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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Impact of U-10Mo HALEU fuel element tolerances on the Massachusetts Institute of Technology reactor safety and operational performance – Thermal hydraulics

The U.S. is coordinating efforts for the conversion of six U.S. High Performance Research Reactors (USHPRR) including one critical facility from highly enriched uranium (HEU) to low-enriched uranium (LEU). In order to continue the mission of these reactors, including the Massachusetts of Institute of Technology Reactor (MITR), and achieve similar performance, high-assay low-enriched uranium (HALEU) with a high-density metallic alloy of uranium with 10 wt% molybdenum (U-10Mo) is being evaluated. The impact of the fabrication specification and tolerances was assessed following the preliminary design of the MITR LEU fuel elements using the U-10Mo monolithic alloy. This research focuses on the analysis of fabrication specification impact on thermal hydraulics (TH) characteristic of the MITR LEU core as a function of the variation of the relevant fuel specification parameters (e.g., coolant channel gap thickness, fuel plate thickness, etc.). The analyses are performed based on an all-fresh LEU fuel conversion plan identified in a preliminary safety analysis report submitted to the Nuclear Regulatory Commission. The reactor power margin to the onset of nucleate boiling (ONB) is assessed under the limiting safety system settings (LSSS), where a scram occurs, to ensure there is sufficient margin to the reactor safety limit, which is defined by the onset of flow instability that occurs after the ONB. The best estimate plus uncertainty approach is employed to analyze this TH characteristic, which yields realistic results while maintaining adequate conservatism, utilizing a statistical uncertainty propagation method with the STAT7 code. The TH characteristic is analyzed as a function of the variability of the specification parameters resulting from the fabrication process. The main findings of this study show that the MITR core can meet the TH safety and operational requirements at the all-LEU initial core startup (cycle 1), selected transition cycles (most reactive cycle and most limiting cycle: cycle 3 and 5, respectively) and equilibrium (cycle 14) cores under all limiting fabrication parameter combinations considered. In addition, the analyses show that the dependency of the core power margin to ONB on those specification parameters that have the most direct impact on TH performance is non-linear but monotonically decreasing within the specification tolerances. The third order polynomial fit curves are reported in detail for selected limiting cases and can serve as a powerful tool for future MITR fuel management in cases such as when HALEU supply is established that may allow additional cycle length or other operational benefits.

Conversion↗
DOE OSTI2025

Dynamic Line Rating Models and Their Potential for a Cost‐Effective Transition to Carbon‐Neutral Power Systems

Most transmission system operators (TSOs) currently use seasonally steady-state models considering limiting weather conditions that serve as reference to compute the transmission capacity of overhead power lines. The use of dynamic line rating (DLR) models can avoid the construction of new lines, market splitting, false congestions, and the degradation of lines in a cost-effective way. DLR can also be used in the long run in grid extension and new power capacity planning. In the short run, it should be used to help operate power systems with congested lines. The operation of the power systems is planned to have the market trading into account; thus, it computes transactions hours ahead of real-time operation, using power flow forecasts affected by large errors. In the near future, within a “smart grid” environment, in real-time operation conditions, TSOs should be able to rapidly compute the capacity rating of overhead lines using DLR models and the most reliable weather information, forecasts, and line measurements, avoiding the current steady-state approach that, in many circumstances, assumes ampacities above the thermal limits of the lines. Here, this work presents a review of the line rating methodologies in several European countries and the United States. Furthermore, it presents the results of pilot projects and studies considering the application of DLR in overhead power lines, obtaining significant reductions in the congestion of internal networks and cross-border transmission lines.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Control System Upgrade for Battery State-of-Charge Indications

