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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗
DOE OSTI2023

Unifying principles for catalytic hydrotreating processes (Final Technical Report)

This project builds on the hypothesis that the hydrotreating processes for the removal of oxygen and sulfur are fundamentally similar at the atomic-scale and existing knowledge from the treatment of petroleum derived feedstock can be leveraged for the design of novel catalysts for the upgrade of bio-oil. We tested this hypothesis by comparing computed potential energy diagrams for hydrodesulfurization (HDS) of thiophene over MoS 2 with hydrodeoxygenation (HDO) of furan over MoO 3 and concluded that certain aspects, such as catalyst promotion with transition metals, are valid strategies for both reactions. On the other hand, we also noticed significant differences in the mechanism for hydrogen (H 2 ) activation, which requires sites with metallic character. While MoS 2 is known to have metallic edge states that can catalyze H 2 dissociation, this elementary step is prohibitively slow on defect-free oxides. Only in the presence of vacancies or by creating metal/oxide interfaces can efficient H 2 activation sites during HDO be formed. The need for bifunctional catalyst when it comes to efficient and selective HDO or dehydrogenation reactions was further corroborated in joint experimental and theoretical studies of the Guerbet reaction for the coupling of biomass derived oxygenates over PdCu alloys, nitrate reduction over In-promoted Pd nanoparticles, and ethylene dehydroaromatization over Ga-exchanged ZSM-5 zeolites. All of these catalytic systems have in common that catalytic sites with distinct functional requirements are needed to create a working catalyst. Detailed computational studies were carried out for HDO of m -cresol and phenol on Ru-modified TiO 2 surfaces, which allowed us to attribute catalytic activity to the metal/oxide interface. A surprising finding was that heterolytic cleavage of the H-H bond across the Ru/TiO 2 interface was critically important, despite lower barriers for homolytic H 2 activation on Ru metal. The explanation lies in the high barriers for hydrogen spillover from Ru to TiO 2 , which becomes unnecessary in the heterolytic activation pathway. Moreover, we also reported that proton transfer steps between metal and oxide sites are mediated by weakly adsorbed surface water. During attempts to develop and validate a kinetic Monte Carlo (kMC) model for HDO reactions at the Ru/TiO 2 interface, it became clear that lateral interactions are paramount to describe realistic surface chemistry and without these interactions, the reduction and hydroxylation behavior from our simulations was inconsistent with reported experiments. To assess the importance of lateral interactions in popular computational catalyst design strategies relying on the identification of reactivity descriptors, which can be used along with Brønsted–Evans–Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends, we compared predicted trends with those obtained from descriptor-based kMC models. We critically evaluated the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. The mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, we concluded that the MKM approach does provide an overall better entry point for computational catalyst design. Overall, this project has led to 11 peer-reviewed publications, and their scientific is impact is well illustrated by their combined 702 citations.

08 HYDROGEN↗
DOE OSTI2021

Measurement and modeling of proton-induced reactions on arsenic from 35 to 200 MeV

72 As is a promising positron emitter for diagnostic imaging that can be employed locally using a 72 Se generator. However, current reaction pathways to 72 Se have insufficient nuclear data for efficient production using regional 100–200 MeV high-intensity proton accelerators. In order to address this deficiency, stacked-target irradiations were performed at LBNL, LANL, and BNL to measure the production of the 72 Se/ 72 As positron emission tomography (PET) generator system via 75 As (p, x) between 35 and 200 MeV. This work provides the most well-characterized excitation function for 75 As ( p , 4 n ) 72 Se starting from threshold. Additional focus was given to report the first measurements of 75 As (p, x) 68 Ge and bolster an already robust production capability for the highly valuable 68 Ge/ 68 Ga PET generator. Thick target yield comparisons with prior established formation routes to both generators are made. In total, high-energy proton-induced cross sections are reported for 55 measured residual products from 75 As, nat Cu , and nat Ti targets, where the latter two materials were present as monitor foils. These results were compared with literature data as well as the default theoretical calculations of the nuclear model codes TALYS, COH, EMPIRE, and ALICE. Reaction modeling at these energies is typically unsatisfactory due to few prior published data and many interacting physics models. Therefore, a detailed assessment of the talys code was performed with simultaneous parameter adjustments applied according to a standardized procedure. Particular attention was paid to the formulation of the two-component exciton model in the transition between the compound and preequilibrium regions, with a linked investigation of level density models for nuclei off of stability and their impact on modeling predictive power. This paper merges experimental work and evaluation techniques for high-energy charged-particle isotope production in an extension to an earlier study of this kind.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation

