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At least 325 records · Page 18

Assembling a Cyber Range to Evaluate Artificial Intelligence / Machine Learning (AI/ML) Security Tools

In this case study, we will describe the design and assembly of a cyber security test range we have built at Oak Ridge National Laboratory in Oak Ridge, TN, USA. The range is designed to provide a flexible environment to evaluate cyber security tools—particularly those involving AI/ML—in a way that provides realistic environments and where we can control the experiments to determine the strengths and weaknesses of the tools. We have designed in the ability to repeat the evaluations, so additional tools can be evaluated and compared at a later time. The system is one that can be scaled up or down for experiment sizes. At the time of the conference we will have completed two full-scale, national, government challenges on this range. These challenges are evaluating the performance and operating costs for AI/ML-based cyber security tools for application into large, government-sized environments. These evaluations will be described, in order to provide motivation and context for various design decisions and adaptations we have made. The first challenge measured end-point security tools against 100K malware samples chosen across a range of types. The second is network detection of attempted penetration and exploitations with varying levels of covertness in a high-volume, business network. The scale of each of these challenges is requiring us to create automation systems to repeat the experiments identically for each tool. Preventing there being easy signs of malicious activity for the AI/ML tools to focus on has been a particularly interesting and challenging aspect of designing and executing these challenge events. After the events, the range continues to be used for other research such as adversarial machine learning where the repeatability, scale, and automation required for the national challenge events become essential elements for research.

Nichols, Jeff↗

Modifying Frank–Kasper Mesophases by Modulating Chain Configuration in PDMS- b -PTFEA Copolymers

The common spherical mesophases observed from chemically distinct compounds have promoted extensive studies of packing structures in soft-matter self-assemblies. In this report we present a new approach for controlling sphere-packing phases by modulating homologous copolymer chain configurations. To this end, three sets of sample pairs, compositionally asymmetric polydimethylsiloxane-b-poly(2,2,2-trifluoroethyl acrylate) (PDMS-b-PTFEA) diblock copolymers (diBCPs) and their homologues containing the corresponding triblock copolymer (triBCP), are synthesized via atom transfer radical polymerization and designed with the consistent volume fractions of the core-forming PTFEA block, f PTFEA = 0.20, 0.18, and 0.15. We identify the formation of C15 and hexagonally close-packed (HCP) phases in the triBCP-containing PDMS-b-PTFEAs, whereas the sigma and C14 phases are formed in their diBCP analogues, respectively. These phase shifts into C15 and HCP, due to molecular configuration differences, reveal a significant yet unrealized role of chain configurations and the associated chain size effects in determining the stable sphere-packing phases in BCP systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of Molecular Size on Resolution in Charge Detection Mass Spectrometry

Instrumental resolution of Fourier transform-charge detection mass spectrometry instruments with electrostatic ion trap detection of individual ions depends on the precision with which ion energy is determined. Energy can be selected using ion optic filters or from harmonic amplitude ratios (HARs) that provide Fellgett’s advantage and eliminate the necessity of ion transmission loss to improve resolution. Unlike the ion energy-filtering method, the resolution of the HAR method increases with charge (improved S/N) and thus with mass. An analysis of the HAR method with current instrumentation indicates that higher resolution can be obtained with the HAR method than the best resolution demonstrated for instruments with energy-selective optics for ions in the low MDa range and above. However, this gain is typically unrealized because the resolution obtainable with molecular systems in this mass range is limited by sample heterogeneity. Here, this phenomenon is illustrated with both tobacco mosaic virus (0.6–2.7 MDa) and AAV9 (3.7–4.7 MDa) samples where mass spectral resolution is limited by the sample, including salt adducts, and not by instrument resolution. Nevertheless, the ratio of full to empty AAV9 capsids and the included genome mass can be accurately obtained in a few minutes from 1× PBS buffer solution and an elution buffer containing 300+ mM nonvolatile content despite extensive adduction and lower resolution. Empty and full capsids adduct similarly indicating that salts encrust the complexes during late stages of droplet evaporation and that mass shifts can be calibrated in order to obtain accurate analyte masses even from highly salty solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sub-Nanometer Nanoclusters of Copper Atop Single-Atom Copper Moieties toward Electrochemical CO 2 Hydrogenation to Methane

