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At least 1,135 records · Page 63

Electrocatalytic oxidation of hydrothermal liquefaction-derived aqueous phase for on-site wastewater treatment and H 2 production

Electrocatalytic oxidation (ECO) is a promising method for generating molecular hydrogen (H 2 ) while simultaneously treating the aqueous phase (AP) from hydrothermal liquefaction (HTL) of biomass-derived feedstocks such as algae, food waste, sludge, and wood. This study highlights the impact of HTL-AP composition on ECO performance, mainly activity, stability, and efficiency in a batch and flow electrolyzer. We demonstrated current efficiency (CE) for chemical oxygen demand (COD) removal ranges from 14% to 85% in the flow electrolyzer with electrode stability increasing from 20 to ≥2,800 h. Decreasing the applied potential enhances the CE. High ammonium content can accelerate deactivation, yet chloride ions appear to aid oxidation of organic compounds and enhanced anode stability. A preliminary energy and H 2 balance for an HTL sewage sludge plant shows that the HTL-AP contains sufficient COD to produce all the H 2 needs for bio-oil hydrotreating, with a 26% surplus available for other uses.

Electrolysis↗

Effect of Impurities on the Redox Properties of Goethite

Iron oxide minerals regulate the flux of electrons in the environment and are important hosts for trace and minor, yet critical, elements. Here, we present the first evidence of a direct link between the local coordination environments of Ni and Zn and the redox properties of their host phase goethite (α-FeOOH), the most abundant Fe(III) (oxyhydr)oxide at Earth’s surface. Here, we used aqueous redox measurements to show that the redox potential E H 0 , and hence the mineral’s stability, follows the order: pure goethite ≥ Zn-goethite > Ni-goethite. Parallel X-ray absorption and scattering measurements demonstrate, using quantum-informed analysis, that the local coordination environment of the smaller impurity, Ni, causes more bulk strain energy than Zn, which nearly accounts for the difference in E H 0 between Ni- and Zn-goethite. Our theory-informed, experimental study reveals how two common impurities affect the stability of goethite with implications for the biogeochemical reactivity of Fe(III) (oxyhydr)oxide in mediating elemental and electron fluxes in the environment.

42 ENGINEERING↗

Surface Crust Formation Controls Evaporation Kinetics of Secondary Organic Aerosols

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

heterogeneous chemistry↗

Spectroscopic Properties of Americium(III) in Mineral Acid Media

We report the preparation and optical characterization of three solutions of Am(III) in common aqueous (aq.) mineral acids (HCl, HNO 3 and HBr), including absorption, emission, and Raman vibrational analyses. To our knowledge, this study provides the first detailed absorption spectra of Am(III) spanning the entire UV/Vis/NIR region in these mineral acids reported since the 1960s. Here, using this high-resolution absorption data, provided in an open access format for the broader field, we build on prior work by Carnall and others to provide detailed optical analysis including all transition assignments. This work also includes the first reported absorption spectrum of Am(III) in aq. HBr. Characteristic Am(III) luminescence could be detected from all three samples. These are the first reports of emission from Am(III) in these acid systems, which build on prior emission reports collected from aq. HClO 4 solutions. The acquired emission spectra display anion-dependent shifting of the visible-region transitions by up to 21 nm from their predicted positions, akin to the nephelauxetic effect. The shift magnitude trends linearly according to the acid p K a and more generally according to the transition metal spectrochemical series. These ligand field effects, coupled with luminescence lifetime experiments, indicate that weak Am-X interactions persist in solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reorganization of Water at Aqueous Aluminum Chloride (AlCl 3 ) Interfaces: Vibrational Sum Frequency Generation and Molecular Dynamics Simulations