This Final Scientific and Technical Report summarizes work performed under the Phase IIA SBIR project “Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation” (DE-SC0020906) from August 2023 through August 2025. The objective of the Phase IIA effort was to mature and harden capabilities developed during Phase II, with the goal of enabling practical interoperability between Coreform’s isogeometric analysis (IGA) technologies and the Multiphysics Object-Oriented Simulation Environment (MOOSE), while improving robustness, performance, and scalability for complex, nuclear-relevant geometries. Over the course of Phase IIA, the project established and validated an extraction-based interoperability pathway between Coreform tools and MOOSE. A combined mesh and matrix format was defined collaboratively with MOOSE developers and integrated into the solver, enabling standard MOOSE workflows to operate on data exported from Coreform’s IGA and Flex Representation Method (FRM) pipelines. Early demonstrations validated architectural compatibility using linear solid mechanics problems, while later efforts focused on benchmark testing and external use. By the end of the project period, engineers at BWXT were able to independently set up and execute a simulation using the Coreform–MOOSE workflow and provide direct feedback that informed further refinement. In parallel, substantial effort was devoted to improving the robustness of trimmed U-spline construction for complex CAD geometries. A growing test suite of nuclear-relevant models was compiled through collaboration with multiple stakeholders and used to drive extensive bug fixing and reliability improvements. These efforts resulted in improved robustness and performance, including the addition of fallback capabilities that enhance reliability when the underlying commercial CAD kernel fails. Performance-oriented work progressed later in the project, with the development and demonstration of methods to decompose complex geometries into structured subregions and updated data representations to support more efficient solver processing. Additionally, extensive enhancements to threadsafe parallel data structures and trimming operations established a foundation for scalable processing of large assemblies. Collaboration with Sandia National Laboratories on the SGM geometric modeling kernel advanced to a functioning interface test case, positioning the workflow for future kernel integration. Overall, the Phase IIA effort successfully transitioned the project from architectural proof-of-concept to externally exercised, solver-integrated capability, while clarifying remaining technical challenges related to standardization, performance optimization, and kernel integration.

42 ENGINEERING↗
DOE OSTI2023

Exploring sustainable electricity system development pathways in South America’s MERCOSUR sub-region

South America has abundant natural water and energy resources, and exploiting these resources to achieve a clean energy future is central to the continent’s economic and sustainable development objectives for the next several decades. Designing pathways to achieving this clean energy future requires better understanding the structural, techno-economic, and policy forces that may influence the future development of the electricity sector in the region. Here, we focus on an interconnected electricity system of five South American countries – Argentina, Brazil, Chile, Paraguay, and Uruguay – which represent major electricity generation, consumption, and trade dynamics in the region. We explore the implications of various forces that could shape the future composition of the power sector in the sub-region, including: evolving renewable energy cost and performance, natural gas prices, cross-border interconnection facilities, early retirement of installed hydropower, and different decarbonization goals. We use a model framework based on a power system planning platform (GridPath) to co-optimize investment and operations of generation, storage, and transmission facilities out to 2050. Our results in a Reference scenario indicate that the electricity system can maintain a relatively clean energy portfolio by leveraging existing hydropower capacity and integrating increasingly cost-competitive wind and solar power. However, dependence on natural gas in the region is likely to remain high. A low-carbon electricity system can cost-effectively be achieved through policy interventions (e.g., renewable portfolio standards) and by diversifying investments in wind, solar, battery storage, and some new hydropower capacity. We also find that existing hydropower is critical for maintaining reliable future grid operations. Enhanced regional electricity trade, mostly based on existing interconnection capacities with nominal investment in new transmission, can significantly benefit the clean energy transition in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

2D in-Plane Ordered MXene Nanosheets Derived from (Mo 2/3 Er 1/3 ) 2 AlC Rare-Earth i-MAX for Energy Storage Applications

