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At least 217 records · Page 12

Environmental controls on the kinetics of iron-sulfur cluster nucleation and nanoparticle formation

Anoxic, sulfidic conditions have been prevalent since the early Proterozoic and favor aqueous iron-sulfur (FeS aq ) clusters as a major fraction of the soluble, reduced iron and sulfur pool. FeS aq cluster formation and nucleation is driven by the high affinity between ferrous iron (Fe(II)) and sulfide (HS − ), ultimately yielding particles that precipitate as iron sulfide minerals. FeS aq clusters were recently shown to be bioavailable sources of iron and sulfur for a variety of anaerobes, yet little is known of the factors that influence the kinetics of their formation and nucleation. Here we apply computational and spectroscopic approaches to investigate the dynamics of FeS aq nucleation, cluster growth, precipitation, and redissolution as a function of Fe(II)/HS − concentration, temperature, and pH. Experiments were conducted under excess HS − to mimic euxinic conditions common to contemporary anaerobic aquatic ecosystems and those of the Proterozoic. Density functional theory calculations reveal the key role of water oxygen-iron interactions in stabilizing small FeS aq clusters and promoting solubility. Dynamic light scattering revealed a concentration-dependent increase in the kinetics of FeS aq nucleation and cluster aggregation. Increasing temperature promoted FeS aq cluster nucleation and aggregation while also enhancing dissolution. Alkaline pH also promoted FeS aq nucleation and cluster aggregation. At 25 °C, pH 7.0, and at reactant concentrations of 30 µM, FeS aq clusters < 10 nm in diameter remained in solution for > 2 h. These results underscore the importance of temperature, pH, and reactant concentration in the kinetics of FeS aq nucleation and cluster growth that, in turn, influence their bioavailability in anaerobic ecosystems.

Aquatic ecosystems↗

Structural evolution of amorphous calcium sulfate nanoparticles into crystalline gypsum phase

The involvement of amorphous calcium sulfate (ACS) as a precursor to calcium sulfate crystallization remains an important but poorly understood phenomenon, especially the mechanism by which ACS evolves into crystalline phase. In this study, we captured the ACS nanoparticles as a precursor to calcium sulfate crystallization in a concentrated CaCl 2 solution at 90 °C and observed several stages of its evolution. The ACS nanoparticles grew by simultaneous fusion and internal structural evolution. Aggregation of the ACS nanoparticles gave birth to bulk ACS particles within which nanocrystalline domains sprouted and developed into crystalline gypsum. This work deepens the understanding of the evolution of ACS nanoparticles and its role in multistage crystallization of calcium sulfate.

36 MATERIALS SCIENCE↗

Deconstruction of biomass enabled by local demixing of cosolvents at cellulose and lignin surfaces

A particularly promising approach to deconstructing and fractionating lignocellulosic biomass to produce green renewable fuels and high-value chemicals pretreats the biomass with organic solvents in aqueous solution. Here, neutron scattering and molecular-dynamics simulations reveal the temperature-dependent morphological changes in poplar wood biomass during tetrahydrofuran (THF):water pretreatment and provide a mechanism by which the solvent components drive efficient biomass breakdown. Whereas lignin dissociates over a wide temperature range (>25 °C) cellulose disruption occurs only above 150 °C. Neutron scattering with contrast variation provides direct evidence for the formation of THF-rich nanoclusters (R g ∼ 0.5 nm) on the nonpolar cellulose surfaces and on hydrophobic lignin, and equivalent water-rich nanoclusters on polar cellulose surfaces. The disassembly of the amphiphilic biomass is thus enabled through the local demixing of highly functional cosolvents, THF and water, which preferentially solvate specific biomass surfaces so as to match the local solute polarity. A multiscale description of the efficiency of THF:water pretreatment is provided: matching polarity at the atomic scale prevents lignin aggregation and disrupts cellulose, leading to improvements in deconstruction at the macroscopic scale.

