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At least 181 records · Page 10

Designing Antifouling and Antimicrobial Interfaces: Structural Characterization using CryoEM, Automated Microscopy, and AI Image Segmentation

The design of functionalized surfaces for interactions with biological systems is critical across sectors such as healthcare, energy, and agriculture. Tailoring materials for specific applications, such as antifouling and antimicrobial surfaces, demands a comprehensive understanding of topology and chemistry across multiple length and time scales on both biological and materials systems. This work presents the development and characterization of nanostructured surfaces with controlled topographies and chemistries that enhance bacterial membrane disruption, reduce biofilm formation, and improve antimicrobial and antifouling capabilities. Two specific use cases will be presented - the use of cellulose nanocrystals (CNCs) for bacterial growth inhibition and the development of antifouling surfaces to prevent protein and bacterial adsorption [1-4]. By leveraging large language models (LLMs) for image segmentation and training [5], we enable automated analysis of terabyte-scale cryogenic electron microscopy (cryoEM) datasets. This analysis provides statistical insights into the biotic/abiotic interface and facilitates automated electron microscopy experiments to mitigate time and dose. The integration of cryogenic electron tomography (cryoET) and cryogenic focused ion beam (cryoFIB) milling enables high-resolution, near-native-state imaging and 3D reconstructions of bio/material interfaces [6]. Orthogonal characterization techniques and computational modeling further enhances our understanding, offering a robust platform for the design and optimization of next-generation functional surfaces [7].

Williams, Alexis [ORNL] (ORCID:0000000252835822)↗

Development of a Gas Chromatography with High-Resolution Time-of-Flight Mass Spectrometry Methodology for BDNPA/F

Analysis of thermally labile compounds such as bis(2,2-dinitropropyl) acetal/formal (BDNPA/F), an energetic plasticizer, is usually performed via liquid chromatography (LC) as opposed to gas chromatography (GC) due to thermal decomposition in the inlet or the analytical column. While LC is a powerful technique, the analysis of volatile and semivolatile compounds is best suited to GC. Herein, a method was developed for a gas chromatograph coupled to high-resolution mass spectrometer (GC-HRMS), utilizing a programmable temperature vaporizer (PTV) inlet. A subset of the native compounds and several produced by the thermal decomposition of BDNPA/F in the inlet were evaluated by using multiple PTV inlet parameters to determine the optimal ramp rate and final temperature of the inlet (60 °C/min from 60 to 325 °C). The optimized GC-HRMS method nearly reduced all thermal decomposition, allowing for an excellent separation to be obtained. Furthermore, multiple ionization methods, including electron impact (EI), negative chemical ionization (NCI), and positive chemical ionization (PCI), were used to explore the many chemical differences between the BDNPA/F samples. A preliminary investigation of the benefits of using GC-HRMS to evaluate the chemical differences between unaged and aged BDNPA/F samples for unique insight was evaluated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hypernetwork science via high-order hypergraph walks

We propose high-order hypergraph walks as a framework to generalize graph-based network science techniques to hypergraphs. Edge incidence in hypergraphs is quantitative, yielding hypergraph walks with both length and width. Graph methods which then generalize to hypergraphs include connected component analyses, graph distance-based metrics such as closeness centrality, and motif-based measures such as clustering coefficients. We apply high-order analogs of these methods to real world hypernetworks, and show they reveal nuanced and interpretable structure that cannot be detected by graph-based methods. Lastly, we apply three generative models to the data and find that basic hypergraph properties, such as density and degree distributions, do not necessarily control these new structural measurements. Our work demonstrates how analyses of hypergraph-structured data are richer when utilizing tools tailored to capture hypergraph-native phenomena, and suggests one possible avenue towards that end.