MXenes have become one of the most versatile families of two-dimensional (2D) materials due to their high conductivity, hydrophilicity, and remarkable electrochemical performance. This has stimulated intense efforts to design and synthesize MXenes, including structurally unique in-plane ordered 2D MXenes called i-MXenes. Here, we have synthesized the quaternary rare earth (RE)-based i-MAX phase (Mo 2/3 Er 1/3 ) 2 AlC using an arc melting method, and the corresponding 2D i-MXene was then obtained through a LiF/HCl soft etching process. Literature studies have shown that Al and the RE element are etched out during the etching process, leading to the formation of pure vacancy-ordered Mo1.33C 2D i-MXene. However, our investigation reveals that upon exposure to a fluorine solution, the i-MAX phase forms RE fluoride impurities, which are challenging to remove through HCl−DI water washing and persist in the final product, resulting in impure Mo 1.33 C@Er i-MXene. These results were confirmed by various characterizations such as X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, and scanning transmission electron microscopy. Although the Mo 1.33 C@Er electrode showed a 24-fold increase in specific capacitance compared to its parent i-MAX phase, it still exhibited a high charge-transfer resistance arising from the insulating nature of RE fluoride byproducts, which adversely influence the overall capacitance behavior of the synthesized 2D Mo 1.33 C@Er i-MXenes. This study contributes to identifying pathways for the preparation of pure 2D i-MXenes from RE-based i-MAX phases and developing improved synthesis methods. With additional process optimization, the 2D i-MXene holds a strong potential for electrochemical energy storage applications. Additionally, the electronic structures of Mo 1.33 C were theoretically studied using first-principles density functional theory calculations, which revealed that pristine Mo 1.33 C is metallic, and this metallic nature is preserved even with −O, −F, and mixed functionalization.

chemical structure↗
NASA NTRS1992

Inputs from regularly and irregularly discharging vestibular nerve afferents to secondary neurons in squirrel monkey vestibular nuclei. III. Correlation with vestibulospinal and vestibuloocular output pathways

1. A previous study measured the relative contributions made by regularly and irregularly discharging afferents to the monosynaptic vestibular nerve (Vi) input of individual secondary neurons located in and around the superior vestibular nucleus of barbiturate-anesthetized squirrel monkeys. Here, the analysis is extended to more caudal regions of the vestibular nuclei, which are a major source of both vestibuloocular and vestibulospinal pathways. As in the previous study, antidromic stimulation techniques are used to classify secondary neurons as oculomotor or spinal projecting. In addition, spinal-projecting neurons are distinguished by their descending pathways, their termination levels in the spinal cord, and their collateral projections to the IIIrd nucleus. 2. Monosynaptic excitatory postsynaptic potentials (EPSPs) were recorded intracellularly from secondary neurons as shocks of increasing strength were applied to Vi. Shocks were normalized in terms of the threshold (T) required to evoke field potentials in the vestibular nuclei. As shown previously, the relative contribution of irregular afferents to the total monosynaptic Vi input of each secondary neuron can be expressed as a %I index, the ratio (x100) of the relative sizes of the EPSPs evoked by shocks of 4 x T and 16 x T. 3. Antidromic stimulation was used to type secondary neurons as 1) medial vestibulospinal tract (MVST) cells projecting to spinal segments C1 or C6; 2) lateral vestibulospinal tract (LVST) cells projecting to C1, C6; or L1; 3) vestibulooculo-collic (VOC) cells projecting both to the IIIrd nucleus and by way of the MVST to C1 or C6; and 4) vestibuloocular (VOR) neurons projecting to the IIIrd nucleus but not to the spinal cord. Most of the neurons were located in the lateral vestibular nucleus (LV), including its dorsal (dLV) and ventral (vLV) divisions, and adjacent parts of the medial (MV) and descending nuclei (DV). Cells receiving quite different proportions of their direct inputs from regular and irregular afferents were intermingled in all regions explored. 4. LVST neurons are restricted to LV and DV and show a somatotopic organization. Those destined for the cervical and thoracic cord come from vLV, from a transition zone between vLV and DV, and to a lesser extent from dLV. Lumbar-projecting neurons are located more dorsally in dLV and more caudally in DV. MVST neurons reside in MV and in the vLV-DV transition zone.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗
DOE OSTI2021

DOE Energy Frontier Research Centers Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio)

