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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Postdoc Accord in Theoretical High Energy Physics

We present the results of a survey meant to assess the opinion of the high-energy physics theory (HET) community on the January 7th postdoc acceptance deadline - specifically, whether there is a preference to shift the deadline to later in January or February. This survey, which served for information-gathering purpose only, is part of a community conversation on the optimal timing of an acceptance deadline and whether the community would be better served by a later date. In addition, we present an analysis of data from the postdoc Rumor Mill, which gives a picture of the current hiring landscape in the field. We emphasize the importance of preserving a universal deadline, and the current results of our survey show broad support for a shift to a later date. A link to the survey, frequently asked questions, a running list of supporters, and next steps can be found on our companion web page.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Analytical Modeling of Biomass Transport and Feeding Systems

The processing of biomass solids in a biorefinery consists of pretreatment, enzyme hydrolysis / concurrent fermentation of sugars to ethanol, product recovery, and drying. Sustainable operation requires a front end that transforms wet solids into a pumpable slurry. Otherwise the biorefinery will suffer unscheduled shut-downs and inefficient operation due to solids that obstruct pumps and other equipment and resist mixing in a bioreactor. Downtime in pioneer biorefineries due to interruptions from materials handling problems has been 50% or more, leading to unsustainable manufacturing processes. This work addresses new technology, predictive computational models, and definition of operational conditions that result in formation of slurries of corn stover at up to 300 g/L using low enzyme loadings (1 to 3 FPU cellulase/g) before the biomass (corn stover) enters the pretreatment step. A team of researchers from Purdue University, Idaho National Laboratory (INL), Forest Concepts, AdvanceBio, Argonne National Laboratory, and DOE BETO have combined their knowledge in agricultural and biological engineering, bioprocess engineering, mechanical engineering, chemical engineering, agricultural economics, materials engineering and enzyme and microbial technology to address the challenge of making lignocellulose flow. This team effort has resulted in the development and validation of conditions that employ low levels of commercial enzyme in an agitated bioreactor to which corn stover pellets are added resulting in formation of slurries at high solids loadings, before pretreatment. This approach overcomes challenges caused by handling of dry, particulate biomass materials at the front end of the biorefinery. The subsequent materials handling issues cause obstruction at pumps, pipes and valves. Formation of high loadings slurries with low yield stress, as reported here, significantly decreases the potential for process interruption and enhances plant operability. Key advances in the knowledge of how slurry formation occurs is reported here and in recently published journal papers. We found that pellets are needed to achieve high solids loading, and that commercial enzymes are effective in forming slurries of corn stover particles from pellets that have not been pretreated. Our work has resulted in models that predict solids behavior for formation of compressed solids and pellets that in turn facilitate slurries made of high concentrations of corn stover particles. A computational model was developed that gives mechanistic insights into properties of particles and mixing process that gives the slurry rheology needed to facilitate pumping. Hence, the corn stover may be pumped into a pretreatment reactor in place of auguring in solids against high pressure which is a root cause of interruptions at the front end of a biorefinery. Subsequent mixing in enzyme and microbial bioreactors results in conversion of lignocellulose to sugars in a biorefinery in agitated bioreactors, with flows in and out of the vessels being less likely to be interrupted due to plugging or materials handling problems. The obtained data coupled to process models, techno-economic assessment (TEA) and Life Cycle Analysis (LCA) were used to assess whether this approach is practical. These results are based on a foundation of laboratory characterization and pilot runs. The NREL biochemical sugar model was utilized to carry out techno-economic analysis of enzyme catalyzed liquefaction followed by enzyme hydrolysis. The minimum sugar selling price was between 17.5 and 18.3 ¢/pound or about the same as calculated by the NREL model for dilute acid pretreatment followed by enzyme hydrolysis. Life cycle analysis (LCA) based on Argonne’s Greet Model showed the enzyme catalyzed route had the lowest greenhouse gas emissions of the three combinations studied (i.e., enzyme, enzyme mimetic, and enzyme + mimetic combined). GHG emissions for enzyme-based corn stover liquefaction step, alone, were about 21 g CO 2 -equivalent/kg of liquefied slurry. We believe this approach will further enhance operability of a pioneer biorefinery, and bring large-scale conversion of lignocellulosic biomass to low carbon footprint biofuels closer to implementation.