97 MATHEMATICS AND COMPUTING↗

Water Mass Transformation Budgets in Finite‐Volume Generalized Vertical Coordinate Ocean Models

Water Mass Transformation (WMT) theory provides conceptual tools that in principle enable innovative analyses of numerical ocean models; in practice, however, these methods can be challenging to implement and interpret, and therefore remain under-utilized. Our aim is to demonstrate the feasibility of diagnosing all terms in the water mass budget and to exemplify their usefulness for scientific inquiry and model development by quantitatively relating water mass changes, overturning circulations, boundary fluxes, and interior mixing. We begin with a pedagogical derivation of key results of classical WMT theory. We then describe best practices for diagnosing each of the water mass budget terms from the output of Finite-Volume Generalized Vertical Coordinate (FV-GVC) ocean models, including the identification of a non-negligible remainder term as the spurious numerical mixing due to advection scheme discretization errors. We illustrate key aspects of the methodology through the analysis of a polygonal region of the Greater Baltic Sea in a regional demonstration simulation using the Modular Ocean Model v6 (MOM6). We verify the convergence of our WMT diagnostics by brute-force, comparing time-averaged (“offline”) diagnostics on various vertical grids to timestep-averaged (“online”) diagnostics on the native model grid. Finally, we briefly describe a stack of xarray-enabled Python packages for evaluating WMT budgets in FV-GVC models (culminating in the new xwmb package), which is intended to be model-agnostic and available for community use and development.

54 ENVIRONMENTAL SCIENCES↗

Business Case Analysis for Digital Safety-Related Instrumentation & Control System Modernizations

The commercial nuclear sector faces unprecedented financial challenges driven by low natural gas prices and subsidized renewables in a marketplace that does not reward carbon-free baseload capacity. These circumstances, along with increasingly antiquated labor-centric operating models and analog technology, have forced the premature closure of multiple nuclear facilities and placed a much larger population of nuclear power stations at risk. Nuclear plant economic survival in current and forecasted market conditions requires an efficient and technology-centric operating model that harvests the native efficiencies of advanced technology. This is analogous to transformations in nearly every other industry. In light of previous industry experience in modernizing safety Instrumentation and Controls (I&C) systems, nuclear utilities are reluctant to pursue these upgrades due to uncertainty in licensing and cost.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Measurement of Transport Properties of Woody Biomass Feedstock Particles Before and After Pyrolysis by Numerical Analysis of X-Ray Tomographic Reconstructions

Lignocellulosic biomass has a complex, species-specific microstructure that governs heat and mass transport during conversion processes. A quantitative understanding of the evolution of pore size and structure is critical to optimize conversion processes for biofuel and bio-based chemical production. Further, improving our understanding of the microstructure of biochar coproduct will accelerate development of its myriad applications. This work quantitatively compares the microstructural features and the anisotropic permeabilities of two woody feedstocks, red oak and Douglas fir, using X-ray computed tomography (XCT) before and after the feedstocks are subjected to pyrolysis. Quantitative analysis of the three-dimensional (3D) reconstructions allows for direct calculations of void fractions, pore size distributions and tortuosity factors. Next, 3D images are imported into an immersed boundary based finite volume solver to simulate gas flow through the porous structure and to directly calculate the principal permeabilities along longitudinal, radial, and tangential directions. The permeabilities of native biomass are seen to differ by three to four orders of magnitude in the different principal directions, but we find that this anisotropy is substantially reduced in the biochar formed during pyrolysis. The quantitative transport properties reported here enhance the ability of pyrolysis simulations to account for feedstock-specific effects and thereby provide a useful touchstone for the biorefining community.

09 BIOMASS FUELS↗

Pore-Scale Analysis of the Permeability Damage and Recovery during Cyclic Freshwater and Brine Injection in Porous Media Containing Non-Swelling Clays

Permeability damage in subsurface porous media caused by clay mobilization is encountered in many engineering applications, such as geothermal energy, water disposal, oil recovery, and underground CO2 storage. During the freshwater injection into rocks containing brine, the sudden decrease in salinity causes native clay fines to detach and clog pore throats, leading to a significant decline in permeability. The clay fines detach due to weakened net-attractive forces binding them to each other and the grain. Past experiments link this permeability damage on the immediate history of the salinity and the direction of flow. To better understand this phenomenon, we conducted pore-scale simulations of cyclic injection of freshwater and brine into sandstone containing Kaolinite clay. Our simulations establish a link between the clay-fine trajectory and the permeability trend observed by Khilar and Fogler (1983). For a uniform clay size of 3 microns, we observe a permeability decline by two orders of magnitude during freshwater injection with respect to brine injection. Increasing salinity and simultaneously reversing flow direction restores the permeability. The permeability restoration upon reversing the brine flow direction is attributed to the unblocking of pore throats in the reverse direction by the movement of the clay particles along the grain surfaces by the hydrodynamic force and the strong net-attractive force under high salinity.