New capabilities to predict, design and control the chemistries of carbon could answer a global imperative to transition from fossil-based to sustainable transportation fuels. While the use of inexpensive hydrocarbons has been an unparalleled achievement and enabler of economic prosperity for many nations, singular dependence upon crude oil has given rise to systemic vulnerabilities in climate, energy, economic, and national security. Lignocellulosic biomass, a renewable and carbon-neutral resource, has the potential to displace an estimated annual equivalent of three billion barrels of oil in the U.S. alone (National Research Council 2009, U. S. Department of Energy, 2011). However, biomass has only one-third the energy density of crude oil (Agrawal and Singh 2009, Richard 2010) and lacks petroleum’s versatility as a feedstock for fuels and chemicals. These limitations keep biomass conversion below the efficiency level needed for strategic impact while the scientific challenge of routing carbon from one molecular context to another remains unmet. In 2009, the Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio) recognized the potential of chemical catalysis and fast pyrolysis to overcome such limitations by transforming the main components of biomass (cellulose, xylan, and lignin) from grasses and trees directly to liquid hydrocarbons and aromatic co-products. Enabled by the EFRC high-risk, high-reward approach to grand challenge science, C3Bio researchers have been key national players in disrupting the conventional paradigm of the cellulosic biorefinery into a new future of “no carbon left behind”—the full utilization of carbon from plant cell walls in energy-dense fuels (Fig. 1). We identified catalytic and fast-pyrolytic pathways that utilize cellulose, xylan and, most significantly, lignin. We developed catalytic processes that deoxygenate and transform monomers and isolated polymers into useful products and tested their use with intact biomass. We gained control of lignin synthesis within plants and initiated tailoring biomass to its end-use through the tools of plant molecular biology and genetic engineering. C3Bio breakthroughs have increased the energy density of biomass-derived substrates via catalytic and pyrolytic conversions into products such as benzoquinones, furfural and hydroxymethylfurfural, levoglucosan and levulinic acid, methoxypropylphenols and propylbenzene. Such advances in biomass conversion would not have been possible without simultaneous advances in analytical instrumentation and methodologies, and imaging technologies and applications. The legacy science developed by C3Bio enables design and control strategies for achieving a targeted product portfolio of fuel and chemical feedstocks from a diverse range of native and tailored biomass. Our research provides the knowledge base required for a bio-economy with product streams as diverse in functionality as those of the petrochemical industry. Coupling targeted computational modeling with experimentation, we achieved: (1) fundamental understanding of biopolymers and cell wall architecture assembly, (2) discovery of new chemistries that allow the development of highly selective pathways to fuels and desirable chemicals, and (3) an integrated systems-level understanding to control catalytic and pyrolytic pathways.

09 BIOMASS FUELS↗
DOE OSTI2024

“Mn 3 AlN” is Really Mn 4 N

We investigate the synthesis of antiperovskite “Mn 3 AlN” using the published synthesis procedure, as well as several new reaction pathways. In each case, only a combination of antiperovskite Mn 4 N and Mn 5 Al 8 or precursors is obtained. The identity of the obtained antiperovskite phase is unambiguously determined to be Mn4N via synchrotron powder X-ray diffraction (SPXRD), X-ray absorption spectroscopy (XAS), and magnetometry. The experimental results are further supported by thermochemical calculations informed by density functional theory (DFT), which find Mn 3 AlN to be metastable versus decomposition into Mn and AlN. The DFT-based calculations also predict an antiferromagnetic ground state for Mn3AlN. This directly contradicts the previously reported ferromagnetic behavior of "Mn 3 AlN". Instead, the observed magnetic behavior is consistent with ferrimagnetic Mn 4 N. We examine the data in the original publication and conclude that the compound reported to be Mn 3 AlN is in fact Mn 4 N.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

High-resolution (30-m) urban land cover projections for Los Angeles California Urban Area: 2010 to 2100 under SSP3 and SSP5 [Updated simulations based on population-driven urban intensity transitions]