09 BIOMASS FUELS↗
DOE OSTI2021

Volumetrically Absorbing Thermal Insulator (VATI) for High-temperature Receivers

This project seeks to exploit volumetric absorption of concentrated solar irradiation in a thin, high-temperature, thermally conductive medium. High efficiency thermal conversion is achieved by volumetric absorption of both incoming solar irradiation (short wavelength) and emitted irradiation (long wavelength), demonstrating a volumetrically absorbing thermally insulating (VATI) effect. The thermalized energy is conducted to the back wall, enclosing the working fluid (molten salt or supercritical CO 2 ). Reliance on conductive thermal transport requires a thermally conductive medium, in the absence of which large temperature gradients drive losses due to emission. The project’s outcomes are important to realize a cost-effective approach to reduce optical and thermal losses from CSP receivers at high temperatures (720°C). High-temperature stable and commercially available porous SiC structures (open-cell foams) were explored as a volumetrically absorbing and thermally insulating layer. To the best of our knowledge, the current state-of-the-art for industrially deployed coatings is Pyromark. However, Pyromark suffers degradation at 700+°C and diurnal temperature changes. This necessitates periodic recoating, and the downtime increases the overall levelized cost of energy (LCOE) production. On the other hand, contemporary research activities have generated significant advances in the development of selective emitter coatings, which present challenges with costs, scalability, and stability. The pursued approach alleviates these concerns by developing a receiver that utilizes the inherent structure of high-temperature stable porous materials to enable robust and cost-effective receivers which require no periodic maintenance downtimes. The overall goal of the project is to experimentally demonstrate a figure of merit (FOM) of 0.92 at a temperature of 720°C and solar irradiation of 1000x concentration with porous receivers. The relevant crystallographic (phase) optical and thermal properties of porous SiC were first characterized. Second, the 3-D geometry of the porous SiC was analyzed using micro-X-ray tomography and converted to CAD data using image processing analysis. Utilizing this 3-D geometry and relevant optical/thermal properties, Monte Carlo- Ray Tracing (MCRT) analysis was performed to extract important parameters governing solar-thermal energy conversion such as extinction coefficient (β, 1/m), scattering albedo (ω) and the scattering phase function (Φ). These properties were then integrated into an in-house radiative and conduction transport model to solve for temperature and transport fluxes characterizing the solar-thermal energy conversion. This model was utilized to predict the FOM for various SiC porous geometries and to identify the highest possible FOM. Testing of the optimized porous structures will be accomplished with a custom-built high-accuracy (< ±4%) FOM measurement test-stand and a 1000x solar concentrator. When neglecting convective losses and resistance at the open boundary and the back wall, the optimized SiC foam leads to a FOM of 0.84. This FOM does not surpass the performance of Pyromark 2500. Yet, conversely to Pyromark 2500, SiC is stable at high temperatures and does not degrade over time. Also, it is possible to boost the FOM of SiC by engineering its effective thermal conductivity and its scattering albedo. A FOM of 0.92 is predicted for an optimized foam by accounting for convective losses and resistance at the open boundary and the back wall. This largely exceeds the FOM of Pyromark 2500 (~0.86) predicted by neglecting convective losses and resistance. Therefore, further engineering of the foam could lead to unprecedented FOMs.

14 SOLAR ENERGY↗
DOE OSTI2021

Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 6061-T651 Aluminum Alloy from Plate

Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The matters of interest here are the elastic-plastic response and ductile failure behavior of 6061-T651 aluminum alloy under the conditions described above. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of a modular $J_2$ plasticity model with isotropic hardening as well as a ductile failure model. Both included modules that accounted for temperature and strain rate dependence. The models were coupled with an adiabatic heating module to calculate the temperature rise due to the conversion of plastic work to heat. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s as well as four geometries of notched tension specimens and two tests on specimens with shear-dominated deformations. The test data collected allowed the calibration of both the plasticity and the ductile failure models. Most test specimens were extracted from a single piece of plate to maintain consistency. Notched tension tests came from a possibly different plate, but from the same lot. When using the model in structural finite element calculations, element formulations and sizes different from those used to model the test specimens in the calibration are likely to be used. A brief investigation demonstrated that the failure model can be particularly sensitive to the element selection and provided an initial guide to compensate in a specific example.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Analysis of heat transfer and AuNPs-mediated photo-thermal inactivation of E. coli at varying laser powers using single-phase CFD modeling

