toward methods for streamlining project development and permitting. Additional knowledge has been added to the body of work on wind behavior of heliostats and arrays of heliostats, with progress made toward a holistic understanding of wind design methods. Finally, techniques have been developed and demonstrated for assessing soiling conditions at a proposed project site, with predictive models for the soiling rate showing good results. Taking these results together, HelioCon has contributed greatly to the global CSP research and development effort over the past several years.

14 SOLAR ENERGY↗

Illuminating the Role of Alcohol Substrate in Nickel Photoredox Catalysis via Ground State and Transient Absorption Spectroscopy

Direct excitation of nickel photocatalysts has gained popularity over the last several years following the successful activation of nickel by Ir and Ru photosensitizers. The ability to pair these photosensitizers with Ni catalysts facilitates the formation of crucial chemical bonds under relatively mild conditions. However, there are still gaps in our understanding of what influences the performance of these Ni photocatalysts. Previous work from our group identified a nickel photocatalyst supported by a tridentate pyridinophane ligand that undergoes wavelength-dependent cross-coupling reactivity. Herein, we report detailed studies of the wavelength dependence of the C–O cross-coupling reactivity, illustrating that the catalytic activity has an optimal wavelength, and excitation on both the blue and red sides of this optimal wavelength leads to a reduction in product yield. We also reveal a crucial catalyst-alcohol preirradiation interaction that drastically alters the catalyst’s optical properties. Furthermore, we investigate both wavelength dependency and alcohol dependency via optical transient absorption spectroscopy and reveal a substrate binding process responsible for the observed wavelength-dependent cross-coupling catalysis.

alcohol↗

Solid State Quantum Refrigeration Superconducting, Absorption and Measurement Based (Final Technical Report)

During this DOE grant, DE-SC0017890, in place for the past six years, all proposed research was carried out and published in peer-reviewed papers, as well as other projects that emerged during the research. In that effort the research team accomplished all proposed research, as well as many closely related research projects discovered and conceived of during the grant. These works included “Efficient Quantum Measurement Engines”, a work published in Physical Review Letters, giving a theory of quantum measurement-based engines, which uses quantum measurement as a resource. These engines are designed to efficiently convert energy from the stochastic quantum measurement process into useful work. Further publications include “Experimental Realization of a Quantum Dot Energy Harvester”, a joint theory and experimental work in collaboration with the group of Charles Smith in Cambridge, UK, as well as long time theoretical collaborators, Rafael Sánchez and Björn Sothmann. This work, featured as an Editor’s Suggestion in Physical Review Letters, realized an earlier theoretical proposal of ours, whereby two resonant tunneling quantum dots are connected to a central electronic cavity that is heated by a hot energy source. We also published “Superconducting Quantum Refrigerator: Breaking and Rejoining Cooper Pairs with Magnetic Field Cycles” a work done in collaboration with experimentalist Francesco Giazotto from ENS Pisa, Italy, which also resulted in a patent. This paper, published in Phys. Rev. Applied, advanced the concept of a cyclic fridge based on the normal/superconducting phase transition together with layered materials separated by tunnel junctions. We also completed the proposed research on a heat transistor, publishing “Thermal transistor and thermometer based on Coulomb-coupled conductors”, carried out as a collaboration between my group and theorists Splettstoesser (Lund U., Sweden), Sothmann (U. Duisburg-Essen, Germany), and Sánchez (U. Autónoma de Madrid, Spain). We carried out an analysis of a quantum coupled to a quantum point contact as a sensitive thermometer and heat transistor. We found the optimal statistical estimator for the temperature and compared it with experiments on the same type of devices. We also investigated autonomous quantum absorption refrigerators using quantum dots to cool by using a very hot thermal reservoir to drive heat between two other reservoirs. In the article “Quantifying the quantum heat contribution from a driven superconducting circuit”, we demonstrated that for a driven superconducting circuit, we showed heat flow provided by a hot source to the qubit can be switched on and off by varying external parameters, the frequency and the intensity of the driving. In the work “Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine”, we reconsidered the autonomous thermoelectric heat engine in terms of underlying cycles. Rather than periodic behavior, the cycles were stochastic in nature. Nevertheless, by undertaking a graph theoretical analysis of the elementary transport processed, great quantitative and qualitative insight could be found. We also considered the quantum measurement process and showed that a quantum version of Maxwell’s demon could be related to the work extraction of a quantum system, closely related to arrow-of-time measures for quantum measurement, as described in our article “Thermodynamics of quantum measurement and Maxwell's demon's arrow of time”. This work was selected in Phys. Rev. A as an Editor’s Suggestion. A recent preprint titled “Cyclic Superconducting Quantum Refrigerators Using Guided Fluxon Propagation” accomplished an important piece of this grant: to propose a new kind of quantum refrigerator using the dynamics of fluxons in a type II superconductor. This invention envisioned a race-track type geometry where fluxons are confined. By applying a gradient of magnetic field together with electric current in a Corbino geometry, the circulating fluxons can actively cool a cold reservoir, realizing a new type of cyclic superconducting refrigerator. We also investigated the possibility of thermal control from different points of view. The application of quantum measurement to the system gives a new kind of control on the system of interest – we have pioneered this approach and shown that measurement can boost the thermal power of quantum engines as described in “Continuous measurement boosted adiabatic quantum thermal machines”. The ability to have heat flows on demand is an outstanding challenge, and we have provided new solutions to this problem in Thermal control across a chain of electronic nanocavities” for a chain of electron cavities using gating voltage control. The control methods using qubit/qubit coupling to create absorption fridges at their most fundamental level have also been developed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Improving Marine Energy Production Through Commercialization of a Low Cost, Drag-Reducing Slippery Coating (CRADA 679 Abstract)