AlCl 3 hydration states and complexation are not well understood both in solutions and at the air–aqueous interface despite their potential significance in natural waters and their industrial and energy-related applications. Here, we investigated Al 3+ and Cl – ion behaviors in an AlCl 3 aqueous bulk solution and at the air–aqueous interface using interface-selective vibrational sum frequency generation (SFG), Raman and infrared spectroscopies, molecular dynamics (MD) simulation, as well as molecular-informed reduced modeling. Our reduced modeling reveals relatively long-range effects for Al 3+ as compared to monovalent ions such as Na + indicating that the interfacial depth of trivalent ions can be significantly larger than that of monovalent ions at the air–water interface. MD simulations reveal interfacial stratification and multiple layering of the ions. Compression of the Al 3+ and Cl – distributions with increasing concentrations from 0.5 to 2.5 m is also observed in the subsurface regions. Significant SSP- and PPP-polarized SFG OH spectral intensity increases are observed from 0.5 to 1.5 m and 0.5 to 2.5 m, respectively, indicative of interfacial depth increases and a change in average orientation above 1.5 m. Extensive evaluation of SFG spectra, Fresnel-corrected using several approaches, shows the same trends. The nonmonotonic trend points to a changing structure in surface and subsurface water orientation and hydrogen bonding environment generally consistent with the MD simulation of stratification and water orientation changes. Furthermore, solvent-shared ion pairing is implicated with MD simulation radial distribution analysis and consistent with infrared spectral identification of the hexaaqua aluminum ion in the solution phase. Spectral evidence of a strong Al 3+ hydration shell and the acidic behavior of the Al 3+ ions is obvious in the Raman and infrared spectra of the bulk solution. In conclusion, we show that the MD dipole potential is directly related to the MD second-order susceptibility of the interface, χ SFG–MD (2) , both of which correlate up to ∼35 Å with the spectral observations of increasing and then saturating intensities, suggesting that both ion stratification and interfacial depth determine the water orientations at an air–water interface of 1-3 electrolyte solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

STEPs-SOL, a Peptoid Force Field Parameterization to Include Solvent Effects

As peptoids (N-substituted glycines) continue to gain popularity as a class of biomimetic polymers, the importance and demand for accurate force fields in molecular simulations also grow. Building on the vacuum-optimized Systematic and Extensible Force Field for Peptoids (STEPs) force field, here we present STEPs-SOL, a novel peptoid force field parametrization that effectively incorporates solvent effects to enhance the accuracy of peptoid simulations. The development of STEPs-SOL is based on the need for precise electrostatic modeling achieved through solvent-specific partial charge optimization. Here, our systematic approach significantly improves agreement with experimental measurements, reducing the mean absolute error in cis/trans ratio predictions (ΔG c/t ) by an average of 38% across multiple peptoid residues and solvent environments. This improved parametrization addresses computational challenges associated with nonbonded energies while maintaining a workflow that relies on high-level quantum mechanical data rather than depending solely on limited experimental equilibrium properties. By evaluating the effects of conformational bias in restrained electrostatic potential (RESP) charge generation and examining their impact on peptoid conformations in various solvents, we enhance our understanding of peptoid structural dynamics while providing a more accurate modeling framework.

force field↗

Radiolytic Production of Radical Species in Gibbsite Doped with Iron and Chromium Ions

Gibbsite (aluminum hydroxide, Al(OH) 3 ) nanoparticles, synthesized from aluminum chloride or aluminum nitrate, were doped with metal ions, Cr(III) or Fe(III), and then irradiated with γ rays to determine the effect of the dopants on radiolytic hydrogen (H 2 ) production and radical generation. The addition of Cr(III) and Fe(III) ions at concentrations of 0.5% or 5% decreased the concentration of stable oxygen-centered radicals, with the strongest suppression in Cr(III) doped samples. A decrease in H 2 yields was observed with increasing Cr(III) or Fe(III) concentrations, with the greatest effect observed for the Fe(III)-doped samples. Reduction of the Cr(III) to Cr(II) and Fe(III) to Fe(II) was also observed, probably due to scavenging of radiolytically produced electrons. However, further processes differ for Fe(III)- and Cr(III)-doped systems. Both ions are reduced by the free electrons, leading to a decrease in H 2 production, but they react differently with the oxygen radicals. Cr(III) can be oxidized by oxygen radicals, whereas Fe(III) cannot. Fe(II) can interact with peroxides, possible products of intermediate oxygen oxidation, converting back to Fe(III) and leaving oxygen radicals behind. These oxidation reactions lead to a difference in the observed relative effects on H 2 yields and oxygen radical production between Cr(III)- and Fe(III)-doped gibbsite. In conclusion, the connection between electron scavenging and H 2 production indicates that radiolytically produced electrons are precursors to H 2 .