In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and scientific progress. The intermediate aim of the work was to present the calibration of the model with respect to the gold nanorods experiment. The purpose of this work is to study the effect of initial concentration of E. coli bacteria, the design of the chamber and the laser power on heat transfer and inactivation of E. coli bacteria. Using the CFD simulation, the work combines three main concepts. 1. The conversion of laser light to heat has been described by a combination of three distinctive approximations: a- Discrete particle integration to take into account every nanoparticle within the system, b- Rayleigh-Drude approximation to determine the scattering and extinction coefficients and c- Lambert–Beer–Bourger law to describe the decrease in laser intensity across the AuNPs. 2. The contribution of the presence of E. coli bacteria to the thermal and fluid-dynamic fields in the microdevice was modeled by single-phase approach by determining the effective thermophysical properties of the water-bacteria mixture. 3. An approach based on a temperature threshold attained at which bacteria will be inactivated, has been used to predict bacterial response to temperature increases. The comparison of the thermal fields and temporal temperature changes obtained by the CFD simulation with those obtained experimentally confirms the accuracy of the light-heat conversion model derived from the aforementioned approximations. The results show a linear relationship between maximum temperature and variation in laser power over the range studied, which is in line with previous experimental results. It was also found that the temperature inside the microchamber can exceed 55 °C only when a laser power higher than 0.8 W is used, so bacterial inactivation begins. The experimental data allows to determinate the concentration of nanoparticles. This parameter is introduced into the mathematical model obtaining the same number of AuNPs. However, this assumption introduces a certain simplification, as in the mathematical model the distribution of nanoparticles is uniform. This work is directly connected to the use of gold nanoparticles for energy conversion, as well as the field of bacterial inactivation in microfluidic systems such as lab-on-a-chip. Presented mathematical and numerical models can be extended to the entire spectrum of wavelengths with particular use of white light in the inactivation of bacteria. This work represents a significant advancement in the field, as to the best of the authors’ knowledge, it is the first to employ a single-phase computational fluid dynamics (CFD) approach specifically combined with the thermal inactivation of bacteria. Moreover, this research pioneers the use of a numerical simulation to analyze the temperature threshold of photothermal inactivation of E. coli mediated by gold nanorods (AuNRs). The integration of these methodologies offers a new perspective on optimizing bacterial inactivation techniques, making this study a valuable contribution to both computational modeling and biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predation probabilities and functional responses: How piscivorous waterbirds respond to pulses in fish abundance

Abstract How predators respond to changes in prey abundance (i.e., functional responses) is foundational to consumer–resource interactions, predator–prey dynamics, and the stability of predator–prey systems. Predation by piscivorous waterbirds on out‐migrating juvenile steelhead trout ( Oncorhynchus mykiss ) is considered a factor affecting the recovery of multiple Endangered Species Act‐listed steelhead populations in the Columbia River basin. Waterbird functional responses, however, may vary by predator species and location, with important implications to predator management strategies. We used a 13‐year dataset on waterbird abundance across seven breeding colonies (three Caspian tern [ Hydroprogne caspia ], two double‐crested cormorant [ Nannopterum auritum ], and two California and ring‐billed gull [ Larus californicus and Larus delawarensis ] colonies) and steelhead tag‐recovery data (>645,000 tagged and >32,000 recovered steelhead) to quantify weekly predation probabilities and functional responses across waterbird species, colonies, and years. Weekly predation probabilities were highly variable, ranging from 0.01 to 0.30 at tern colonies, 0.01 to 0.20 at cormorant colonies, and 0.03 to 0.13 at gull colonies. Per capita predation probabilities were an order of magnitude higher at inland tern and cormorant colonies relative to estuary colonies of the same species. Terns displayed Type II functional responses across colonies and years, where predation probabilities peaked at low steelhead abundances and declined as steelhead abundance increased (i.e., predator swamping). Cormorants nesting at the large estuary colony (several thousand birds) displayed a Type III functional response, but cormorants nesting at the smaller inland colony (several hundred birds) displayed a Type II response. Consumption probabilities of steelhead by gulls remained consistent across a large range of steelhead availability, suggesting a Type I or a Type III functional response, but a lack of colony abundance data prevented quantifying functional responses. The level of tern predation combined with Type II functional responses indicate possible population‐level impacts that could destabilize small or declining prey populations. Conversely, the apparent Type III functional responses of gulls and estuary nesting cormorants are indicative of prey switching behaviors targeted at periods of high steelhead abundance. Our results illustrate the complexity of predator–prey interactions and the importance of quantifying predator‐ and location‐specific functional responses when predicting the efficacy of management strategies to enhance prey populations.