The electrochemical CO 2 reduction (eCO 2 R) offers a compelling route for converting CO 2 into value-added fuels and chemicals. Among CO 2 -derived products, methane (CH 4 ) occupies a distinct position, serving both as a key intermediate for emerging cascade electro-oxidation to oxygenates and as a strategically important extraterrestrial fuel that can be generated in situ from off-planet CO 2 resources. Although Cu-based catalysts capable of selectively producing CH 4 have been reported, they seldom sustain high selectivity at practically relevant current densities. Here, we created a single-step co-pyrolysis strategy toward generating and anchoring Cu sub-nanometer clusters (Cu SNC ) atop Cu-N x single-atom (SA) motifs embedded within N-doped carbon (NC), with controllable nanostructures through tuning of the synthesis parameters. Complementary spectroscopic analyses and density functional theory (DFT) calculations help reveal a structure−activity correlation that could guide the catalyst design. The Cu SNC @NC sample synthesized at 550 °C pyrolysis temperature (best described and modeled as Cu 3 -CuN 4 domains) represents the most effective combination of cluster size, metal-nitrogen coordination, and adsorption energetics needed to selectively promote CH 4 generation versus other eCO 2 R products. Incorporating pulsed electrolysis and hydrophobicity-modulated transport tuning at the triple-phase boundary (TPB) further enhanced CH 4 production achieving a partial CH 4 current density of ∼321 mA cm −2 , 53% Faradaic efficiency (FECH 4 ), and less than 4% combined FE for other eCO 2 R products, simplifying downstream CH 4 purification or upgrading. This work establishes generalizable principles for controlling Cu cluster atomicity and metal−nitrogen coordination, both of which are recognized determinants of CH 4 -efficient eCO 2 R.

CH4 production↗

Effects of Carbonic Acid-Rock Interactions on CO2/Brine Multiphase Flow Properties in the Upper Minnelusa Sandstones

Summary Carbon dioxide (CO2) injection into a deep saline aquifer can dissolve into formation brine and generate carbonic acid. The resulting acid can drive fluid-rock geochemical reactions. The impact of these fluid-rock geochemical reactions on porosity, permeability, and multiphase flow responses is relevant to the determination of CO2 storage capacity of deep saline aquifers. In this research, carbonic acid flooding experiments were performed on core samples consisting of poorly sorted, quartz-rich sand with laminated bedding from a possible CO2 storage target in northwest Wyoming. Complementary pre- and post-injection porosity and permeability, thin-section, Brunauer-Emmett-Teller (BET) surface area, mercury intrusion capillary pressure (MICP), and time-domain nuclear magnetic resonance (TD-NMR) measurements were conducted. Overall, both core porosity and permeability increased after a 7-day carbonic acid injection, from 6.2 to 8.4% and 1.6 to 3.7 md, respectively. We attributed these changes to carbonate mineral dissolution, which was evidenced by the effluent brine geochemistry, pore-throat size distribution (PTSD), and BET surface area. To be more specific, within the more-permeable section of core samples containing larger pore size, the permeability increment is apparent due to dolomite mineral grains and cements dissolution. However, for the lower-permeability section corresponding to the smaller pore size, mineral precipitation possibly lessened dissolution effects, leading to insignificant petrophysical properties changes. Consequently, the observed heterogeneous carbonic acid-rock interactions resulted in alterations of CO2/brine relative permeability (i.e., the initial CO2 saturation decreased and the CO2 flow capacity was enhanced). This research provides a fundamental understanding regarding effects of fluid-rock reactions on changes in static and multiphase flow properties of eolian sandstones, which lays the foundation for more accurate prediction/simulation of CO2 injection into deep saline aquifers.