Anions↗

Imaging Domain Walls in van der Waals Ferroelectrics Using Tip-Enhanced Second Harmonic Generation

van der Waals ferroelectrics have captured significant interest for applications in novel memory and neuromorphic computing devices. Within these materials, interfaces between regions of different ferroelectric polarizations (i.e., domain walls) exhibit distinctive behaviors. Characterization of these behaviors remains a challenge, as domain wall thickness resides at the nanoscale. Using tip-enhanced second harmonic generation (TESHG), we demonstrate nanoscale imaging of domain walls in 2D ferroelectric α-In 2 Se 3 . With a narrow-band near-IR laser, we take advantage of high-wavelength, off-resonant signal enhancement to generate robust and reproducible TESHG. In conclusion, a 16 nm spatial resolution is achieved, and we identify spectral features suggesting that nonlocal effects from domain walls persist nanometers into adjacent domains.

Mantilla, Alexander B. C. [Washington State Univ.,↗

DancePartner: Python Package to Mine Multiomics Relationship Networks from Literature and Databases

A goal of multi-omics experiments is to understand how mechanistic molecular biology is altered between conditions, typically a control group and experimental groups. Oftentimes this involves studying changes in biomolecule relationships (e.g. interactions, metabolic relationships) of several types of biomolecules (e.g. proteins, lipids, metabolites). Though several databases contain relationships between biomolecules, understudied species may have little to no relationship information in databases and thus must be mined from literature. There are several challenges to literature mining, including automated full-text extraction, duplicate biomolecule term collapsing, and implementing complex machine learning tools. To make relationship extraction more accessible to the community, a python package called DancePartner was developed to allow for the extraction of relationships from literature and databases, with functions to map biomolecule synonyms to standardized identifiers and visualize and characterize the resulting multi-omics network. Here, in this study, an example dataset involving Caenorhabditis elegans is presented, where relationships are mined from 1443 publications using DancePartner. These relationships are combined with relationships from KEGG, WikiPathways, UniProt, and LipidMaps, and visualized.

BERT↗

Reactive Modified Epoxy Resin and Its Miscible Blends Based on Recycled Oligomers from Solvolysis

Chemical depolymerization of fully cured epoxy resin with 20% reactive modifier was successfully performed via a solvent-assisted solvolysis process into low molecular weight recyclable oligomers (RO) at 240 °C in a pressure vessel at 650 psi for 4 h. The thermoset epoxy resin was depolymerized into transparent brown viscous fluid with a higher viscosity than the uncured epoxy resin with approximately 93% yield. Different concentrations of the RO were homogeneously mixed with the pure epoxy resin, and their curing kinetics, viscosity, FTIR, mechanical properties, DMA, and cross-link density were investigated. The curing kinetics of the pure reactive modified epoxy resin (baseline) and its mixtures with RO of different concentrations were investigated under both isothermal and nonisothermal conditions using small amplitude oscillatory shear flow. The elastic and viscous moduli (G′ and G″), complex viscosity (η*), and tan δ values were evaluated at different curing times and temperatures. The G′, G″, and η* increased dramatically, while tan δ decreased strongly by several orders of magnitude at the gel point. The zero-shear viscosity (η 0 ) was determined from the angular frequency dependent on η* based on the Cross model for different blend compositions in the liquid state before curing. The composition dependence of η 0 showed a positive deviation from the linear mixing rule and was well described by the Lecyar model. Here, the apparent activation energy of curing (E a ) was also evaluated according to the Arrhenius equation and was found to be 46 ± 2 kJ/mol regardless of the different contents of RO. For all blends up to 40 wt % RO, only one tan δ peak systematically shifting to lower temperatures with increasing content of RO was observed in the DMA measurements, indicating that the epoxy resin and the RO are miscible with up to 40 wt % RO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetics of Pyrolysis and Thermal Evolution of Negev Desert Lithologies