Hostetter, Nathan J.↗
DOE OSTI2025

Spectroscopy and crystallography define carotenoid oxygenases as a new subclass of mononuclear non-heme Fe II enzymes

Carotenoid cleavage dioxygenases (CCDs) are non-heme Fe II enzymes that catalyze the oxidative cleavage of alkene bonds in carotenoids, stilbenoids, and related compounds. How these enzymes control the reaction of dioxygen (O 2 ) with their alkene substrates is unclear. Here, we apply spectroscopy in conjunction with X-ray crystallography to define the iron coordination geometry of a model CCD, CAO1 (Neurospora crassa carotenoid oxygenase 1), in its resting state and following substrate binding and coordination sphere substitutions. Resting CAO1 exhibits a five-coordinate (5C), square pyramidal Fe II center that undergoes steric distortion toward a trigonal bipyramidal geometry in the presence of piceatannol. Titrations with the O 2 -analog, nitric oxide, show a >100-fold increase in iron–nitric oxide affinity upon substrate binding, defining a crucial role for the substrate in activating the Fe II site for O 2 reactivity. The importance of the 5C Fe II structure for reactivity was probed through mutagenesis of the second-sphere Thr151 residue of CAO1, which occludes ligand binding at the sixth coordination position. A T151G substitution resulted in the conversion of the iron center to a six-coordinate state and a 135-fold reduction in apparent catalytic efficiency toward piceatannol compared with the wildtype enzyme. Substrate complexation resulted in partial six-coordinate to 5C conversion, indicating solvent dissociation from the iron center. Additional substitutions at this site demonstrated a general functional importance of the occluding residue within the CCD superfamily. Taken together, these data suggest an ordered mechanism of CCD catalysis occurring via substrate-promoted solvent replacement by O 2 . CCDs thus represent a new class of mononuclear non-heme Fe II enzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Man‐in‐the‐middle attacks and defence in a power system cyber‐physical testbed

Abstract Man‐in‐The‐Middle (MiTM) attacks present numerous threats to a smart grid. In a MiTM attack, an intruder embeds itself within a conversation between two devices to either eavesdrop or impersonate one of the devices, making it appear to be a normal exchange of information. Thus, the intruder can perform false data injection (FDI) and false command injection (FCI) attacks that can compromise power system operations, such as state estimation, economic dispatch, and automatic generation control (AGC). Very few researchers have focused on MiTM methods that are difficult to detect within a smart grid. To address this, we are designing and implementing multi‐stage MiTM intrusions in an emulation‐based cyber‐physical power system testbed against a large‐scale synthetic grid model to demonstrate how such attacks can cause physical contingencies such as misguided operation and false measurements. MiTM intrusions create FCI, FDI, and replay attacks in this synthetic power grid. This work enables stakeholders to defend against these stealthy attacks, and we present detection mechanisms that are developed using multiple alerts from intrusion detection systems and network monitoring tools. Our contribution will enable other smart grid security researchers and industry to develop further detection mechanisms for inconspicuous MiTM attacks.

Wlazlo, Patrick↗
DOE OSTI2024

The crystal structure of bacteriophage λ RexA provides novel insights into the DNA binding properties of Rex-like phage exclusion proteins

Abstract RexA and RexB function as an exclusion system that prevents bacteriophage T4rII mutants from growing on Escherichia coli λ phage lysogens. Recent data established that RexA is a non-specific DNA binding protein that can act independently of RexB to bias the λ bistable switch toward the lytic state, preventing conversion back to lysogeny. The molecular interactions underlying these activities are unknown, owing in part to a dearth of structural information. Here, we present the 2.05-Å crystal structure of the λ RexA dimer, which reveals a two-domain architecture with unexpected structural homology to the recombination-associated protein RdgC. Modelling suggests that our structure adopts a closed conformation and would require significant domain rearrangements to facilitate DNA binding. Mutagenesis coupled with electromobility shift assays, limited proteolysis, and double electron–electron spin resonance spectroscopy support a DNA-dependent conformational change. In vivo phenotypes of RexA mutants suggest that DNA binding is not a strict requirement for phage exclusion but may directly contribute to modulation of the bistable switch. We further demonstrate that RexA homologs from other temperate phages also dimerize and bind DNA in vitro. Collectively, these findings advance our mechanistic understanding of Rex functions and provide new evolutionary insights into different aspects of phage biology.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Marine Energy Environmental Toolkit for Permitting and Licensing

