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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 109 records · Page 6

A grid-scale study of demand bidding by large industrial users

A demand bidding mechanism for engaging large industrial electricity users in the operation of the power grid is presented. Demand bidding is formulated as an optimization problem based on a modified version of the alternating current optimal power flow problem, and can be interpreted as a tâtonnement process between the grid operator and electricity users. Here, the work provides the first – to the authors’ knowledge – grid-scale case study of demand bidding, using a synthetic grid structure in the footprint of the grid of Texas. Results reveal that the demand bidding lowers overall power generation costs, but economic benefits plateau as the number of participants increases. Transmission line and transformer capacity constraints become the limiting factors, revealing that expanding and fortifying the transmission infrastructure is key to expanding demand-side participation. Demand bidding does not substantially alter the optimal operation of existing bidding entities when the number of bidders increases, thereby supporting existing bidders to stay in the system and encouraging new ones to join.

Chlor-alkali plant↗

Surface Crust Formation Controls Evaporation Kinetics of Secondary Organic Aerosols

Gas-particle partitioning is critical for the evolution of secondary organic aerosols (SOA) in the atmosphere. SOA particles evaporate more slowly than expected at nearly size-independent rates, but the underlying mechanism remains controversial. Here, in this study, we apply kinetic multilayer modeling to simulate evaporation of α-pinene SOA, demonstrating that surface crust formation, emerging from accumulation of low-volatility compounds at the particle surface, leads to slow evaporation and reduced size dependence of the evaporation rate. While evaporation induced by decomposition of oligomers would naturally lead to size-independent evaporation rates, we observe and simulate nearly size-independent slow evaporation of polyethylene glycol mixture particles containing polymeric species that do not decompose, confirming the relevance of composition-dependent diffusivity for size-independent, slow evaporation. Slow evaporation of limonene SOA was also observed in environmental chamber experiments, and model simulations demonstrate strong surface crust formation with bulk diffusivity being depressed by up to 5 orders of magnitude compared to the inner bulk. We present experimental evidence using a surface-based mass spectrometry technique that shows that the particle surface becomes enriched in high molecular weight compounds upon evaporation of monomers. Our findings imply that viscous surface crusts may also limit the growth and chemical transformation of SOA particles, influencing their impacts on air quality and climate.

heterogeneous chemistry↗

Localized Orbital Excitation Drives Bond Formation in Plasmonic Catalysis

Localized surface plasmons generated on metallic nanostructures can be used to accelerate molecular transformations; however, the efficiency is limited by the challenge to control the energy/charge transfer at the interfaces. Here, we combine density functional theory (DFT) calculations and experiments to reveal the mechanism of nitrophenol reduction on Au nanoparticles under visible-light irradiation and propose a strategy to further enhance the reaction rates. DFT calculations show a reduced activation barrier under electronic excitation on Au(111), thus explaining the measured higher rates under visible-light irradiation. Furthermore, we propose a heterostructure with Au nanoparticles covered by a thin film of hexagonal boron nitride; the latter is used to decouple the molecular orbitals from the metal to enable charge localization in the molecule. DFT calculations show that, by this electronic decoupling, the activation barrier can be lowered by a factor of five. Furthermore, this work thus provides a valuable strategy for optimizing catalytic efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials representation and transfer learning for multi-property prediction

The adoption of machine learning in materials science has rapidly transformed materials property prediction. Hurdles limiting full capitalization of recent advancements in machine learning include the limited development of methods to learn the underlying interactions of multiple elements as well as the relationships among multiple properties to facilitate property prediction in new composition spaces. To address these issues, we introduce the Hierarchical Correlation Learning for Multi-property Prediction (H-CLMP) framework that seamlessly integrates: (i) prediction using only a material's composition, (ii) learning and exploitation of correlations among target properties in multi-target regression, and (iii) leveraging training data from tangential domains via generative transfer learning. The model is demonstrated for prediction of spectral optical absorption of complex metal oxides spanning 69 three-cation metal oxide composition spaces. H-CLMP accurately predicts non-linear composition-property relationships in composition spaces for which no training data are available, which broadens the purview of machine learning to the discovery of materials with exceptional properties. This achievement results from the principled integration of latent embedding learning, property correlation learning, generative transfer learning, and attention models. The best performance is obtained using H-CLMP with transfer learning [H-CLMP(T)] wherein a generative adversarial network is trained on computational density of states data and deployed in the target domain to augment prediction of optical absorption from composition. H-CLMP(T) aggregates multiple knowledge sources with a framework that is well suited for multi-target regression across the physical sciences.