The Negev desert in Israel is home to large quantities of organic-rich, shallow marine sedimentary lithologies that could potentially accommodate the disposal of spent nuclear fuel. Previous thermal analyses of Negev carbonates have focused on industrially relevant considerations such as natural gas and oil extraction or pyrolysis for recovering hydrocarbon fuels. Here, this study addresses thermal evolution of the Negev organic-rich carbonate, siliceous, and phosphorite rocks and associated chemical, mineralogical, and microstructural changes that may occur under prolonged thermal loading in the vicinity of spent nuclear fuel disposal systems. Our employed methods include high-temperature X-ray diffraction, high-temperature infrared spectroscopy, and thermal analysis integrating thermogravimetry, differential scanning calorimetry, and mass spectrometry. Further, we apply iterative iso-conversional model-free methods to derive kinetic parameters for thermal decomposition of the Negev organic-rich carbonate rocks from 200 to 550 °C. Our results have provided mechanistic insights into the thermal evolution encompassing water desorption, decomposition of organic matter, and decarbonation of carbonate phases.

58 GEOSCIENCES↗

Chemical Composition and Mixing State of Wintertime Aerosol from the European Arctic Site of Ny-Ålesund, Svalbard

The Arctic is rapidly warming, and aerosols play an increasingly important role by scattering and absorbing sunlight and by participating in cloud formation. Their optical and cloud-forming properties depend on the mixing state and chemical composition, but observations of these features remain limited. This study comprehensively characterizes 25,254 individual particles collected at Ny-Ålesund, Svalbard (November −December 2020), using microspectroscopy techniques to investigate their size, morphology, mixing state, and chemical composition. Fresh sea salt aerosols (SSA) were identified as the most abundant (∼85%), of the total observed aerosol population, with potential sources from sea spray and blowing snow. Air masses originating from the Arctic Ocean surrounding Svalbard likely contribute to increased concentrations of sub-micrometer “Fresh SSA” particles. “Aged SSA” particles (7.4%) are enriched in sulfur and nitrogen, compared to “Fresh SSA”. These elevated ratios may result from various atmospheric aging processes including the uptake of sulfuric and nitric acids. Here, our results suggest that aged SSA, with sizes larger than 300 nm, likely underwent chlorine depletion by sulfuric and nitric acids during transport. Additionally, elemental analysis reveals that both fresh and aged SSA can mix with dust particles, regardless of the SSA size (49.9% in sub-micrometer size and 50.1% in super-micrometer size, respectively). Dust particles are efficient ice-nucleating particles (INPs), and SSA is known to act as cloud condensation nuclei (CCN), and therefore, their mixtures may inherit both properties. The non-negligible number (4.4%) of SSA-dust mixtures underscores the importance of these particles as potential sources of CCN and INP in the Arctic atmosphere.