The permitting and licensing process for marine energy in the U.S. could take up to 7 years for even small demonstrations or pilot studies despite existing resources like Tethys, MarineCadstre, and the FERC E-Library. The goal of the Marine Energy Environmental Toolkit Project was to increase regulators, developers, and marine energy innovators’ understanding of potential environmental effects of marine energy conversion devices deployments and provide information to make efficient and effective determinations during permitting and licensing; develop a one-stop shop for existing environmental, spatial, regulatory, and scientific data that allows users to access disparate sources of data through a series of tags and spatial queries. The Toolkit (marineenergy.app) builds upon prior U.S. Department of Energy (DOE) Water Power Technologies Office (WPTO) investments by pulling from WPTO-funded and outside resources to facilitate the permitting and licensing process, inform technology developers of required permits, and disseminate the latest knowledge of the environmental effects of these devices to regulators, developers, and marine energy innovators and stakeholders.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Transformation rate maps of dissolved organic carbon in the contiguous US

Riverine dissolved organic carbon (DOC) plays a vital role in regional and global carbon cycles. However, the processes of DOC conversion from soil organic carbon (SOC) and leaching into rivers are insufficiently understood, inconsistently represented, and poorly parameterized, particularly in land surface and Earth system models. As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux (P r ), accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. We then derive high-resolution P r maps over the contiguous US (CONUS) using SOC data from two different sources: the Harmonized World Soil Database v1.2 (HWSD) and SoilGrids 2.0. Both maps are developed following the same five major steps: (1) selecting independent catchments where observed riverine DOC data are available with reasonable quality; (2) estimating catchment-average SOC for the independent catchments; (3) estimating the P r values for these catchments based on the generic formula and catchment-average SOC; (4) developing a predictive model of P r with machine learning (ML) techniques and catchment-scale climate, hydrology, geology, and other attributes; and (5) deriving a national map of P r based on the ML model. For evaluation, we compare the DOC concentration derived using the P r map and the observed DOC concentration values at evaluation catchments. The resulting mean absolute scaled error and coefficient of determination are 0.73 and 0.47 for the HWSD-based model and 0.58 and 0.72 for the SoilGrids-based model, respectively, suggesting the effectiveness of the overall methodology. Efforts to constrain uncertainty and evaluate sensitivity of P r to different factors are discussed. To illustrate the use of such maps, we derive a riverine DOC concentration reanalysis dataset over CONUS. The two P r maps, robustly derived and empirically validated, lay a critical cornerstone for better simulating the terrestrial carbon cycle in land surface and Earth system models. Our findings not only set a foundation for improving our predictive understanding of the terrestrial carbon cycle at the regional and global scales, but also hold promises for informing policy decisions related to decarbonization and climate change mitigation. The data presented in this study are publicly available at https://doi.org/10.5281/zenodo.14563816 (Li et al., 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Quantitative Prediction of Perovskite Stability Using Accelerated Testing and Machine Learning