09 BIOMASS FUELS↗

Electrolyte Solvation and Ionic Association. VII. Correlating Raman Spectroscopic Data with Solvate Species

Raman spectroscopy is a widely utilized method for determining information about the solvate species present in electrolyte solutions. Difficulties arise, however, when interpreting the Raman data in terms of correlating the spectroscopic vibrational bands with specific solvate species. Examples are provided to demonstrate how erroneous conclusions may be drawn with regard to the identity and population (distribution) of the solvent-separated ion pair (SSIP), contact ion pair (CIP) and aggregate (AGG) solvate species frequently mentioned in the scientific literature.

contact ion pairs↗

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Residential Demand Side Aggregation of Privacy-Conscious Consumers

The increasing adoption of smart meters has led to growing concerns regarding privacy risks stemming from the high resolution measurements. This has given rise to privacy protection techniques that physically alter the consumer's energy load profile, masking private information by using localised devices, e.g. batteries or flexible loads. Meanwhile, there has also been increasing interest in aggregating the distributed energy resources (DERs) of residential consumers to provide services to the grid. In this paper, we propose an online distributed algorithm to aggregate the DERs of privacy-conscious consumers to provide services to the grid, whilst preserving their privacy. Results show that the optimisation solution from the distributed method converges to one close to the optimum computed using an ideal centralised solution method, balancing between grid service provision, consumer preferences and privacy protection. More importantly, the distributed method preserves consumer privacy, and does not require high-bandwidth two-way communications infrastructure.

ancillary services↗

Interpretable artificial intelligence and exascale molecular dynamics simulations to reveal kinetics: Applications to Alzheimer's disease

The rapid increase in computing power, especially with the integration of graphics processing units, has dramatically increased the capabilities of molecular dynamics simulations. To date, these capabilities extend from running very long simulations (tens to hundreds of microseconds) to thousands of short simulations. However, the expansive data generated in these simulations must be made interpretable not only by the investigator who performs them but also by others as well. Here, we demonstrate how integrating learning techniques, such as artificial intelligence, machine learning, and neural networks, into analysis pipelines can reveal the kinetics of Alzheimer's disease (AD) protein aggregation. Finally, we review select AD targets, describe current simulation methods, and introduce learning concepts and their application in AD, highlighting limitations and potential solutions.

59 BASIC BIOLOGICAL SCIENCES↗

Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning

In this work, we present large-scale dynamical simulations of electronic phase separation in the single-band double-exchange model based on deep-learning neural-network potentials trained from small-size exact diagonalization solutions. We uncover an intriguing correlation-induced freezing behavior as doped holes are segregated from half filled insulating background during equilibration. While the aggregation of holes is stabilized by the formation of ferromagnetic clusters through Hund’s coupling between charge carriers and local magnetic moments, this stabilization also creates confining potentials for holes when antiferromagnetic spin-spin correlation is well developed in the background. The dramatically reduced mobility of the self-trapped holes prematurely disrupts further growth of the ferromagnetic clusters, leading to an arrested phase separation. Implications of our findings for phase separation dynamics in materials that exhibit colossal magnetoresistance effect are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

BAMCensus (The Behavior and Advanced Mobility Census Dataset Aggregator) [SWR-25-120]

This software is a high-performance tool developed in Rust for downloading and processing large-scale geospatial datasets, specifically focusing on US Census data. It is designed to address scaling limitations found in existing tools, such as R's [tidycensus](https://walker-data.com/tidycensus/), by providing performant streaming dataset JOIN operations between various US Census datasets (like ACS and LEHD) and their corresponding geometries stored on the TIGER/Lines web server. The tool automates the process of joining these data sources, returning aggregated data to the user based on a specified census GEOID type. The tool automates the process of joining these data sources, returning aggregated data to the user based on a specified census GEOID type. Its primary motivation stems from the need for a high-performance solution to combine spatial datasets with graph traversals within the context of mobility analysis tooling being developed at NREL's Behavior and Advanced Mobility (BAM) group.

Fitzgerald, Robert [National Renewable Energy Labo↗

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Comparing the Effects of Side Chain Dipole–Dipole Interactions and Hydrogen Bonding on the Mechanical and Electrical Properties of Poly(3-hexylthiophene)

Poly(3-alkylthiophenes) are simple conjugated polymers with good electrical properties, but tend to be brittle, limiting their application. Here, we investigate how side chain modifications can improve their toughness without compromising their charge transport. Specifically, we compare a weak dipole–dipole interaction of ester groups with a stronger hydrogen-bonding interaction of the hydroxyl groups. Two copolymers with targeted 5 and 10 mol % ester-functionalized side chains were synthesized and hydrolyzed in the solid state to introduce hydroxyl groups. Both hydrolyzed polymers became insoluble in most organic solvents, providing a path to layer-by-layer solution processing. All polymers’ optical, thermal, structural, electrical, and mechanical properties were investigated. Optical spectroscopy revealed that functionalization at these low levels did not significantly affect aggregation or π–π stacking. Differential scanning calorimetry indicated reduced crystallinity in the functionalized copolymers compared to that of P3HT. Grazing-incidence wide-angle X-ray diffraction data showed that functionalization led to an increase in lamellar spacing without altering molecular orientation or π–π stacking. Mechanical testing highlighted that at the lower functionalization level, both ester and hydroxyl groups similarly enhanced toughness, suggesting that disorder, rather than the specific nature of the functional group, was responsible for these improvements. At the higher functionalization level, hydroxyl groups significantly increased the elastic modulus while also negatively impacting charge carrier mobility. This study suggests that with stronger hydrogen-bonding groups, only very small amounts can improve P3HT’s toughness. For a wider tunable range, it may be a better strategy to use weak interactions such as dipole–dipole interactions of ester groups.