Bhuvankar, Pramod (ORCID:000000027739973X)↗

Feasibility Study on Implementing a Staggered-Grid Finite Volume Method for System Analysis Code Development Under the MOOSE Framework

Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.

MOOSE↗

Pb dimerization greatly accelerates charge losses in MAPbI 3 : Time-domain ab initio analysis

Metal halide perovskites constitute a new type of semiconducting materials with long charge carrier lifetimes and efficient light-harvesting. The performance of perovskite solar cells and related devices is limited by nonradiative charge and energy losses, facilitated by defects. Combining nonadiabatic molecular dynamics and time-domain density functional theory, we demonstrate that charge losses depend strongly on the defect chemical state. By considering an extra Pb atom in CH 3 NH 3 PbI 3 , which is a common defect in lead halide perovskites, we investigate its influence on charge trapping and recombination. In a chemically inert form as a Pb interstitial, the extra Pb atom has only a mild influence on charge recombination. However, if the extra Pb atom binds to a native Pb atom to form a dimer, the charge trapping and recombination are greatly accelerated because the Pb-dimer creates a localized midgap trap state that couples strongly to the perovskite valence band edge. Holes disappear from the valence band two orders of magnitude faster than in the pristine perovskite and recombine with conduction band electrons one order of magnitude faster. The simulations identify the phonon modes involved in the nonradiative charge trapping and recombination and highlight the importance of rapid decoherence within the electronic subsystem for long carrier lifetimes. The detailed atomistic analysis of the charge trapping and recombination mechanisms enriches the understanding of defect properties and provides theoretical guidance for improving perovskite performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of dislocation-related and point-defects in III-As layers for silicon photonics applications

Abstract The aim of this paper is to identify, analyze and compare the defects present in III-As, as a function of dislocation density, and as a function of the presence/absence of quantum dots (QDs). Such materials are of fundamental importance for the development of lasers and photodiodes for silicon photonics. The study is based on an extensive deep-level transient spectroscopy investigation, carried out on GaAs pin diodes grown on Si and on GaAs (that differ in the dislocation density), with and without embedded QDs. The original results described in this paper demonstrate that: (a) we were able to identify four different defects within the device grown on Si (three electron and one hole traps) and one defect (hole trap) in the device on GaAs, common to both samples; (b) all the majority carrier traps identified are located near midgap, i.e. are efficient non-radiative recombination centers; (c) such defects are absent (or non-detectable) in the sample grown on GaAs substrate, having a very low dislocation density; (d) the presence of QDs does not result in additional defects within the semiconductor material; (e) the analysis of the capture kinetics revealed that two of the identified traps are related to point defects, whereas the other two traps can be associated with point defects located near a dislocation; (f) a comparison with previous reports indicate that the detected traps are related to native III-As defects, or to oxygen-related complexes.

Physics↗

pvplr-python: Python package implementation of PVplr for Performance Loss Rate (PLR) analysis

Due to software fragmentation, PV system modeling teams can be limited to language specific packages, preventing cross-sectional analysis of different modeling techniques and workflows. To this end, PVplr, a popular PV performance modeling R software package, has been ported to the Python programming language. To verify and test the robustness of the port, NSRDB data has been used to simulated PV installations at native resolution (~2 million Sites), with a variety of degradation rates, degradation patterns, and modules. Performance Ratios were calculated using the ported functions from pvplr-python and compared against Rdtools YoY values. Due to the complicated nature of degradation, a new metric has been proposed to quantify the performance loss of a system. The cumulative production loss, is the total amount of energy lost due to the degrading performance of the system. Cumulative production loss alleviates the problems with fitting linear functions to non-linear degradation. Cumulative Production loss was shown to better estimate the total lost revenue for non-linear degradation patterns. $XbX + UTC$ was found to most accurately predict the total lost revenue in simulated systems.

Kumar, Suraj↗

A General Autofluorescence Method to Characterize Polymerization Progress

Abstract An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium‐catalyzed ring‐opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here‐developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst‐inhibitor‐stabilized formulations. Multiple‐well analysis demonstrated suitability for future high‐throughput evaluation of formulations for thermosets. The central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.