Marine energy capture systems offer great promise for providing clean energy, but they operate in a challenging and dynamic environment and must be optimized to the highest extent possible. Computational studies predict that drag reduction on marine energy and blue economy systems will result in meaningful improvements in energy efficiency. Based on extensive coating experience, PNNL is proposing to bring to market a new drag-reducing coating called Superhydrophobic Lubricant-Infused Drag-Efficient Coating – SLIDE-Coat. PNNL has a deep knowledge base regarding this class of slippery coatings, and we have a group of enthusiastic industry partners who have committed to partnering, conducting field testing, and providing well over 50% cost share. In addition to validating the technology, the team will create a commercialization roadmap to ensure the commercial success of the technology after the government-sponsored two-year program is complete. The main technical goal is to design, manufacture, and experimentally validate a new coating that can reduce hydrodynamic skin friction drag by 20%. The main commercialization goal is to develop a roadmap that identifies activities needed to complete SLIDE-Coat’s development after the conclusion of this project. Year 1 will focus on adaptation and modification of the existing SLIC coating system to optimize drag reduction and assessment and quantification of drag reduction on relevant materials in a laboratory setting. Year 2 will focus on optimizing and demonstrating drag reduction with preferred coatings. The manufacturability, ease of application, adhesion to relevant surfaces, and consistency will be assessed. Quantification of drag reduction on prototype materials in a relevant marine field setting will be executed.

16 TIDAL AND WAVE POWER↗

Polysulfamates as “Macroisosteres” of Polyurethanes with Improved Degradability

Abstract Addressing the environmental persistence of plastics requires the development of next‐generation polymers that combine high performance with enhanced degradability. Progress toward this grand challenge has been impeded, in part, by the absence of a general blueprint for the macromolecular design of such materials. Herein, we introduce a “macroisostere” design strategy, where the carbonyl group (–CO–) in polyurethanes (PUs) is replaced with a sulfonyl group (–SO 2 –), resulting in a virtually unknown family of polymers called polysulfamates. This approach, inspired by the use of bioisosteres in drug discovery, aims to preserve key interchain interactions that contribute to thermomechanical performance while enhancing the hydrolytic lability of the polymer backbone. The optimization of a Sulfur(VI) Fluoride Exchange (SuFEx) polymerization allowed the synthesis of ten polysulfamates structurally analogous to common PUs. Comparative analysis of one PU and its polysulfamate analog showed that this isosteric substitution increases thermal stability, slightly lowers the glass transition temperature, and retains similar hardness and reduced Young's modulus. Notably, the S(VI)‐based polysulfamate demonstrated significantly enhanced hydrolytic degradability. These results highlight the potential of the “macroisostere” approach as a generalizable strategy for designing high‐performance, degradable alternatives to traditional plastics.

Chemistry↗

Pairing a Global Optimization Algorithm with EXAFS to Characterize Lanthanide Structure in Solution

Ensemble-average sampling of structures from ab initio molecular dynamics (AIMD) simulations can be used to predict theoretical extended X-ray absorption fine structure (EXAFS) signals that closely match experimental spectra. However, AIMD simulations are time-consuming and resource-intensive, particularly for solvated lanthanide ions, which often form multiple nonrigid geometries with high coordination numbers. Here, to accelerate the characterization of lanthanide structures in solution, we employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm, to efficiently screen first-shell structures. As case studies, we examine two systems: Eu(NO 3 ) 3 dissolved in acetonitrile with a terpyridine ligand (terpyNO 2 ), and Nd(NO 3 ) 3 dissolved in acetonitrile. The theoretical spectra for structures identified by NWPEsSe were compared to both experimental and AIMD-derived EXAFS spectra. The NWPEsSe algorithm successfully identified the proper solvation structure for both Eu(NO 3 ) 3 (terpyNO 2 ) and Nd(NO 3 )(acetonitrile) 3 , with the calculated EXAFS signals closely matching the experimental spectra for the Eu-ligand complex and showing good similarity for the Nd salt; the better agreement with the ligand-containing structure is attributed to a less dynamic coordination environment due to the rigid ligand. The key advantage of the global optimization algorithm lies in its ability to sample the coordination environment across the potential energy surface and reduce the time required to identify structures from generally a month to within a week. Additionally, this approach is versatile and can be adapted to characterize main-group metal complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