These data (v3) are updated from previous versions (1 and 2) in that they include consider the effects of population on transitions in urban land intensity. This leads to more reasonable differences in urban land projections under variant SSPs. For the present dataset, both SSP3 and SSP5 are provided. These data represent simulations of future land use and land cover (LULCC) for Los Angeles urban area (U.S. Census Bureau defined area) as raster tiff images at a 30-m pixel resolution and at decadal time steps from 2010 to 2100. LULCC classes in this product follow the National Land Cover Dataset (NLCD) classification. NLCD 21-24 correspond to open developed, low developed, medium developed, and high developed urban land classes, respectively. Only urban land cover classes (NLCD class 21, 22, 23, and 24) are dynamic over time; however, all NLCD classes are included in the final product. Therefore, NLCD classes that do not convert to an urban class will be similar to year 2000. The products were developed using a hybridized statistical and cellular automata approach. Linear mixed models (LMMs) were used to estimate future urban land budgets based on 1-km urban land fraction projections from Gao and Pesaresi (2021), whereas separate generalized linear mixed models (GLMMs) were used to estimate shifts in urban land intensities based on retrospective shifts in NLCD urban class intensities over a 20- year period. Based on urban land allocations from the statistical models, a cellular-automata and downscaling routine was used to simulate dynamic urban land expansion at a 30-m resolution based on suitability criteria. Scenarios of future urban landcover change projections include variant solutions for the Shared Socioeconomic Pathway 5 (SSP5) and SSP 3 based on different population assumptions, different land use intensification assumptions, variable land zoning constraints, and iterative adjustments to correct for over allocation of urban expansion across decadal time periods from 2010 to 2100. This results in 320 raster products.

Land↗
DOE OSTI2025

Spin-State and Reorganization Energy Considerations for Metal-Centered Photoredox Catalysis

Transition-metal complexes featuring metal-centered excited states have recently emerged as mechanistically distinct platforms for selective photochemistry, including photoredox catalysis. Among these, Co(III) complexes have demonstrated productive photoinduced electron transfer via the 3 T 1 metal-centered state. In contrast, photoreactivity from the 5 T 2 metal-centered state in Fe(II) polypyridyl complexes remains limited. Building on our prior report concerning reactivity associated with the 5 T 2 state in [Fe(tren(py) 3 )] 2+ (tren(py) 3 = tris(2-pyridylmethyliminoethyl)-amine), we introduced stronger-field ligands in an effort to increase excited-state energies of Fe(II) polypyridyl complexes and enhance reactivity. Despite achieving nanosecond-scale excited-state lifetimes and favorable thermodynamic driving forces, no photoreactivity was observed. Reinvestigation of the observations previously reported for [Fe(tren(py) 3 )] 2+ revealed interactions between the metal complex and the substrate in their respective ground states that mimicked dynamic quenching of the chromophore, prompting a reassessment of mechanistic considerations inherent in leveraging reductive chemistry from the 5 T 2 excited state of Fe(II). Our analysis indicates that electron transfer from the 5 T 2 excited state of a low-spin d6 metal is subject to significant barriers both in terms of reorganization energies and spin conservation that undermines its ability to act as an electron donor for photoredox catalysis. In contrast, ligand fields that are sufficient to stabilize the 3 T 1 excited state have available to them numerous spin-allowed and, in certain cases, near-barrierless pathways to engage in excited-state electron transfer (both oxidative and reductive depending on the identity of the metal). These results highlight the critical role of spin-state changes and their associated reorganization energy requirements in metal-centered photoredox catalysis.

charge transfer↗
DOE OSTI2025

Efficient machine learning interatomic potentials robust for liquid and multiple solid polymorphs of NaF and KF

Achieving atomic-level understanding of crystallization of molten salts is of importance to a wide range of technological applications. Recent work [Fan et al., Proc. Natl. Acad. Sci. USA 122, e2425702122 (2025)] revealed that crystal nucleation in molten LiF salt is a multistage process according to the molecular-dynamics (MD) simulations based on an atomic cluster expansion (ACE) machine-learning interatomic potential (MLIP). In order to understand the influence of increasing cation size on nucleation pathways and nucleation rates of molten fluoride salts, here we develop two new ACE MLIPs for NaF and KF. The two ACE MLIPs feature DFT-SCAN-level accuracy for liquid and multiple solid polymorphs over a wide temperature (0–2000 K) and pressure (0–100 GPa) range, and also reproduce well a number of experimental data for solid and liquid equilibrium properties. The efficiency of the two ACE MLIPs enable million-atom-scale or microsecond-scale MD simulations. The two general-purpose ACE MLIPs are expected to be useful for atomistic simulations for different purposes, in addition to studying crystallization of molten NaF and KF salts.