36 MATERIALS SCIENCE↗

Pathways of bio-jet adoption in the US aviation industry with implications for the overall transportation and energy sectors: an integrated, multi-sectoral analysis of future scenarios

Bio-jet adoption has emerged as an attractive option to complement and supplement the use of refined fossil liquid fuels in the aviation industry in the US. However, there are significant uncertainties surrounding the costs of bio-jet including but not limited to costs of feedstock, transformation costs and the competition with co-products of bio-jet that may be demanded elsewhere in the transportation or energy sectors. This study models alternative trajectories of bio-jet adoption in the US aviation industry by 2050 through the use of a global integrated multi sector dynamics model. Three bio-jet production and consumption pathways are presented- soybean oil to jet, corn ethanol to jet (ETJ) and Fisher–Tropsch-based bio-jet, with each pathway explicitly considering the co-production of renewable diesel and renewable gasoline alongside the bio-jet. Without explicit actions or technology changes to offset the technology cost of bio-jet, scenarios where bio-jet displaces refined liquids result in higher aviation fuel prices (ranging from a 25% increase to 120% increase by mid-century) and lower demand (ranging from −14% to −43%). Corn ethanol will play an important role in the US if large scale amounts of bio-jet are to be produced with smaller effects on demand and prices. While scenarios with high levels of bio-jet availability without the availability of ETJ in the US can significantly reduce emissions in the aviation sector, these reductions are achieved more through the reduction in overall aviation fuel demand rather than technology adoption.

09 BIOMASS FUELS↗

Science Applications of Phased Array Radars

Phased array radars (PARs) are a promising observing technology, at the cusp of being available to the broader meteorological community. PARs offer near instantaneous sampling of the atmosphere with flexible beam forming, multi-functionality, low operational and maintenance costs, and without mechanical inertia limitations. These PAR features are transformative compared to those offered by our current reflector-based meteorological radars. The integration of PARs into meteorological research has the potential to revolutionize the way we observe the atmosphere. The rate of adoption of PARs in research will depend on many factors including i) the need to continue educating the scientific community on the full technical capabilities and trade-offs of PARs through an engaging dialogue with the science and engineering communities and ii) the need to communicate the breadth of scientific bottlenecks that PARs can overcome in atmospheric measurements and the new research avenues that are now possible using PARs in concert with other measurement systems. The former is the subject of a companion article that focuses on PAR technology while the latter is the objective here.

54 ENVIRONMENTAL SCIENCES↗

Digital Twin and Cybersecurity Requirements for Beartooth

This report summarizes the requirements for the Cybersecurity and the Digital Twin for Beartooth. The Beartooth digital twin will ultimately allow for both comprehensive offline data analysis and transformational autonomy. This document places limits on the IPL-funded work scope to end at a predictive digital twin stage but allow for future expansion to support full autonomy. It is expected that this work will support both currently funded LDRD and future direct-funded digital twin research.

42 ENGINEERING↗

Harnessing photoenzymatic reactions for unnatural biosynthesis in microorganisms

Photoenzymatic catalysis enables new-to-nature transformations, but its scalability is limited by high enzyme loading, costly cofactors, and radical-induced instability. Here we report the integration of light-driven photoenzymatic reactions into the cellular metabolism of Escherichia coli, bridging flavin-based photobiocatalysis with biosynthesis. Using synthetic biology strategies, we engineered microbial cells to continuously produce olefin substrates and ene-reductase photoenzyme while regenerating cofactors directly from glucose. By externally supplying radical precursors or by introducing synthetic pathways for their in situ production, we enabled fermentation-based microbial photobiosynthesis, achieving high titers and demonstrating its feasibility for scale-up in bioreactor. This approach extends photobiocatalysis from in vitro applications to in vivo semi-biosynthesis and complete biosynthesis, revealing its full potential for integrating light-driven reactions into cellular metabolism.

Bioproducts↗

Stress-Induced Structural Transformations in Au Nanocrystals

Nanocrystals can exist in multiply twinned structures like icosahedron or single crystalline structures like cuboctahedron. Transformations between these structures can proceed through diffusion or displacive motion. Experimental studies on nanocrystal structural transformations have focused on high-temperature diffusion-mediated processes. Limited experimental evidence of displacive motion exists. We report structural transformation of 6 nm Au nanocrystals under nonhydrostatic pressure of 7.7 GPa in a diamond anvil cell that is driven by displacive motion. X-ray diffraction and transmission electron microscopy were used to detect the structural transformation from multiply twinned to single crystalline. Single crystalline nanocrystals were recovered after unloading, then quickly reverted to the multiply twinned state after dispersion in toluene. Furthermore, the dynamics of recovery was captured using TEM which showed surface recrystallization and rapid twin boundary motion. Molecular dynamics simulations showed that twin boundaries are unstable due to defects nucleated from the interior of the nanocrystal.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Carbon Tetrachloride Degradation Results for 200-ZP-1 Operable Unit