López, Pía A.↗

Genome-Wide Analysis of RNA Decay in the Cyanobacterium Synechococcus sp. Strain PCC 7002

ABSTRACT RNA degradation is an important process that influences the ultimate concentration of individual proteins inside cells. While the main enzymes that facilitate this process have been identified, global maps of RNA turnover are available for only a few species. Even in these cases, there are few sequence elements that are known to enhance or destabilize a native transcript; even fewer confer the same effect when added to a heterologous transcript. To address this knowledge gap, we assayed genome-wide RNA degradation in the cyanobacterium Synechococcus sp. strain PCC 7002 by collecting total RNA samples after stopping nascent transcription with rifampin. We quantified the abundance of each position in the transcriptome as a function of time using RNA-sequencing data and later analyzed the global mRNA decay map using machine learning principles. Half-lives, calculated on a per-ORF (open reading frame) basis, were extremely short, with a median half-life of only 0.97 min. Despite extremely rapid turnover of most mRNA, transcripts encoding proteins involved in photosynthesis were both highly expressed and highly stable. Upon inspection of these stable transcripts, we identified an enriched motif in the 3′ untranslated region (UTR) that had similarity to Rho-independent terminators. We built statistical models for half-life prediction and used them to systematically identify sequence motifs in both 5′ and 3′ UTRs that correlate with stabilized transcripts. We found that transcripts linked to a terminator containing a poly(U) tract had a longer half-life than both those without a poly(U) tract and those without a terminator. IMPORTANCE RNA degradation is an important process that affects the final concentration of individual mRNAs, affecting protein expression and cellular physiology. Studies of how RNA is degraded increase our knowledge of this fundamental process as well as enable the creation of genetic tools to manipulate RNA stability. By studying global transcript turnover, we searched for sequence elements that correlated with transcript (in)stability and used these sequences to guide tool design. This study probes global RNA turnover in a cyanobacterium, Synechococcus sp. strain PCC 7002, that both has a unique array of RNases that facilitate RNA degradation and is an industrially relevant strain that could be used to convert CO 2 and sunlight into useful products.

59 BASIC BIOLOGICAL SCIENCES↗

A General Autofluorescence Method to Characterize Polymerization Progress

An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium-catalyzed ring-opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here-developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst–inhibitor-stabilized formulations. Multiple-well analysis demonstrated suitability for future high-throughput evaluation of formulations for thermosets. Furthermore, the central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV- 2 main protease

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) approaches followed by experimental validation. Generative deep learning models have been recently developed that can generate thousands of new candidates, but their physiochemical properties are typically not optimized. Using our deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 M pro that preserve the core scaffold. Here we utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure–activity relationships, multi-parameter optimization, and graph neural networks on libraries of generated candidates to predict biological activity and binding affinity a priori. From these collective computational results, eight promising candidates were identified and tested experimentally using Native Mass Spectrometry (MS) and FRET-based functional assays. Two compounds, with quinazoline-2-thiol and acetylpiperidine core moiety showed IC 50 values in the low micromolar range: 2.95±0.0017 µM and 3.41±0.0015 µM, respectively. The molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations in the chain B and the interface domains of the M pro . The key fragments from these top hits can be used as input for closed loop lead optimization in the integrated pipeline.

60 APPLIED LIFE SCIENCES↗

Data for "Integrated Green Biorefinery for the Production of Anthocyanins, Fermentable Sugars, and High Pure Lignin from Miscanthus × giganteus "

Miscanthus x giganteus (Mxg) is a promising perennial crop for producing natural colorants, renewable fuels, and bioproducts. However, natural recalcitrance and high pretreatment cost are major barriers to their complete conversion. In this study, a green processing method has been investigated for efficient recovery of natural pigments (anthocyanins), fermentable sugars, and pure lignin from Mxg genotypes using choline chloride-based natural deep eutectic solvents (NADES) systems. Interestingly, choline chloride: lactic acid (ChCl: LA) NADES-processed biomass resulted in 67.8 ± 2.1 μg g−1 of anthocyanins from dry biomass. A maximum of 87.4%–94.1% glucose yield was achieved after enzymatic saccharification. The effective extraction of lignin with high purity with higher β-aryl ether (βO4) bonds from advanced crops is crucial for lignin valorization. Notably, highly pure lignin (≈93.4% ± 1.4%) is achieved after low-temperature NADES pretreatment while retaining lignin’s native structure. 31P nuclear magnetic resonance demonstrated that total phenolics for ChCl: LA-lignin resulted in 1.20 mmol g−1 hydroxyls. The relative monolignol composition of syringyl (S), guaiacyl (G), and p-hydroxyphenyl (H) is 19.0, 65.7, and 14.3%, respectively, as evidenced by heteronuclear single quantum coherence analysis. This study provides a novel approach for obtaining high-purity lignin for catalytic depolymerization for oligomers and bifunctional monoaromatics production and leverages current cellulosic biorefinery technologies.