The Advanced Test Reactor (ATR) Complex at Idaho National Laboratory (INL) relies on Battery Backed Power (BBP) systems and Uninterruptible Power Supplies (UPS) to ensure continuous power supply to critical components. This project aims to enhance the reliability and functionality of the battery monitoring and control systems by updating the State-of-Charge (SOC) system, Programmable Logic Controller (PLC), and Human-Machine Interface (HMI) for the nuclear safety-related battery banks. The current system, while functional, has areas for improvement, particularly in recharging calculations and alarm functions. The project objectives include developing flow charts, programming the new PLC and HMI, conducting bench tests, and updating design documentation. Additionally, the project ensures compliance with safety standards, develops training materials, creates comprehensive documentation, and integrates seamlessly with existing ATR infrastructure. The new SOC system is designed to be scalable for future upgrades, improve efficiency, enhance data accuracy, implement redundancy features, and achieve project goals within budget constraints while considering environmental impact. The methodology involved familiarizing with BBP and UPS systems, collecting current readings, rescaling signals, learning ladder logic, and updating the HMI. The transition from SLC 5/03 PLC using RS Logix 500 to CompactLogix 5380 using Studio 5000 was a key step. Despite challenges in transferring outdated PLC ladder logic and HMI code, starting from scratch led to a more accurate and efficient monitoring system, contributing to improved safety and operational efficiency. The project is currently awaiting approval of the Engineering Calculation and Analysis Report (ECAR) before implementation.

42 - ENGINEERING↗
DOE OSTI2025

Probing Nanorod Assembly and Dynamics in Polymer Nanocomposites in Equilibrium and Shear

Coarse-grained molecular dynamics simulations are used to examine the structure and dynamics of nanorod assemblies in polymer melts under equilibrium and simple shear. We show that as the concentration of nanorods increases, there is a transition from an isotropic phase to a two-phase region in which the nanorods phase separate into a dilute phase and dense bundles of hexagonally packed nanorods. The onset of the two-phase region is below that predicted by Onsager theory, which we attribute to an effective increase in the diameter of nanorods due to a layer of polymer bound to the rod surfaces. Equilibrium simulations show that increasing polymer chain length N enhances nanorod bundling at fixed nanorod concentration. Simulations of systems undergoing simple shear show that flow enhances nanorod alignment and bundling relative to those of equilibrium systems with similar properties. Finally, simulations reveal that increasing nanorod length enhances nanorod alignment under shear at equivalent shear rates but not at equivalent Péclet numbers. Overall, our simulations highlight that polymer matrix-nanorod attraction (i.e., chemistry), shear rate, and matrix chain length are desirable design variables to control the structure of nanorod-containing soft materials under simple shear.

diffusion↗
DOE OSTI2024

Stress Testing California's Hydroclimatic Whiplash: Potential Challenges, Trade‐Offs and Adaptations in Water Management and Hydropower Generation

Abstract Inter‐annual precipitation in California is highly variable, and future projections indicate an increase in the intensity and frequency of hydroclimatic “whiplash.” Understanding the implications of these shocks on California's water system and its degree of resiliency is critical from a planning perspective. Therefore, we quantify the resilience of reservoir services provided by water and hydropower systems in four basins in the western Sierra Nevada. Using downscaled runoff from 10 climate model outputs, we generated 200 synthetic hydrologic whiplash sequences of alternating dry and wet years to represent a wide range of extremes and transitional conditions used as inputs to a water system simulation model. Sequences were derived from upper (wet) and lower (dry) quintiles of future streamflow projections (2030–2060). Results show that carryover storage was negatively affected in all basins, particularly in those with lower storage capacity. All basins experienced negative impacts on hydropower generation, with losses ranging from 5% to nearly 90%. Reservoir sizes and inflexible operating rules are a particular challenge for flood control, as in extremely wet years spillage averaged nearly the annual basins' total discharge. The reliability of environmental flows and agricultural deliveries varied depending on the basin, intensity, and duration of whiplash sequences. Overall, wet years temporarily rebound negative drought effects, and greater storage capacity results in higher reliability and resiliency, and lesser volatility in services. We highlight potential policy changes to improve flexibility, increase resilience, and better equip managers to face challenges posed by whiplash while meeting human and environmental needs.

Environmental Sciences & Ecology↗
DOE OSTI2025

A quantitative risk assessment framework for fault reactivation in underground hydrogen storage: Coupled simulation and deep learning approach