Carbon tetrachloride (CT) contamination in the 200-ZP-1 Operable Unit (OU) at the Hanford Site originated from large-volume discharges to the subsurface during plutonium production operations between 1955 and 1973. Contamination migrated through more than 70 meters of unsaturated sediment to reach the underlying unconfined aquifer, where it persists as a large and complex groundwater plume. The 200-ZP-1 OU Record of Decision (ROD) requires that groundwater CT concentrations be reduced to 3.4 µg/L within 125 years. Current groundwater modeling projections estimate that the existing pump-and-treat, even when combined with monitored natural attenuation (specifically hydrolysis), will not achieve this target within the designated timeframe. A fundamental contributor to this shortfall is the extremely slow rate of CT hydrolysis under Hanford aquifer conditions, which has been estimated to have a half-life of 630 years. If faster-acting biotic and abiotic degradation processes are operating within the aquifer, their contribution to CT mass reduction could have a meaningful impact. However, site-specific measurements of these processes and their rates have not previously been performed. This report documents the results of a two-phase laboratory investigation designed to characterize and quantify the capacity of site-specific 200-ZP-1 OU sediments and groundwater to support natural attenuation of CT through biotic and abiotic pathways. In this context, degradation capacity is defined as the intrinsic potential of the subsurface matrix to transform CT under optimized, controlled conditions. System capacity is evaluated in two ways: (1) as rate-limited capacity, which establishes the maximum kinetic velocity of CT transformation and is measured using half-lives and first order rate constants; and (2) as mass limited capacity, which defines the total contaminant mass the batch experimental system can degrade before reactants are exhausted, representing the maximum amount of contaminant the microbial community and reactive mineral phases can transform under the experimental conditions.

abiotic degradation↗

Operando real-space imaging of a structural phase transformation in the high-voltage electrode LixNi0.5Mn1.5O4

Abstract Discontinuous solid-solid phase transformations play a pivotal role in determining the properties of rechargeable battery electrodes. By leveraging operando Bragg Coherent Diffractive Imaging (BCDI), we investigate the discontinuous phase transformation in Li x Ni 0.5 Mn 1.5 O 4 within an operational Li metal coin cell. Throughout Li-intercalation, we directly observe the nucleation and growth of the Li-rich phase within the initially charged Li-poor phase in a 500 nm particle. Supported by the microelasticity model, the operando imaging unveils an evolution from a curved coherent to a planar semi-coherent interface driven by dislocation dynamics. Our data indicates negligible kinetic limitations from interface propagation impacting the transformation kinetics, even at a discharge rate of C/2 (80 mA/g). This study highlights BCDI’s capability to decode complex operando diffraction data, offering exciting opportunities to study nanoscale phase transformations with various stimuli.

Sun, Yifei (ORCID:0000000295625120)↗

Raman spectroscopic characterization of SiO 2 phase transformation and Si substrate stress relevant to EBC performance

To accurately model the long-term durability of environmental barrier coatings (EBCs), a more complete understanding of the phase composition and transformations of the thermally grown oxide SiO 2 (TGO) is desired. For the TGO formed during thermal cycling in steam, cristobalite formation and the subsequent β- to α-cristobalite transformation has been identified as a potentially life-limiting mechanism. In this study, Raman micro-spectroscopy was used to quantify the cristobalite transformation on a polycrystalline Si coupon that was exposed to steam at 1350°C for 100 h. The phase transformation was mapped at 200–260°C on the TGO surface at different ramp rates using a heating stage and a micro-positioning stage. The stress in the Si substrate was also determined using Raman spectroscopy by measuring the stress induced peak shift. The α→β phase transformation produced a 300–500 MPa tensile stress in the Si substrate, which compared well to the stress predicted from the volumetric expansion of the cristobalite. In conclusion, quantifying the phase transformation and residual stress are critical tools in developing the next generation of high performance EBCs.

36 MATERIALS SCIENCE↗

Late-Stage Oxidation of C( sp 3 )─H Bonds with High Efficiency and Alkyl Group Dihydroxylation of Complex Molecules

Here, the late-stage oxidation of C(sp 3 )─H bonds is highly valuable for modulating the solubility and binding of bioactive compounds and for diversification of complex molecules. Undirected methods for C(sp 3 )─H oxidation are valuable for the installation of hydroxyl groups at sites remote from other functional groups present in the molecule, but existing catalysts are limited by low turnover numbers and lengthy ligand syntheses. Perfluorinated ruthenium porphyrins are highly active catalysts for the oxidation of alkyl C─H bonds, but the scope of the transformation with complex molecules under conditions of limiting substrate has not been investigated. We report that carbonylruthenium(II) tetrakis(pentafluorophenyl)porphyrin [Ru(TPFPP)(CO)] catalyzes the selective oxidation of tertiary C(sp 3 )─H bonds in a broad range of complex natural products and drugs, with turnover numbers as high as 1000, and the tolerance of the reaction to various functional groups was rapidly assessed by performing a model reaction in the presence of additives. We show how the combination of this undirected C(sp 3 )─H oxidation and a directed C(sp 3 )─H silylation and oxidation provides rapid access to highly oxidized, 1,2-diol derivatives of natural products by a formal dihydroxylation of an alkyl group.