Engineering↗

Establishing the accuracy of position–specific carbon isotope analysis of propane by GC–pyrolysis–GC–IRMS

Rationale: Position-specific (PS) δ 13 C values of propane have proven their ability to provide valuable information on the evolution history of natural gases. Two major approaches to measure PS δ 13 C values of propane are isotopic 13 C nuclear magnetic resonance (NMR) and gas chromatography-pyrolysis-gas chromatography-isotope ratio mass spectrometry (GC-Py-GC-IRMS). Measurement accuracy of the isotopic 13 C NMR has been verified, but the requirements of large sample size and long experimental time limit its applications. GC-Py-GC-IRMS is a more versatile method with a small sample size, but its accuracy has not been demonstrated. Methods: We measured the PS δ 13 C values of propane from nine natural gases using both 13 C NMR and GC-Py-GC-IRMS, then evaluated the accuracy of the GC-Py-GC-IRMS method. Results: The results show that large carbon isotope fractionations occurred for both terminal and central carbons within propane during pyrolysis. The isotope fractionations during the pyrolysis are reproducible at optimum conditions, but vary between the two GC-Py-GC-IRMS systems tested, affected by experimental conditions (e.g., pyrolysis temperature, flow rate, and reactor conditions). Conclusions: It is necessary to evaluate and calibrate each GC-Py-GC-IRMS system using propane gases with accurately determined PS δ 13 C values. Finally, this study also highlights a need for PS isotope standards for propane and other molecules (e.g., butane and acetic acid).

03 NATURAL GAS↗

Ruthenium solubility and its impact on the crystallization behavior and electrical conductivity of MoO 3 -containing borosilicate-based model high-level nuclear waste glasses

The present study focuses on investigating the solubility of RuO 2 in a borosilicate-based model high-level waste glass and understanding its impact on the crystallization behavior and electrical conductivity of the resulting vitrified waste forms. The solubility limit of RuO 2 in the investigated glass composition has been determined to be 460 ppm by weight. The higher concentration of RuO 2 results in sub-micron sized Ru-rich inclusions in the glassy matrix, which eventually agglomerate to form needle-like and polyhedral RuO 2 crystals. It is observed that RuO 2 selectively promotes the crystallization of the rare-earth apatite phase over the powellite phase. The as-synthesized RuO 2 -containing glasses exhibit semiconducting behavior with a similar level of electrical conductivity below the glass transition. Here, the percolation of non-uniformly distributed RuO 2 inclusions may result in a formation of short-range low-resistive conduction pathways in the host glass matrix leading to an apparent metallic-like behavior of selected thin samples with the highest ruthenium content.

36 MATERIALS SCIENCE↗

Mini-Micropulse Lidar data from TAMU TRACER campaign in the Houston TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (mini-MPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. The mini-MPL deployed with ROAM-V is a 532 nm elastic and polarization lidar. The mini-MPL outputs normalized relative backscatter (NRB) derived from raw signal after after-pulse, overlap, and dead-time correction calibration. The depolarization ratio is calculated from the co-polarized and cross-polarized NRB (Flynna et al., 2007). The NRB and depolarization ratio data are resampled from the original data at 1-minute intervals. The vertical resolution of the mini-MPL data is 15 meters. The mini-MPL data can be used to determine the boundary layer, cloud top, and cloud bottom height and can be used to retrieve aerosol type and concentration profile. This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu . Flynna, C. J., Mendozaa, A., Zhengb, Y., & Mathurb, S. (2007). Novel polarization-sensitive micropulse lidar measurement technique. Optics express, 15(6), 2785-2790.

54 ENVIRONMENTAL SCIENCES↗

Structural incorporation into goethite fractionates rare earth elements

Up to 20% of rare earth elements (REEs) in ion adsorption deposits (IADs) are associated with iron oxide minerals, primarily goethite. Often termed “non-extractable”, goethite-hosted REEs are thought to be structurally incorporated into the mineral lattice. The large mismatch in size and charge density between REEs (ionic radius, r = 0.86–1.03 Å) and Fe 3+ (r = 0.65 Å), however, makes direct substitution energetically unfavorable. To determine REE compatibility with and incorporation into goethite on the atomic level, we used X-ray pair distribution function analysis (PDF) and LIII-edge extended X-ray absorption fine structure (EXAFS) spectroscopy. The compatibility of REEs with goethite and the precursor ferrihydrite (FH) is Lu ≥ Yb ≫ Dy > Nd for both phases. Nd and Dy primarily form secondary amorphous phases, with <30% Nd and Dy incorporated into goethite. In the FH precursor at pH 6.8, Yb and Lu assumed a local REE-OOH like structure with next nearest neighbor Fe. The Yb, Lu, and Nd-FH samples were also matured at ambient conditions for 100 days; despite the presence of only ∼5% goethite, Lu and Yb were 42% and 100% in goethite-like structural environments, respectively, whereas the PDF and EXAFS of Nd showed little evidence of any incorporation. Using ab initio molecular dynamics (AIMD) to model the EXAFS, we determined the presence of protonated Fe vacancies, edge-sharing with structural Lu and Yb, likely helped accommodate these REEs in the goethite structure. Incorporation into Fe oxyhydroxides thus potentially fractionates the REEs during weathering associated with formation of lateritic and ion adsorption deposits.