Underground hydrogen storage (UHS) is emerging as a critical solution for large-scale energy storage. However, like all subsurface fluid injection activities, UHS poses the risk of injection-induced fault reactivation. Accurate risk assessment is essential to ensuring the safety and efficiency of UHS operations. This study presents the development of deep-learning surrogate models for fault reactivation prediction in UHS, trained on a comprehensive database of fully coupled fluid flow-geomechanics simulations. Our findings reveal that analytical models often yield unreliable estimates, with errors up to 54% in the allowable injection pressure, potentially leading to a 40% reduction in UHS operational capacity. The developed surrogate models were incorporated into a quantitative risk assessment (QRA) framework, enabling probabilistic evaluation of fault reactivation risk while accounting for uncertainties in the input variables. Site-specific features, such as horizontal stress gradients, fault’s dip and strike angles, and operational parameters like bottom-hole injection pressure and well-fault distance, were identified as the primary drivers of fault reactivation across various stress regimes. Whereas other hydraulic, geological, and poroelastic reservoir properties were found to have a secondary impact. Notably, we observed that the risk of fault reactivation for a critically oriented fault with a static friction coefficient greater than 0.55 remains below 10% in a normal faulting stress regime. However, the risk significantly increases as the stress regime transitions from normal to strike-slip and ultimately to reverse faulting conditions. These findings underscore the importance of rigorous site characterization and comprehensive QRA evaluations to optimize UHS performance and minimize geomechanical risks.

25 ENERGY STORAGE↗
DOE OSTI2026

Nonequilibrium universality of the nonreciprocally coupled 𝑂⁡(𝑛 1 ) × 𝑂⁡(𝑛 2 ) model

Nonequilibrium dynamics play an important role in all contexts of physics, both classical and quantum as well as living and nonliving, so it is crucial to develop a foundational understanding of nonequilibrium phase transitions. In this work we investigate an important class of nonequilibrium dynamics in the form of nonreciprocal interactions. In particular we study how nonreciprocal coupling between two 𝑂⁡(𝑛𝑖) order parameters (with 𝑖 = 1,2) affects the universality at a multicritical point, extending the analysis of J. T. Young et al. [Phys. Rev. X 10, 011039 (2020)], which considered the case 𝑛 1 = 𝑛 2 = 1, i.e., a ℤ 2 × ℤ 2 model. We show that nonequilibrium fixed points (NEFPs) emerge for a broad range of 𝑛 1 ,𝑛 2 and exhibit intrinsically nonequilibrium critical phenomena, namely a violation of fluctuation-dissipation relations at all scales and underdamped oscillations near criticality in contrast to the overdamped relaxational dynamics of the corresponding equilibrium models. Furthermore, the NEFPs exhibit an emergent discrete scale invariance in certain physically relevant regimes of 𝑛 1 ,𝑛 2 , but not others, depending on whether the critical exponent 𝜈 is real or complex. The boundary between these two regions is described by an exceptional point in the renormalization group (RG) flow, leading to distinctive features in correlation functions and the phase diagram. Another contrast with the previous work is the number and stability of the NEFPs as well as the underlying topology of the RG flow. Lastly, we investigate an extreme form of nonreciprocity where one order parameter is independent of the other order parameter but not vice versa. Unlike the ℤ 2 × ℤ 2 model, which becomes nonperturbative in this case, we identify a distinct nonequilibrium universality class whose dependent field similarly violates fluctuation-dissipation relations but does not exhibit discrete scale invariance or underdamped oscillations near criticality.

Critical phenomena↗
DOE OSTI2024

A nanoscale photonic thermal transistor for sub-second heat flow switching

Abstract Control of heat flow is critical for thermal logic devices and thermal management and has been explored theoretically. However, experimental progress on active control of heat flow has been limited. Here, we describe a nanoscale radiative thermal transistor that comprises of a hot source and a cold drain (both are ~250 nm-thick silicon nitride membranes), which are analogous to the source and drain electrodes of a transistor. The source and drain are in close proximity to a vanadium oxide (VO x )-based planar gate electrode, whose dielectric properties can be adjusted by changing its temperature. We demonstrate that when the gate is located close ( < ~1 µm) to the source-drain device and undergoes a metal-insulator transition, the radiative heat transfer between the source and drain can be changed by a factor of three. More importantly, our nanomembrane-based thermal transistor features fast switching times ( ~ 500 ms as opposed to minutes for past three-terminal thermal transistors) due to its small thermal mass. Our experiments are supported by detailed calculations that highlight the mechanism of thermal modulation. We anticipate that the advances reported here will open new opportunities for designing thermal circuits or thermal logic devices for advanced thermal management.