PV technologies based on hybrid perovskites offer the potential for reducing solar cell costs, but they are particularly vulnerable to degradation by environmental factors such as moisture, oxygen, and illumination. Commercialization will require not only stable materials and device architectures but also accelerated testing protocols and models that can predict degradation from the accelerated testing data. Here, we report results from in situ photoluminescence (PL) and photoconductivity (PC) measurements during perovskite degradation with simultaneous optical transmittance (Tr) measurements or reflected dark field (DF) imaging. From PL, PC, Tr, and DF, we determine (respectively) the steady-state quasi-Fermi level splitting, the mean effective carrier diffusion length, the extent of conversion of perovskite to higher bandgap degradation products, and the extent of scattering from domains with different orientation or composition, all as a function of time during degradation. Simultaneous measurement of PL-PC-Tr or PL-PC-DF on perovskite absorbers in an environmental chamber over a wide range of humidity, oxygen, temperature, and illumination levels yields a rich data set. We use machine learning to develop a model that accurately predicts (within 10%) the time for the diffusion length to decrease to 85% of its initial value. The model takes the environmental conditions and the first few measurements from the PL-PC-Tr or PL-PC-DF experiment as input. Thus, the model provides a framework to interpret the results of accelerated testing of absorber materials. One of the dominant features in the model of degradation for CH 3 NH 3 PbI 3 is the initial rate at which transmittance increase. For devices with opaque contacts, the pixel-averaged rate of change of the intensity in dark-field images can be used in place of transmittance. Results are also presented on full PV devices with in-situ current-voltage (JV) measurements. Here, the data from simultaneous PL-DF-JV under environmental stresses reveal intimate connection between degradation and shunts and provide a framework to extend accelerated testing to devices. Further, the presentation reveals underlying universal behavior in degradation pathways over a broad range of environmental stresses and perovskite compositions.

14 SOLAR ENERGY↗
DOE OSTI2024

Annual Technology Baseline (ATB): The 2024 Transportation Update

The Transportation Annual Technology Baseline (ATB) provides detailed cost and performance data, estimates, and assumptions for vehicle and fuel technologies in the United States. It includes current and projected estimates for vehicle technologies as well as fuels, and it details the assumptions used to calculate those costs, such as gas and electricity prices, discount rates, and vehicle miles traveled. The 2024 update added more biofuels pathways to align with pathways used in the Biomass Scenario Model.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗
DOE OSTI2020

Molecular Structure of Sphingomyelin in Fluid Phase Bilayers Determined by the Joint Analysis of Small-Angle Neutron and X-ray Scattering Data

In this work, we have determined the fluid bilayer structure of palmitoyl sphingomyelin (PSM) and stearoyl sphingomyelin (SSM) by simultaneously analyzing small-angle neutron and X-ray scattering data. Using a newly developed scattering density profile (SDP) model for sphingomyelin lipids, we report structural parameters including the area per lipid, total bilayer thickness, and hydrocarbon thickness, in addition to lipid volumes determined by densitometry. Unconstrained all-atom simulations of PSM bilayers at 55 °C using the C36 CHARMM force field produced a lipid area of 56 Å 2 , a value that is 10% lower than the one determined experimentally by SDP analysis (61.9 Å2). Furthermore, scattering form factors calculated from the unconstrained simulations were in poor agreement with experimental form factors, even though segmental order parameter (S CD ) profiles calculated from the simulations were in relatively good agreement with S CD profiles obtained from NMR experiments. Conversely, constrained area simulations at 61.9 Å 2 resulted in good agreement between the simulation and experimental scattering form factors, but not with S CD profiles from NMR. We discuss possible reasons for the discrepancies between these two types of data that are frequently used as validation metrics for molecular dynamics force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Substrate–Support Interactions Mediate Hydrogenation of Phenolic Compounds by Pd/CeO 2 Nanorods

Ceria-supported palladium (Pd/CeO 2 ) has spawned significant attention in recent years due to its ability to catalyze selective hydrogenation of phenolic compounds to cyclohexanones and cyclohexanols at a mild temperature and pressure. However, the mechanistic basis by which ceria enhances catalytic conversion is still unclear. Here, we use the increase in the 13 C transverse relaxation rate upon the addition of nanoparticles (NPs) ( 13 C ΔR 2 ) to investigate the adsorption of phenolic compounds on the surface of the Pd/CeO 2 catalyst by solution NMR. We show that hydroxyphenols adsorb on the support more efficiently than underivatized phenol and methoxyphenols and that phenol derivatives with an oxygen atom at position 2 (i.e., 2-hydroxyphenol and 2-methoxyphenol) form very stable interactions with the Pd site of Pd/CeO 2 . An analysis of the kinetics of hydrogenation revealed that catalytic conversion is linearly correlated with the ability of the substrate to form interactions with the CeO 2 support and is inhibited by the formation of stable substrate–Pd adducts. Our data suggest that CeO 2 –substrate interactions mediate phenol hydrogenation more efficiently than Pd–substrate interactions and explain the exceptional catalytic performance reported for Pd/CeO 2 .