Mergelsberg, Sebastian T. [Pacific Northwest Natio↗

HIPASS study of southern ultradiffuse galaxies and low surface brightness galaxies

ABSTRACT We present results from an H i counterpart search using the HI Parkes All Sky Survey (HIPASS) for a sample of low surface brightness galaxies (LSBGs) and ultradiffuse galaxies (UDGs) identified from the Dark Energy Survey (DES). We aimed to establish the redshifts of the DES LSBGs to determine the UDG fraction and understand their properties. Out of 409 galaxies investigated, none were unambiguously detected in H i. Our study was significantly hampered by the high spectral rms of HIPASS and thus in this paper we do not make any strong conclusive claims but discuss the main trends and possible scenarios our results reflect. The overwhelming number of non-detections suggest that (a) Either all the LSBGs in the groups, blue or red, have undergone environment aided pre-processing and are H i deficient or the majority of them are distant galaxies, beyond the HIPASS detection threshold. (b) The sample investigated is most likely dominated by galaxies with H i masses typical of dwarf galaxies. Had there been Milky Way (MW) size (Re) galaxies in our sample, with proportionate H i content, they would have been detected, even with the limitations imposed by the HIPASS spectral quality. This leads us to infer that if some of the LSBGs have MW-size optical diameters, their H i content is possibly in the dwarf range. More sensitive observations using the SKA precursors in future may resolve these questions.

Zhou, Yun-Fan↗

Mechanisms of Retention and Transport of Fission Products in Virgin and Irradiated Nuclear Graphite

To fulfill the design and licensing requirements for advanced reactors, the U.S. Department of Energy (DOE) is specifically interested in targeted research to quantify the mechanisms of fission product transport and retention in graphitic grades that will likely be used in next-generation very/high temperature reactors, fluoride salt-cooled high temperature reactors and molten salt reactors. We have examined an integrated experimental-computational approach to determine the diffusivities of selected fission products – ruthenium (Ru) and silver (Ag) in five nuclear graphite grades – POCO AXF-5Q, POCO ZXF-5Q, PCEA, IG110, and NBG-18. Experimental investigation for diffusion of other fission products (iodine, cesium, and krypton) in graphite could not be carried out due to extreme evaporation due to high vapor pressure, despite several attempts incorporating various experimental schemes. Experimental investigation with irradiated graphite could not be carried out because necessary approval to transport irradiated graphite could not be obtained due to procedural reasons at ORNL and national policy change in UK. An effort was made to “produce” by ion sputtering, but it was discontinued because the outcome did not adequately represent irradiated graphite. Thin film and “cup-and-cap” methods were employed to deposit fission products, diffusion annealed were carried out in an argon atmosphere, and concentration profiles were determined by dynamic secondary ion mass spectroscopy depth profiling technique. Regardless of graphite type, anomalous diffusion behavior of Ru (i.e., lower than expected based on Arrhenius temperature dependence) at an intermediate temperature, around 600 to 700 °C, was observed. Diffusion behavior of silver on the other hand agreed well to the Arrhenius temperature dependence although the excessive evaporation of silver hampered the accurate determination of diffusivities at temperature higher than 900 °C. In general, silver was observed to diffuse faster than Ru in the temperature range compared from 500 to 900 °C, had consistently had higher pre-exponential factor corresponding to higher jump frequency. To understand the abnormal diffusional behavior of Ru in graphite in intermediate temperature range, a detailed microstructural analysis was carried out. Clustering of Ru into particles on the surface of graphite was observed around 700 °C corresponding to de-wetting and spheroidization. This change would influence the boundary condition of diffusion, although features of clustering was much smaller (<1 mm) than the SIMS raster size (120 x 120 mm). Raman spectroscopy also demonstrated that Raman peak intensity for Ru decreased significantly for samples annealed higher than 700 °C and presence of Ru in graphite altered the crystallinity of graphite. To further elucidate the abnormal diffusion behavior observed in intermediate temperature investigated, the vibrational properties of graphene, bilayer graphene and Kr atoms in bilayer graphene were investigated with molecular dynamics. Krypton, which is a fission product, was introduced between a bilayer graphene system to evaluate (i) whether the phonon dispersion curves change with high temperature in bilayer graphene (ii) whether the addition of Kr atoms between the bilayer introduces any significant change in the vibrational properties, and (iii) whether any change in the vibrational properties can be correlated to the diffusive behavior of Kr atoms. The results show that the Kr atoms indeed exhibit an anomalous diffusive behavior at 550°C. Phonon analysis shows that a few phonon frequencies are enhanced as much as 20 to 30 % with the addition of just 0.2 at.% Kr. So, this may explain the unexpected self-diffusivity of fission products.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantile-specific heritability of sibling leptin concentrations and its implications for gene-environment interactions

“Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., leptin) is high or low relative to its distribution. Leptin concentrations are strongly related to adiposity, whose heritability is quantile dependent. Whether inheritance of leptin concentrations is quantile dependent, and whether this explains the greater heritability in women than men in accordance with their greater adiposity, and explains other gene-environment interactions, remains to be determined. Therefore, leptin and leptin receptor concentrations from 3068 siblings in 1133 sibships from the Framingham Heart Study Third Generation Cohort were analyzed. Free leptin index (FLI) was calculated as the ratio of leptin to soluble leptin receptor concentrations. Full-sib (β FS ) regression slopes were robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. The analyses showed β FS increased significantly with increasing percentiles of the offspring’s age- and sex-adjusted leptin distribution (P linear = 0.0001), which was accelerated at the higher concentrations (P quadratic = 0.0003). β FS at the 90th percentile (0.418 ± 0.066) was 4.7-fold greater than at the 10th percentile (0.089 ± 0.032, P difference = 3.6 × 10 –6 ). Consistent with quantile-dependent expressivity, the β FS was greater in female sibs, which was attributable to their higher leptin concentrations. Reported gene-environment interactions involving adiposity and LEP , LEPR , MnSOD , PPARγ , PPARγ2 , and IRS-1 polymorphisms were consistent with quantile-dependent expressivity of leptin concentrations. β FS for leptin receptor concentrations and free leptin index also increased significantly with increasing percentiles of their distributions (P linear = 0.04 and P linear = 8.5 × 10 –6 , respectively). In conclusion, inherited genetic and shared environmental effects on leptin concentrations were quantile dependent, which likely explains male–female differences in heritability and some gene-environment interactions.

59 BASIC BIOLOGICAL SCIENCES↗

SpeckleNN: a unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature. Classifying SPI scattering patterns, or `speckles', to extract single-hits that are needed for real-time vetoing and three-dimensional reconstruction poses a challenge for high-data-rate facilities like the European XFEL and LCLS-II-HE. Here, we introduce SpeckleNN, a unified embedding model for real-time speckle pattern classification with limited labeled examples that can scale linearly with dataset size. Trained with twin neural networks, SpeckleNN maps speckle patterns to a unified embedding vector space, where similarity is measured by Euclidean distance. We highlight its few-shot classification capability on new never-seen samples and its robust performance despite having only tens of labels per classification category even in the presence of substantial missing detector areas. Without the need for excessive manual labeling or even a full detector image, our classification method offers a great solution for real-time high-throughput SPI experiments.