Arctic↗

Chemoproteomic Elucidation of β-Lactam Drug Targets in Mycobacterium abscessus

The pathogen Mycobacterium abscessus (Mab) can cause severe and difficult-to-treat chronic lung infections. Despite the rising incidence and clinical concern of Mab infections, treatment options are limited and often ineffective. Treatment is complicated by Mab’s ability to persist in a nonreplicating, drug-resistant state. Several β-lactam antibiotics are potently bactericidal against Mab but are underutilized because their molecular mechanisms of action against Mab are incompletely understood. In the current study, we used β-lactam-derived activity-based probes and chemoproteomics to report the first comprehensive list of Mab enzymes targeted by β-lactams. We compared β-lactam targets across two Mab subspecies in actively replicating and nonreplicating cultures, using a new carbon starvation model of persistence. We identified 17 targets that were active in every condition tested, seven of which were previously unknown to bind β-lactams. Lastly, we characterized the β-lactamase activity and β-lactam inhibition profiles of nine Mab enzymes, demonstrating that imipenem inhibits these targets more effectively than cefoxitin. These findings demonstrate β-lactam target engagement in persistent Mab and provide clarity on the mechanisms of action of clinically relevant β-lactams in Mab, crucial steps toward fully realizing their potential for treating infections caused by this opportunistic pathogen.

Mycobacterium abscessus↗

Correlating Protein Dynamics and Catalytic Activity of a Model Hydrogenase Using Paramagnetic and Biological Nuclear Magnetic Resonance Spectroscopy

Rational catalyst design remains a significant challenge, with electronic structure, steric, and electrostatic effects known to contribute to activity. Recently, dynamics has been recognized as another factor that impacts catalysis, though identifying and predicting these effects has remained out of reach. Nickel-substituted rubredoxin (NiRd), a protein-based mimic of a hydrogenase enzyme, serves as a model catalytic system in which dynamics can be systematically investigated with respect to activity. While over 30 secondary-sphere mutants of NiRd have been shown to be catalytically active, no significant correlation was observed between the rates and catalytic overpotential or electronic structure, prompting questions about the protein-derived factors that modulate activity. Here, in this work, NMR spectroscopy was used to investigate the roles of substrate accessibility, protein dynamics, and protein stability in controlling catalysis. Significant paramagnetic effects from the nickel center (S = 1) isolate the methylene proton resonances of the metal-coordinating cysteine residues. The sensitivity of resonance positions and linewidths to local environment offers an opportunity to study dynamical molecular changes around the metal center with high resolution. Machine learning algorithms were employed to identify correlations between the catalytic activity and the paramagnetic NMR spectra. These analyses revealed spectroscopic features of specific cysteine protons that report on catalytic overpotential and increased turnover rates, which are further supported by the results obtained using high-field NMR techniques. Collectively, these studies indicate the potential for multifrequency NMR techniques to resolve key contributors to catalytic activity and highlight the importance of local and outer-sphere dynamics.

Protein Engineering↗

The Power of Many: An Ensemble Approach to Spectral Similarity

Quantifying the similarity between two mass spectra─a known reference mass spectrum and an unidentified sample mass spectrum─is at the heart of compound identification workflows in gas chromatography–mass spectrometry (GC-MS). The reference spectrum most like the sample is assigned as its identification (provided some quantitative similarity threshold is met, e.g., 80%) and thus accurately measuring similarity is essential. Significant research has gone toward developing metrics for this purpose, each of which has attempted to improve upon existing methods by incorporating GC-MS-specific information (e.g., peak ratios or retention times) or adopting various statistical and algorithmic frameworks. While this active development has led to a plethora of similarity metrics with demonstrated value across different contexts, the unfortunate consequence has been confusion surrounding which metric should be used as a global standard. No such metric is currently accepted as the standard method because different metrics have demonstrated optimal performance in different contexts. In this work, we propose an ensemble approach to spectral similarity scoring that combines the collective information from across existing similarity metrics to form an improved, globally representative similarity metric as a step toward establishing a global standard method. In conclusion, the resulting ensemble metrics are evaluated on over 88,000 spectra of varying complexity and demonstrate improved abilities to accurately rank the correct reference spectrum as the top-matching candidate for a sample relative to the rankings generated by individual similarity scores.