36 MATERIALS SCIENCE↗

Polyvinyl acetate-based polymer host for optical and far-infrared spectroscopy of individualized nanoparticles

Preparation techniques for producing films of individualized solution-dispersed nanoparticles (NPs) for optical spectroscopy are frequently technically challenging and tailored for a specific NP system. In this work, we present a rapid, easy, and economical technique for producing polyvinyl acetate (PVAc)-based NP-polymer films on the order of 100’s of micrometers thick that exhibit high uniformity, low aggregation, excellent optical transparency, and low terahertz absorption. In addition, we find that these films are robust at cryogenic temperatures and have a high laser damage threshold of 0.3 TW cm –2 , which make them suitable for pulsed laser measurements. We show that free-standing, flexible, PVAc films can incorporate both one-dimensional single-wall carbon nanotubes (SWCNTs) and zero-dimensional Au NPs. Using absorbance, Raman scattering, and photoluminescence excitation spectroscopy, we observe that SWCNT individualization is maintained, and minimized polymer strain imposed, when the nanotubes are transitioned from the solution to the polymer host. This PVAc-based polymer host presents researchers with a straightforward method for producing free-standing and flexible NP films with low aggregation.

36 MATERIALS SCIENCE↗

Chain conformations and phase separation in polymer solutions with varying solvent quality

Molecular dynamics simulations are used to investigate the conformations of a single polymer chain, represented by the Kremer-Grest bead-spring model, in a solution with a Lennard-Jones liquid as the solvent when the interaction strength between the polymer and solvent is varied. Results show that when the polymer-solvent interaction is unfavorable, the chain collapses as one would expect in a poor solvent. For more attractive polymer-solvent interactions, the solvent quality improves and the chain is increasingly solvated and exhibits ideal and then swollen conformations. However, as the polymer-solvent interaction strength is increased further to be more than about twice the strength of the polymer-polymer and solvent-solvent interactions, the chain exhibits an unexpected collapsing behavior. Correspondingly, for strong polymer-solvent attractions, phase separation is observed in the solutions of multiple chains. These results indicate that the solvent becomes effectively poor again at very attractive polymer-solvent interactions. Nonetheless, the mechanism of chain collapsing and phase separation in this limit differs from the case with a poor solvent rendered by unfavorable polymer-solvent interactions. In the latter, the solvent is excluded from the domain of the collapsed chains while in the former, the solvent is still present in the pervaded volume of a collapsed chain or in the polymer-rich domain that phase separates from the pure solvent. Finally, in the limit of strong polymer-solvent attractions, the solvent behaves as a glue to stick monomers together, causing a single chain to collapse and multiple chains to aggregate and phase separate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure–property relationships of reduced graphene oxide membranes intercalated with polycyclic aromatics

Graphene oxide (GO) membranes intercalated with various organic moieties have shown excellent potential for a range of water processing applications. However, microstructure–functional property relationships in these structurally disordered membranes are not well understood. We demonstrate a practical methodology for developing such relationships for GO membranes intercalated with molecular species, with polycyclic aromatic toluidine blue O (TBO) as an example functional intercalant. We use solid-state UV–vis absorbance and fluorescence measurements to quantitatively track the arrangements of TBO in a series of TBO-loaded reduced GO (rGO) membranes. This study reveals the evolution of diverse arrangements including TBO monomers, lateral and stacked dimers, and other aggregates, as a function of overall TBO loading. These microstructures are then correlated to changes in overall properties such as interlayer d-spacings, permeate fluxes, and solute rejections. The characterization of these different intercalant microstructures explains non-intuitive flux and rejection trends, which can circumvent flux and solute rejection trade-offs.