42 ENGINEERING↗
DOE OSTI2025

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗
DOE OSTI2025

Analysis of Liquids Using the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER)

We developed a sensor called the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER) probe, which uses an atmospheric pressure glow discharge below the surface of liquids to excite species in the liquid. Through emission spectroscopy of molten salts, liquid metals, and heavy water, we demonstrated the SPIDER probe’s high resolution, accuracy, and versatility. We successfully identified trace concentrations of transition and rare-earth metals in molten salts and detected the isotopic shift of the H β → D β emission line. Our analysis revealed unconventional spectral alkali line shapes, indicating two competing excitation modes: film explosion and droplet vaporization. The film explosion mode, characterized by dense plasma, exhibited self-reversal and broadband continuum emission, while the droplet vaporization mode, associated with diffusive plasma, produced narrow-line emissions. Furthermore, by analyzing circuit transients alongside individual plasma events, we observed that film explosions generate higher currents, likely due to a shorter plasma length as the current preferentially flows through the thin liquid layer. Altogether, our results highlight the SPIDER probe’s efficacy and flexibility, making it well-suited for online material quantification of liquids in extreme environments.

AES↗
DOE OSTI2025

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗
DOE OSTI2024

A block-spectral adaptive H-/$p$-refinement strategy for shock-dominated problems

An adaptive H-/p-refinement strategy using a novel sensor is devised and tested in a block-spectral compressible Euler code equipped with adaptive-mesh refinement (AMR) and high-order flux-reconstruction numerics. At each Gauss quadrature point (or solution point) within each spectral block (or mesh element) the discrete velocity jump ΔU = ∂U/∂y 1 Δy 1 + ∂V/∂y 2 Δy 2 + ∂W/∂y 3 Δy 3 is calculated and normalized by the local speed of sound, a. Here, the grid spacing, Δx i , is calculated in each direction as the distance between auxiliary Gauss-Lobatto points, staggered relative to the solution points. The polynomial order is increased from p = 0 to p = p max in regions of weak compression, (ΔU/a) crit < ΔU/a < 0 and kept at p = p max in regions of flow expansion ΔU/a ≥ 0, while staying at the H = 0 base mesh level. Regions experiencing strong compressions, i.e. ΔU/a < (ΔU/a) crit , are H-refined up to H = H max where H max is applied at the location of maximum compression, ΔU/a = min(ΔU/a) in the domain, while keeping p = 0 to guarantee robustness and monotonicity of the solution in the H refined region. The critical value of (ΔU/a) crit = -0.06 is found to effectively separate smooth and non-smooth solution regions, supported by a 1D detonation initiation test case in ideal gas and a shock-to-detonation transition in high explosives. Using this value, the Sod shock tube, Shu-Osher problem, double Mach reflection and a 2D detonation in a high-explosive are simulated with the proposed adaptive H-/p-refinement. In the Sod shock tube case, p-refinement resolves the (weak) contact discontinuity while H-refinement enhances the grid resolution in the shock exploiting the monotonicity of the p = 0 reconstruction. For the Shu-Osher problem, p-refinement captures the small-scale oscillations trailing the shock that would be otherwise attenuated, while H-refinement triggered by the ΔU-sensor appropriately tracks the shock. In the double Mach reflection problem, H-refinement confines the numerical diffusion around the reflected shock while p-refinement recaptures many physical features trailing the shock. Finally, in the 2D high-explosive detonation case, H-refinement follows the leading shock and resolves the curvature of the detonation wave, while p-refinement adds resolution to the trailing reaction zone. Finally, the proposed methodology is tested in a detonation-wave propagation test case in high-explosives with numerical predictions comparing favorably against experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

From photosynthetic electron flow to gene regulation: redox signal transduction in cyanobacteria

In cyanobacteria, the free-living ancestors of chloroplasts, photosynthesis simultaneously sustains growth and generates reactive oxygen species (ROS) that damage proteins, lipids, and DNA when light capture outpaces carbon fixation. Maintaining redox balance, therefore, requires cells to read photosynthetic electron flow as a signal that continuously tunes gene expression and protein activity. This review traces how these redox signals are transduced to transcription machinery through three routes: membrane-localized sensors, cytoplasmic redox sensors downstream of photosystem I, and ROS generated when electron sinks are saturated. Membrane-bound histidine kinases (two-component systems) relay the redox state of the plastoquinone pool to control photosystem remodeling, pigment biosynthesis, and circadian timing. Cytoplasmic one-component regulators, by contrast, sense redox directly through thiol-disulfide switches, glutathionylation, iron-sulfur clusters, and metal-catalyzed oxidation to control photosystem-cofactor, electron-carrier, and transition-metal homeostasis. Because many of these regulators persist in algal and plant chloroplasts, cyanobacteria illuminate principles of redox control across photosynthetic eukaryotes. Post-transcriptional and translational control further shapes redox-dependent gene expression programs through transcript stability, ribosome assembly, and translation initiation, extending redox regulation beyond transcription to every step of protein synthesis and even activity modulation. Finally, we connect redox regulation to photosynthetic physiology, stress resilience, and the rational engineering of cyanobacteria for sustainable bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hybrid combustion modeling approach for turbulent jet ignition in natural-gas pre-chamber spark-ignition engines at high EGR