Carbohydrates↗

On the Prediction of Aerosol-Cloud Interactions Within a Data-Driven Framework

Aerosol-cloud interactions (ACI) pose the largest uncertainty for climate projection. Among many challenges of understanding ACI, the question of whether ACI can be deterministically predicted has not been explicitly answered. Here we attempt to answer this question by predicting cloud droplet number concentration N c from aerosol number concentration N a and ambient conditions using a data-driven framework. We use aerosol properties, vertical velocity fluctuations, and meteorological states from the ACTIVATE field observations (2020–2022) as predictors to estimate N c . We show that the campaign-wide N c can be successfully predicted using machine learning models despite the strongly nonlinear and multi-scale nature of ACI. However, the observation-trained machine learning model fails to predict N c in individual cases while it successfully predicts N c of randomly selected data points that cover a broad spatiotemporal scale. This suggests that, within a data-driven framework, the N c prediction is uncertain at fine spatiotemporal scales.

54 ENVIRONMENTAL SCIENCES↗

Relationships Between Mesoscale Convective System Properties and Midlevel Dynamic Perturbations

Abstract Past studies implicate dynamic anomalies operating on subsynoptic scales as a possible initiation source of summertime (July–August) mesoscale convective systems (MCSs) in the central United States during northwesterly flow regimes. To improve our understanding of warm season MCSs occurring over a variety of flow regimes, we track midlevel (600 hPa) vorticity perturbations (“MPs”) as 2D objects comprising wavelengths of 500–2,500 km over the central US from May–August of 2004–2021. We perform statistical analysis of relationships between metrics of MP objects (e.g., duration, size, intensity, and origin) and high‐resolution MCS precipitation characteristics (e.g., duration, total rainfall, rain coverage area, and motion) that occur while collocated with or in the absence of MPs to discern predictive capability of background dynamic features on storm precipitation potential. Although the majority of MPs collocated with MCS initiation occur during July–August, a significant number (40%) occur between May and June. Northwesterly flow MPs comprise a relative minority of our events, suggesting that MPs can affect MCSs across a variety of warm season flow regimes. MPs affecting MCSs initiated primarily over the high plains near the central Rockies. Only approximately 20% of tracked MCS initiation events were collocated with MPs, but these storms produced ∼25% greater lifetime rainfall and coverage area, and ∼29% more stratiform rain than non‐MP‐induced MCSs. In general, larger and more vigorous MPs resulted in more hydrologically impactful MCSs. The most directly attributable benefit to MCS initiation was from MP‐enhanced background vertical motion and thermodynamic instability (e.g., increased CAPE).

54 ENVIRONMENTAL SCIENCES↗

Ensemble‐Based Spatially Distributed CLM5 Hydrological Parameter Estimation for the Continental United States

Abstract One of the major challenges in large‐domain hydrological modeling efforts lies in the estimation of spatially distributed hydrological parameters while simultaneously accounting for their associated uncertainties. Addressing this challenge is particularly difficult in ungauged locations. With growing societal demands for large‐scale streamflow projections to inform water resource management and long‐term planning, evaluating and constraining hydrological parameter uncertainty is increasingly vital. This study introduces a hybrid regionalization approach to enhance hydrological predictions of the Community Land Model version 5 (CLM5) across the Continental United States (CONUS), with a total of 50,629 1/8° grid cells. This hybrid method combines the strengths of two existing techniques: parameter regionalization and streamflow signature regionalization. It identifies ensemble behavioral parameters for each 1/8° grid cell across the CONUS domain, tailored to three distinct streamflow signatures focused on low flows, high flows, and annual water balance. Evaluating this hybrid method for 464 CAMELS (Catchment Attributes and Meteorology for Large‐sample Studies) basins demonstrates a significant improvement in CLM5 hydrological predictions, even in challenging arid regions. In CONUS applications, the derived spatially distributed parameter sets capture both spatial continuity and variation of parameters, highlighting their heterogeneous nature within specific regions. Overall, this hybrid regionalization approach offers a promising solution to the complex task of improving hydrological modeling over large domains for important hydrological applications.

CLM5↗