47 OTHER INSTRUMENTATION↗

Quantile-dependent expressivity of plasma adiponectin concentrations may explain its sex-specific heritability, gene-environment interactions, and genotype-specific response to postprandial lipemia

“Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. adiponectin) is high or low relative to its distribution. We have previously shown that the heritability ( h 2 ) of adiposity, lipoproteins, postprandial lipemia, pulmonary function, and coffee and alcohol consumption are quantile-specific. Whether adiponectin heritability is quantile specific remains to be determined. Plasma adiponectin concentrations from 4,182 offspring-parent pairs and 1,662 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (β OP , h 2 = 2 β OP /(1 + r spouse )) and full-sib regression slopes ( β FS , h 2 = {(1 + 8r spouse β FS ) 0.05 -1}/(2r spouse )) were robustly estimated by quantile regression with nonparametric significance assigned from 1,000 bootstrap samples. Quantile-specific h 2 (± SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted adiponectin distribution when estimated from β OP ( P trend = 2.2 × 10 -6 ): 0.30 ± 0.03 at the 10th, 0.33 ± 0.04 at the 25th, 0.43 ± 0.04 at the 50th, 0.55 ± 0.05 at the 75th, and 0.57 ± 0.08 at the 90th percentile, and when estimated from β FS (P trend = 7.6 × 10 -7 ): 0.42 ± 0.03 at the 10th, 0.44 ± 0.04 at the 25th, 0.56 ± 0.05 at the 50th, 0.73 ± 0.08 at the 75th, and 0.79 ± 0.11 at the 90th percentile. Consistent with quantile-dependent expressivity, adiponectin’s: (1) heritability was greater in women in accordance with their higher adiponection concentrations; (2) relationships to ADIPOQ polymorphisms were modified by adiposity in accordance with its adiponectin-lowering effect; (3) response to rosiglitazone was predicted by the 45T> G ADIPOQ polymorphism; (4) difference by ADIPOQ haplotypes increased linearly with increasing postprandial adiponectin concentrations. Adiponectin heritability is quantile dependent, which may explain sex-specific heritability, gene-environment and gene-drug interactions, and postprandial response by haplotypes.

Postprandial↗

Multiplexed Probing for Functional Capacity Measurements in Complex and Limited-Size Samples

A new strategy using glass as a solid support for functionalization with chemical probes has been recently developed with successful results. The next step in glass functionalization is to pair chemical probes with fluorescent glass microspheres. This approach gives us a way to directly quantify probe-bound protein using Fluorescence-Activated Cell Sorting (FACS). FACS has already shown to be amendable to glass microspheres, demonstrating changes in probe-bound protein concentration. Suitable probing conditions for gram-positive and negative microbes, complex microbial communities from myriad ecosystems, and eukaryotic cells/tissues have traditionally suffered from set-backs, such as limited protein per sample and conditions atypical for probing. To remedy this, we propose to: (1) Demonstrate probe functionalization specific to glass microspheres by paired fluorophore and use those activity probes successfully with proteomics. Probes that are currently available (CYP5, GSH/GST, Glycoside Hydrolase) can be easily prepared onto glass surfaces. Probe-bound microspheres can be tested in ratios, first with known amounts of purified protein and then complex microbiome lysates. (2) Our validated microspheres are then used to determine quantitative amounts of protein through FACS sorting. Complimenting these results by proteomics, prepared microspheres are then optimized and condensed into a user-friendly kit. Once successfully commercialized, this multiplexed assay can be used with little to no technical expertise, making this available to various industries users.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of measuring thermal conductivity of isotropic and anisotropic thermally insulating materials by transient plane source (Hot Disk) technique

The transient plane source (TPS) technique, also referred as the Hot Disk method, has been widely used due to its ability to measure the thermal properties of an extensive range of materials (solids, liquids, and powder). Recently, it has been recognized that typical Hot Disk sensors can influence TPS results of thermally insulating materials and lead to an overestimation of thermal conductivity. Although improvements have been proposed, they have not yet been implemented in the commercial TPS, leaving researchers with non-standardized modifications or options provided by a commercial Hot Disk apparatus. An empirical study of thermally insulating materials such as extruded polystyrene (XPS) and aerogel blanket is conducted in order to address the factors that affect the reliability of thermal conductivity k obtained using the commercial TPS apparatus. Sensor size, input power, duration of the measurements, applied pressure, and, in the case of anisotropic materials, heat capacity are investigated, and the results are compared with those using a Heat Flow Meter apparatus. The effect of sensor size on the k value is ascribed to heat loss through connecting leads and is more pronounced in smaller sensors and in materials with lower k values . In the case of XPS and aerogel, the effect becomes minimal for sensors with a radius r ≥ 6.4 mm. The low input power yields a high scattering of the results and should be avoided. Applied contact pressure and the tested region of the specimen play an important role in experiments with low-density fibrous materials due to the large percentage of heat being transferred by radiation and the heterogeneous nature of the samples, respectively. Additionally, the sensitivity of anisotropic measurements to the value of the material’s volumetric heat capacity ( ρC p ) is shown, emphasizing the need for the precise determination.