Crystal melting↗
DOE OSTI2020

Pathway to Complete Energy Sector Decarbonization with Available Iridium Resources using Ultralow Loaded Water Electrolyzers

We present ultralow Ir-loaded (ULL) proton exchange membrane water electrolyzer (PEMWE) cells that can produce enough hydrogen to largely decarbonize the global natural gas, transportation, and electrical storage sectors by 2050, using only half of the annual global Ir production for PEMWE deployment. This represents a significant improvement in PEMWE's global potential, enabled by careful control of the anode catalyst layer (CL), including its mesostructure and catalyst dispersion. Using commercially relevant membranes (Nafion 117), cell materials, electrocatalysts, and fabrication techniques, we achieve at peak a 250× improvement in Ir mass activity over commercial PEMWEs. An optimal Ir loading of 0.011 mg Ir cm -2 operated at an Ir-specific power of ~100 MW kg Ir -1 at a cell potential of ~1.66 V versus RHE (85% higher heating value efficiency). Here, we further evaluate the performance limitations within the ULL regime and offer new insights and guidance in CL design relevant to the broader energy conversion field.

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

Interplay between Mixed and Pure Exciton States Controls Singlet Fission in Rubrene Single Crystals

Singlet fission (SF) is a multielectron process in which one singlet exciton S converts into a pair of separated triplet excitons T. SF is widely studied as it may help overcome the Shockley−Queisser efficiency limit for semiconductor photovoltaic cells. To elucidate and control the SF mechanism, great attention has been given to the identification of intermediate states in SF materials, which often appear elusive due to the complexity and fast time scales of the SF process. Here, we apply 14 fs-1 ms transient absorption techniques to high-purity rubrene single crystals to disentangle the intrinsic fission dynamics from the effects of defects and grain boundaries and to identify reliably the fission intermediates. Our data demonstrates that above-gap excitation directly generates a hybrid vibronically assisted mixture of singlet state and triplet-pair multiexciton [S/TT], which rapidly (<100 fs) and coherently branches into pure singlet or triplet excitations. The relaxation of [S/TT] to S is followed by a relatively slow and temperature-activated (48 meV activation energy) incoherent fission process. The SF competing pathways and intermediates revealed here unify the observations and models presented in previous studies of SF in rubrene and offer alternative strategies for the development of SF-enhanced photovoltaic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

CO 2 Chemisorption Behavior in Conjugated Carbanion-Derived Ionic Liquids via Carboxylic Acid Formation

Superbase-derived task-specific ionic liquids (STSILs) represent one of the most attractive and extensively studied systems in carbon capture via chemisorption, in which the obtained CO 2 uptake capacity has a strong relationship with the basicity of the anions. High energy input in desorption and side reactions caused by the strong basicity of the anions are still unsolved issues. The development of other customized STSILs leveraging an alternative driving force to achieve efficient CO 2 chemisorption/desorption is highly desirable yet challenging. Here, in this work, carbanion-derived STSILs were developed for efficient CO 2 chemisorption via a carboxylic acid formation pathway. The STSIL with the deprotonated malononitrile molecule ([MN]) as the anion exhibited much higher CO 2 uptake capacity than the one derived from 2-methylmalononitrile ([MMN]). Notably, this trend was opposite to their basicity ([MN] < [MMN]). Detailed characterization of the products, supported by density functional theory simulations of spectra and calculations of the reaction energetics, demonstrated that carboxylic acid was formed upon reacting with CO 2 via proton transfer in [MN]-derived STSILs but not in the case of [MMN] due to lack of an α-H. The preference of the carboxylic acid product over carboxylate formation was driven by the extended conjugation among the central sp 2 carbon, the as-formed carboxylic acid, and the two nitrile groups. The achievements made in this work provide an alternative design principle of STSILs by leveraging the extended conjugation in the CO 2 -integrated product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Decoding α-MoC 1− x Nanoparticle Formation in Continuous Flow via Machine Learning

Molybdenum carbide nanoparticles (α-MoC 1−x NPs) are promising catalysts that offer noble-metal-like performance at lower cost. We report a mild continuous-flow synthesis of α-MoC 1−x NPs from Mo(CO) 6 , coupled with in-line spectroscopic monitoring and machine learning (ML)-based analysis to quantify precursor conversion and product formation in real time. A multilayer perceptron ML model was found to accurately deconvolute complex, nonlinear spectral patterns, enabling identification of a two-step reaction pathway, involving precursor conversion to an amorphous intermediate followed by intraparticle crystallization to α-MoC 1−x NPs, with the first step being rate limiting. Ex situ small angle X-ray scattering (SAXS) and X-ray diffraction (XRD) validation confirm the predicted concentration profiles and crystallization behavior. This integrated approach showcases how ML can empower insights into NP nucleation and growth, paving the way for self-driving, flow-based platforms for NP synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