Here, this study presented a hybrid modeling approach for simulating turbulent jet ignition and combustion processes in a natural-gas pre-chamber spark-ignition engine operating under exhaust gas recirculation (EGR) diluted conditions. In-depth analyses of experimental data and simulation results from previous work [Chinnathambi et al., ICEF2021-67836; Kim et al., Fuel 409: 137815, 2026] revealed two key findings: (i) the magnitude of pressure difference between the pre-chamber and main chamber ($∆P_{PC-MC}$) was positively correlated with the combustion duration from the moment of $∆P_{PC-MC}=0$ to the point of 5% mass fraction burned, with larger $∆P_{PC-MC}$ associated with longer duration; and (ii) the turbulent combustion regime in the main chamber transitioned from the broken reaction zone to the corrugated flamelet regime, with the Karlovitz number exceeding 100 immediately after turbulent hot jets were ejected from nozzles, coinciding with observed local extinction events. To accurately simulate the entire combustion process, a hybrid approach was developed under Reynolds-Averaged Navier Stokes framework, combining the G-equation model for pre-chamber combustion with the multi-zone well-stirred reactor approach and a turbulence-chemistry interaction (TCI) submodel for main chamber combustion. The TCI submodel accounted for the attenuation of reaction rates due to turbulent strain and modeled local extinction by suppressing reaction rates under certain flow and flame conditions. When applied to three EGR rate conditions toward the dilution limit, the hybrid modeling approach accurately reproduced experimental data in terms of cylinder pressure, apparent heat release rate, and the observed positive correlation, including the delayed onset of main chamber combustion—a feature not captured by existing combustion models.

computational fluid dynamics simulation↗
DOE OSTI2026

Analytical model for balling defects in laser melting using rivulet theory and solidification

In laser welding and additive manufacturing communities, the balling (humping) defect is primarily attributed to the Plateau–Rayleigh fluid instability (PRI) with a few authors suggesting fluid jetting and volume conservation as alternative mechanisms. As analytical descriptions of these mechanisms are unavailable, combining them into a single formalism is unfeasible. We present a new model of PRI with higher accuracy, accounting for competition with solidification, to compare the expected behavior with known experimental trends when fluid jetting is neglected. We adapt a rivulet instability model from fluid physics to account for the stabilizing effects of the substrate, which the traditional cylindrical-jet geometry does not account for and estimate the instability growth rate. Our model yields a continuous transition from non-balling to balling hitherto lacking in current literature and predicts instability growth at higher wavelengths with strong sensitivity to the solidification front curvature. While the fluid surface is most unstable for shallow melt pools, the absolute magnitude of balling relevant to printing defects scales with melt pool depth and has a maximum for a given melt pool geometry. Synchrotron-based x-ray radiography of thin samples indicates that PRI growth rates and solidification can be comparable in magnitude and thus compete, as we find in this work. We predict that deviations between model predictions and our experimental results demonstrate the importance of fluid flows and heat transport in the balling process. Our experiments further demonstrate at least one mechanism by which the melt pool length and the balling wavelength are not equivalent, as commonly claimed.