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

Catalytic Reduction of Esters over Zirconia-Supported Metal Catalysts

Esters are often produced as unwanted byproducts during the catalytic upgrading of ethanol to diesel fuel precursors through Guerbet coupling. Removal of esters from the product stream is important to prevent the loss of downstream catalyst activity from ester-derived carboxylic acids. In this work, we studied ester hydrogenolysis to the parent alcohols as a viable route for enhanced diesel fuel production. Specifically, we investigated the reduction of hexyl acetate in butanol over ZrO 2 -supported Ni, Co, Cu, Rh, Pd, and Pt catalysts, where Cu/ZrO 2 was the most selective catalyst for the hydrogenolysis of hexyl acetate into hexanol and ethanol. Thermodynamic analysis reveals that a 90% alcohol yield can be obtained at 200 °C, 30 bar, and a relatively high H 2 :hexyl acetate molar ratio of 480:1. Experimentally, an alcohol yield of 88% yield was obtained with a 10 wt % Cu/ZrO 2 catalyst at these conditions with a residence time of 5.4 h kg cat kmol gas –1 . Catalytic tests on the support revealed that ZrO 2 catalyzes the transesterification reaction between hexyl acetate and butanol. However, only the Cu sites can catalyze the hydrogenolysis of the esters into the final alcohols. We developed a kinetic model for our experimental results, which shows that the transesterification and hydrogenolysis reactions run at two different timescales, the former being 10 times faster than the latter. Data regression has been used to develop a model to predict the mole fraction distribution of ester hydrogenolysis products over a wide range of contact times. Cu/ZrO 2 loses half its catalytic activity after 80 h of time on stream. Modeling of deactivation data reveals that the ZrO 2 support conserves a residual activity due to external active sites, while active sites over the Cu surface deactivate at different rates. Furthermore, the catalytic conversion of esters into their parent alcohols is relevant to the production of surrogate liquid fuels since alcohols can be bimolecularly dehydrated to produce a blend of ethers with diesel fuel-like properties.

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

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion

In this Letter, we introduce FusionNet, a multi-modality deep learning framework designed to predict and analyze output pulses in high-power rare-earth-doped laser systems driving parametric conversion in homogeneous guided nonlinear media. FusionNet integrates temporal, spectral, and physical experimental conditions to model ultrafast nonlinear phenomena, including parametric nonlinear frequency conversion, self-phase modulation, and cross-phase modulation in homogeneous guided systems such as gas-filled hollow-core fibers. These systems bridge physical models with experimental data, advancing our understanding of light-guiding principles and nonlinear interactions while expediting the design and optimization of on-demand high-power, high-brightness systems. Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. This work establishes a new paradigm for accelerating parametric simulations and optimizing experimental designs in high-power laser systems, with further implications for high-precision spectroscopy, quantum information science, and distributed entangled interconnects.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Predominance of Methanomicrobiales and diverse hydrocarbon–degrading taxa in the Appalachian coalbed biosphere revealed through metagenomics and genome–resolved metabolisms

Coalbed deposits are a unique subsurface environment and represent an underutilized resource for methane generation. Microbial communities extant in coalbed deposits are responsible for key subsurface biogeochemical cycling and could be utilized to enhance methane production in areas where existing gas wells have depleted methane stores, or in coalbeds that are unmined, or conversely be utilized for mitigation of methane release. Here we utilize metagenomics and metagenome-assembled genomes to identify extant microbial lineages and genome-resolved microbial metabolisms of coalbed produced water, which has not yet been explored in the Appalachian Basin. Our analyses resulted in the recovery of over 40 metagenome-assembled genomes (MAGs) from eight coalbed methane wells. The most commonly identified taxa among samples were hydrogenotrophic methanogens from the order Methanomicrobiales and these dominant MAGs were highly similar to one another. Conversely, low-abundance coalbed bacterial populations were taxonomically and functionally diverse, mostly belonging to a variety of Proteobacteria classes, and encoding various hydrocarbon solubilization and degradation pathways. Further, the data presented herein provides novel insights into Appalachian Basin coalbed microbial ecology, and our findings provide new perspectives on underrepresented Methanocalculus species and low-relative abundance bacterial assemblages in coalbed environments, and their potential roles in stimulation or mitigation of methane release.

59 BASIC BIOLOGICAL SCIENCES↗