thermal conductivity↗

On the feasibility of using physics-informed machine learning for underground reservoir pressure management

In this work, we evaluate the feasibility of using physics-informed machine learning (PIML) for underground energy-related pressure management. To this end, we develop a PIML framework to manage underground reservoir pressures by training neural networks to determine fluid extraction rates for dedicated extraction wells during fluid injection operations given a range of reservoir conditions (e.g., transmissivity and storativity). We implement an automatically-differentiable analytical physics model of fluid flow in porous media within the PIML framework as a proxy for more complicated models. This allows us to execute a sufficient number of training scenarios to fully evaluate the feasibility of using PIML to support pressure management activities. We quantify the number of physics-model parameters required for automatic differentiation to become more efficient than finite-difference gradient calculations. We use a simple scenario with a single injector, extractor, and critical location for our feasibility analysis. We evaluate the effect of the size of the training dataset (i.e., the number of reservoir condition samples) on the accuracy and efficiency of the PIML framework. For an equivalent number of model evaluations, the larger training dataset took less time to train and produced a neural network that was able to more accurately manage reservoir pressures. We also evaluate the effect of the training dataset batch size (i.e., number of reservoir condition samples used to update the neural network coefficients during training; i.e., how the training dataset is partitioned). While training ran faster with larger batch sizes, they produced neural networks that managed pressures less accurately. We demonstrate the approach on a more complex scenario involving 10 injectors, 10 extractors, and 4 critical locations (a relatively high well density of 20 wells/km2). We provide the number of forward and adjoint model evaluations required in each case as an indication of the feasibility of using PIML for pressure management when more complicated physics models with longer execution times are used.

54 ENVIRONMENTAL SCIENCES↗

Fixed-target serial femtosecond crystallography using in cellulo grown microcrystals

The crystallization of recombinant proteins in living cells is an exciting new approach in structural biology. Recent success has highlighted the need for fast and efficient diffraction data collection, optimally directly exposing intact crystal-containing cells to the X-ray beam, thus protecting the in cellulo crystals from environmental challenges. Serial femtosecond crystallography (SFX) at free-electron lasers (XFELs) allows the collection of detectable diffraction even from tiny protein crystals, but requires very fast sample exchange to utilize each XFEL pulse. Here, an efficient approach is presented for high-resolution structure elucidation using serial femtosecond in cellulo diffraction of micometre-sized crystals of the protein HEX-1 from the fungus Neurospora crassa on a fixed target. Employing the fast and highly accurate Roadrunner II translation-stage system allowed efficient raster scanning of the pores of micro-patterned, single-crystalline silicon chips loaded with living, crystal-containing insect cells. Compared with liquid-jet and LCP injection systems, the increased hit rates of up to 30% and reduced background scattering enabled elucidation of the HEX-1 structure. Using diffraction data from only a single chip collected within 12 min at the Linac Coherent Light Source, a 1.8 Å resolution structure was obtained with significantly reduced sample consumption compared with previous SFX experiments using liquid-jet injection. This HEX-1 structure is almost superimposable with that previously determined using synchrotron radiation from single HEX-1 crystals grown by sitting-drop vapour diffusion, validating the approach. This study demonstrates that fixed-target SFX using micro-patterned silicon chips is ideally suited for efficient in cellulo diffraction data collection using living, crystal-containing cells, and offers huge potential for the straightforward structure elucidation of proteins that form intracellular crystals at both XFELs and synchrotron sources.

Lahey-Rudolph, J. Mia (ORCID:0000000152797267)↗