biomass analytics↗

Integrated Green Biorefinery for the Production of Anthocyanins, Fermentable Sugars, and High Pure Lignin from Miscanthus × giganteus

Miscanthus x giganteus (Mxg) is a promising perennial crop for producing natural colorants, renewable fuels, and bioproducts. However, natural recalcitrance and high pretreatment cost are major barriers to their complete conversion. In this study, a green processing method has been investigated for efficient recovery of natural pigments (anthocyanins), fermentable sugars, and pure lignin from Mxg genotypes using choline chloride-based natural deep eutectic solvents (NADES) systems. Interestingly, choline chloride: lactic acid (ChCl: LA) NADES-processed biomass resulted in 67.8 ± 2.1 μg g –1 of anthocyanins from dry biomass. A maximum of 87.4%–94.1% glucose yield was achieved after enzymatic saccharification. The effective extraction of lignin with high purity with higher β-aryl ether (β—O—4) bonds from advanced crops is crucial for lignin valorization. Notably, highly pure lignin (≈93.4% ± 1.4%) is achieved after low-temperature NADES pretreatment while retaining lignin's native structure. 31 P nuclear magnetic resonance demonstrated that total phenolics for ChCl: LA-lignin resulted in 1.20 mmol g –1 hydroxyls. The relative monolignol composition of syringyl (S), guaiacyl (G), and p-hydroxyphenyl (H) is 19.0, 65.7, and 14.3%, respectively, as evidenced by heteronuclear single quantum coherence analysis. This study provides a novel approach for obtaining high-purity lignin for catalytic depolymerization for oligomers and bifunctional monoaromatics production and leverages current cellulosic biorefinery technologies.

Raj, Tirath [University of Illinois at Urbana-Cham↗

Revisiting heat treatment and surface activation of GaAs photocathodes: In situ studies using scanning tunneling microscopy and photoelectron spectroscopy

The lifetime of GaAs photocathodes in polarized electron guns is limited due to the delicate activation layer. An atomically clean and smooth GaAs surface is needed to deposit a robust activation layer, such as Cs 2 Te, with longer lifetime compared to traditional (Cs,O) activation. A previous experiment with Cs 2 Te activation on GaAs used heat cleaning temperatures around 400°C to avoid an increase in surface roughness [Bae et al., Appl. Phys. Lett. 112, 154101 (2018)]. Furthermore, high-temperature heat cleaning around 580°C, which results in a relatively contamination-free surface, could be one possible way to improve quantum efficiency. However, one should be cautious about surface roughness degradation during high-temperature heat cleaning. In this paper, we report results of surface roughness measurements on native, heat cleaned, and (Cs,O) activated GaAs photocathodes under vacuum. The results, measured by ultrahigh vacuum scanning tunneling microscopy, show that the surface roughness improves as the heat cleaning temperature is increased, by at least a factor of three for 580°C heat cleaning, compared to the native sample. Activation with (Cs,O) is shown to increase surface roughness by a factor of four compared to a 580°C heat cleaned sample. This confirms that high-temperature heat cleaning can be useful for depositing good quality robust activation layers on GaAs. Additionally, we also report chemical analysis for each step of preparation for p-doped GaAs photocathodes using X-ray photoelectron spectroscopy (XPS), angle-resolved XPS, and ultraviolet photoelectron spectroscopy. Our results indicate that the (Cs,O) activation layer forms a sandwich structure consists of Cs and oxygen. We found no formation of any specific compound such as Cs 2 O or Cs 11 O 3 .

43 PARTICLE ACCELERATORS↗