Taylor, Z. [Stanford Univ., CA (United States); SL↗
DOE OSTI2024

Preparation and Characterization of YBa 2 Cu 4 O 8 Superconductor

Solid-state reaction of appropriate amounts of Y 2 O 3 , BaCOs, and CuO for 2 h at 800°C in flowing oxygen with a total pressure of 2.7 x 10 2 Pa (2 mm Hg), followed by cooling and annealing at 750°C for 10 h in oxygen at ambient pressure, has produced orthorhombic YBa 2 Cu 4 O 8 (124) as the main phase with YBa 2 Cu 3 O x (123) as an impurity phase. After the as-calcined powder was annealed in oxygen at 800°C for 24 h under ambient pressure, the phase purity improved considerably. Calcined 124 powder was pressed into pellets and rapidly annealed at temperatures from 870°C to 935°C. At these temperatures, the 124 decomposed into 123. The superconducting transition temperature, T c , of the annealed samples depended upon the annealing temperature and atmosphere. The decomposed samples have been characterized by low field RF SQUID magnetometer and high resolution transmission electron microscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

High-Rate, Selective Electrosynthesis of Cyclohexanone Oxime via In Situ Generation and Release of Hydroxylamine on Bismuth

Oxime compounds are key industrial intermediates for nylon precursors and commodity chemicals. However, conventional routes rely on multistep reactions and hydroxylamine (NH 2 OH) salts, raising significant safety and sustainability concerns. Although electrosynthesis offers an alternative, oxime formation on d-block transition metals suffers from poor selectivity, as nitrogen oxyanion intermediates bind strongly to the surface and are readily over-reduced to ammonia. Here, we report morphology-controlled p-block bismuth rhombic dodecahedra (Bi RDs) that promote in situ NH 2 OH generation and its desorption into the electrolyte, enabling an electrochemical-chemical decoupled route for cyclohexanone oxime (CHO) synthesis. Bi RDs deliver nearly 100% Faradaic efficiency (FE) at −0.5 V vs. RHE and a yield of 1.4 mmol h –1 cm –2 at −0.9 V vs. RHE in an H-cell, while maintaining a CHO selectivity of nearly 100% at 100 mA cm –2 in a flow cell. Under identical conditions, d-block electrodes (Cu, Pd, Ag) show FE below 30%. Density functional theory calculations reveal that Bi 6p orbital-derived surface states weaken intermediate binding and facilitate NH 2 OH desorption, suppressing over-reduction. Kinetic analysis, post-addition trapping experiments, and in situ ATR-FTIR and Raman spectroscopy suggest the following reaction mechanism: NH 2 OH is selectively generated at the electrode surface, released as a freely diffusing intermediate, and undergoes homogeneous condensation with cyclohexanone in the bulk electrolyte, bypassing the surface-confined Langmuir–Hinshelwood pathway. These findings demonstrate that regulating intermediate desorption through p-block orbital chemistry provides a general strategy for achieving high selectivity in electro-organic nitrogen synthesis.

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

Demystifying group-4 polyolefin hydrogenolysis catalysis: Gaseous propane hydrogenolysis mechanism over the same catalysts

A kinetic/mechanistic investigation of gaseous propane hydrogenolysis over the single-site heterogeneous polyolefin depolymerization catalysts AlS/ZrNp 2 and AlS/HfNp 2 (AlS = sulfated alumina, Np = neopentyl), is use to probe intrinsic catalyst properties without the complexities introduced by time- and viscosity-dependent polymer medium effects. In a polymer-free automated plug-flow catalytic reactor, propane hydrogenolysis turnover frequencies approach 3,000 h −1 at 150 °C. Both catalysts exhibit approximately linear relationships between rate and [H 2 ] at substoichiometric [H 2 ] with rate law orders of 0.66 ± 0.09 and 0.48 ± 0.07 for Hf and Zr, respectively; at higher [H 2 ], the rates approach zero-order in [H 2 ]. Reaction orders in [C 3 H 8 ] and [catalyst] are essentially zero-order under all conditions, with the former implying rapid, irreversible alkane binding/activation. This rate law, activation parameter, and DFT energy span analysis support a scenario in which [H 2 ] is pivotal in one of two plausible and competing rate-determining transition states—bimolecular metal-alkyl bond hydrogenolysis vs. unimolecular β-alkyl elimination. The Zr and Hf catalyst activation parameters, ΔH ‡ = 16.8 ± 0.2 kcal mol −1 and 18.2 ± 0.6 kcal mol −1 , respectively, track the relative turnover frequencies, while ΔS ‡ = −19.1 ± 0.8 and −16.7 ± 1.4 cal mol −1 K −1 , respectively, imply highly organized transition states. These catalysts maintain activity up to 200 °C, while time-on-stream data indicate multiday activities with an extrapolated turnover number ~92,000 at 150 °C for the Zr catalyst. This methodology is attractive for depolymerization catalyst discovery and process optimization.

03 NATURAL GAS↗