Alcohols↗

Complex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks

As an optical processor, a diffractive deep neural network (D2NN) utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing, completing its tasks at the speed of light propagation through thin optical layers. With sufficient degrees of freedom, D2NNs can perform arbitrary complex-valued linear transformations using spatially coherent light. Similarly, D2NNs can also perform arbitrary linear intensity transformations with spatially incoherent illumination; however, under spatially incoherent light, these transformations are nonnegative, acting on diffraction-limited optical intensity patterns at the input field of view. Here, we expand the use of spatially incoherent D2NNs to complex-valued information processing for executing arbitrary complex-valued linear transformations using spatially incoherent light. Through simulations, we show that as the number of optimized diffractive features increases beyond a threshold dictated by the multiplication of the input and output space-bandwidth products, a spatially incoherent diffractive visual processor can approximate any complex-valued linear transformation and be used for all-optical image encryption using incoherent illumination. The findings are important for the all-optical processing of information under natural light using various forms of diffractive surface-based optical processors.

36 MATERIALS SCIENCE↗

Acid-base bifunctional porous liquids

Basic solutions are essential for gas-involved catalytic transformations, yet their ultralow free volume limits gas solubility and diffusivity. Engineering permanent porosity in such reactive liquids has remained a longstanding challenge. Here, we introduce a surface-sacrifice strategy that incorporates Brønsted-acidic zeolite nanocrystals into strong organic bases to create permanently porous reactive liquids. Stereochemically controlled acid–base neutralization at the external zeolite surface forms a thin ionic solvation shell that stabilizes the dispersion while fully preserving the internal microporosity and crystallinity of the zeolite framework. The resulting basic media exhibit persistent microporosity, confirmed by inert-gas sorption, 129Xe nuclear magnetic resonance, neutron scattering, and theoretical simulations. These porous liquids show significantly enhanced catalytic performance in CO2 conversion and hydrogenation reactions. The coexisting acidic and basic sites further enable antagonistic cascade catalysis within a single liquid phase. This surface-sacrifice approach provides a general route to introduce permanent porosity into reactive media, enabling boosted gas transformations.

Qiu, Liqi [University of Tennessee, Knoxville (UTK↗

Examining the order-of-limits problem and lattice constant performance of the Tao–Mo functional

In their recent communication a semi-local density functional derived from the density matrix expansion of the exchange hole localised by a general coordinate transformation. We show that the order-of-limits problem present in the functional, dismissed as harmless in the original publication, causes severe errors in predicted phase transition pressures. We also show that the claim that lattice volume prediction accuracy exceeds that of existing similar functionals was based on comparison to reference data that misses anharmonic zero-point expansion and consequently overestimates accuracy. Here, by highlighting these omissions, we give a more accurate assessment of the Tao-Mo functional and show a possible direction for resolving the order-of-limits problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Curating a comprehensive set of enzymatic reaction rules for efficient novel biosynthetic pathway design

Enzyme substrate promiscuity has significant implications for metabolic engineering. The ability to predict the space of possible enzymatic side reactions is crucial for elucidating underground metabolic networks in microorganisms, as well as harnessing novel biosynthetic capabilities of enzymes to produce desired chemicals. Reaction rule-based cheminformatics platforms have been implemented to computationally enumerate possible promiscuous reactions, relying on existing knowledge of enzymatic transformations to inform novel reactions. However, past versions of curated reaction rules have been limited by a lack of comprehensiveness in representing all possible transformations, as well as the need to prune rules to enhance computational efficiency in pathway expansion. To this end, we curated a set of 1224 most generalized reaction rules, automatically abstracted from atom-mapped MetaCyc reactions and verified to uniquely cover all common enzymatic transformations. Additionally, we developed a framework to systematically identify and correct redundancies and errors in the curation process, resulting in a minimal, yet comprehensive, rule set. These reaction rules were capable of reproducing more than 85% of all reactions in the KEGG and BRENDA databases, for which a large fraction of reactions is not present in MetaCyc. Our rules exceed all previously published rule sets for which reproduction was possible in this coverage analysis, which allows for the exploration of a larger space of known enzymatic transformations. By leveraging the entire knowledge of possible metabolic reactions through generalized enzymatic reaction rules, we are able to better utilize underground metabolic pathways and accelerate novel biosynthetic pathway design to enable bioproduction towards a wider range of new molecules.

59 BASIC BIOLOGICAL SCIENCES↗