02 PETROLEUM↗

Chalcocarbogels as High-Capacity and Cycle-Stable Electrode Materials for Lithium and Sodium Ion Batteries

The low capacities of commercial Li ion batteries and cycle instabilities of amorphous metal sulfide based batteries impose constraints on their utilization for large-scale energy storage. We report here the acid-free, room-temperature (RT), and solution-based synthesis of a chalcogenide–carbonaceous hybrid aerogel, termed as “chalcocarbogel”, comprising molybdenum sulfide (MoS x ) and graphene oxide (GO). The chalcocarbogel is a nanoparticle-aggregated, porous, amorphous gel consisting of Mo 3 S 13 and Mo 2 S 12 -like structures as determined by synchrotron X-ray PDF, XANES, and EXAFS. The MoS x -GO chalcocarbogel demonstrates high specific capacities of ~1215 and ~807 mAh g –1 for Li/MoS x -GO and Na/MoS x -GO cells, respectively, for a 50 mAg –1 discharge rate during the first cycle. After the activation cycles, the MoS x -GO chalcocarbogel stabilizes, maintaining high specific capacities of approximately ~700 mAh g –1 for Li/MoS x -GO and ~473 mAh g –1 for Na/MoS x -GO cells, while continuously cycling. Importantly, the MoS x -GO aerogel reported here serves as a promising platform to develop chalcocarbogels for applications spanning both Li and Na ion batteries.

25 ENERGY STORAGE↗

Synergy between Photoluminescence and Charge Transport Achieved by Finely Tuning Polymeric Backbones for Efficient Light-Emitting Transistor

The lack of design principle for developing high-performance polymer materials displaying strong fluorescence and high ambipolar charge mobilities limited their performance in organic light-emitting transistors (OLETs), electrically pumped organic laser, and other advanced electronic devices. Here, a series of semiladder polymers by copolymerization of weak acceptors (TPTQ or TPTI) and weak donors (fluorene (F) or carbazole (C)) have been developed for luminescent and charge transporting properties. It was found that enhanced planarity, high crystallinity, and a delicate balance in interchain aggregation obtained in the new copolymer, TPTQ-F, contributed to high ambipolar charge mobilities and photoluminescent quantum yield. TPTQ-F showed excellent performance in solution-processed multilayered OLET devices with an external quantum efficiency (EQE) of 5.3%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct measurement of Stokes–Einstein diffusion of Cowpea mosaic virus with 19 µs-resolved XPCS

Brownian motion of Cowpea mosaic virus (CPMV) in water was measured using small-angle X-ray photon correlation spectroscopy (SA-XPCS) at 19.2 µs time resolution. It was found that the decorrelation time τ(Q) = 1/DQ 2 up to Q = 0.091 nm -1 . The hydrodynamic radius R H determined from XPCS using Stokes–Einstein diffusion D = kT/(6πηR H ) is 43% larger than the geometric radius R 0 determined from SAXS in the 0.007 M K 3 PO 4 buffer solution, whereas it is 80% larger for CPMV in 0.5 M NaCl and 104% larger in 0.5 M (NH 4 ) 2 SO 4 , a possible effect of aggregation as well as slight variation of the structures of the capsid resulting from the salt–protein interactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Nanofabrication of silicon surfaces for reduced virus adhesion

Nanofabrication is a remarkably effective technique to create desirable nanoscale patterns. Here, the effect of surface nanofabrication on altering virus adhesion to the substrates was examined. Arrays of nanoholes, 50 nm in diameter, 22 nm deep, and 100 nm in pitch distance, were created on silicon (Si) wafers by electron-beam lithography and reactive ion etching. MS2 coliphage, which is 26 ± 2 nm in diameter and is frequently used as a surrogate for human viruses, was applied to investigate the interaction between the virions and smooth or nanostructured Si surfaces. Scanning electron microscopy and atomic force microscopy along with surface wettability analyses revealed that the nanofabrication had the effect of reducing not only the number of viruses attached but also the strength of virus adhesion. These effects were ascribed to the presence of nanoholes, which were inaccessible to the virions due to the unique surface topographical parameters and the surface chemistry, resulting in the decrease of the overall solid contact area for MS2 attachment. The periodic spacing of the nanoholes also limited the unit landing area for MS2 particles, restricting the formation of MS2 aggregates and leading to the reduced amount of MS2 attachment. We anticipate that smart design of a surface’s chemical composition and nanostructure will offer a feasible solution to improve mitigations for controlling viral adhesion and transmission to and from food contact surfaces.

36 MATERIALS SCIENCE↗