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At least 649 records · Page 36

Postfire Biogeochemical Processes: Implications to Source Water Quality in Fire-Influenced Watersheds

Forested watersheds are instrumental in providing purified and reliable water to millions of people worldwide. The changing climate has increased the frequency and severity of global fire events. Forested watersheds and their ecosystem functions are greatly disrupted during fire activity. Postfire concerns in forested watersheds include unpredictable and potentially simultaneous alterations in source water quality and hydro-biogeochemical processes. Here, the degree of fire severity can complexly modify water quality through the production of fire-transformed constituents on the burned forest floor (i.e., nutrients, metal(loid)s, dissolved organic matter, and the formation of disinfection byproducts). Correspondingly, fire severity and postfire rainfall patterns can refine hydro-biogeochemical processes that influence the transport of the fire-transformed constituents (i.e., vegetation function, soil structure, hydrological pathways, and microbial communities). Postfire alterations to water quality and hydro-biogeochemical processes introduce further complexity with varying temporal influence, which ranges from months to decades. As postfire water quality and watershed response research progresses, it is essential to homogenize interdisciplinary expertise to bridge knowledge gaps between fields ranging from forest ecology, hydrology, microbiology, and geochemistry. A multidisciplinary approach in wildfire research will facilitate a comprehensive perception of the diverse water quality risks associated with fire activity and mitigate fire concerns on a global level.

Disinfection Byproducts↗

Facet-Dependent Adsorption of Pb(II) on Hematite (001), (116), and (104) Surfaces

Hematite’s common (001) and (012) facets are frequently used in model studies of lead (Pb) adsorption behavior, but there is a lack of research on the high-energy facets, e.g. (104), present in nature. Also, few studies have attempted to connect the molecular details of facet-specific Pb adsorption to macroscopic uptake behavior. Here, to address these knowledge gaps, we investigated Pb(II) adsorption behaviors on facet-engineered hematite nanoparticles dominated by (001), (104), and (116). Adsorption experiments revealed significant variations in Pb(II) uptake among the three samples, with (001) demonstrating the highest capacity and (116) showing the best adsorption efficiency when normalized to specific surface area. Adsorption kinetics followed the pseudo-second-order model, indicating the adsorption process is governed mostly by chemisorption. Adsorption isotherms were well fitted by the Langmuir model, indicating uptake proceeds until roughly monolayer adsorption. Detailed characterization revealed Pb(II) was adsorbed as single atoms with complex inner-sphere binding modes that varied across different facets, indicating adsorption is both structurally and energetically facet-dependent. Co-adsorption experiments further demonstrated Cu 2+ , Zn 2+ , and humic acid significantly promoted Pb(II) adsorption. This study advances the understanding of hematite surface reactivity in controlling macroscopic wet adsorption behaviors, providing valuable insights into the environmental fate of Pb(II).

Contaminant removal↗

Optimizing Cryo-Focused Pyrolysis GC/MS for Tracing Soil Organic Matter Across Diverse Ecosystems

The cycling of organic matter in terrestrial soils and sediments is central to a range of biogeochemical processes that regulate nutrient cycling, crop productivity, trace gas emissions, and contaminant transport. Pyrolysis-gas chromatography/mass spectrometry (py-GC/MS) is a powerful tool for characterizing bulk soil organic matter (SOM) at the molecular level. In this study, we used a cryo-focused py-GC/MS system to analyze soil samples from seven diverse ecosystems: vernal pool, prairie pothole, temperate forest, tropical forest, tundra, wildfire-affected boreal forest, and grassland. We addressed a key bottleneck in molecular-level SOM characterization by developing an automated data analysis pipeline to optimize py-GC/MS and complementary evolved gas analysis/mass spectrometry (EGA/MS) methods, incorporating advanced tools for peak deconvolution, developing a custom compound class library, and implementing fragmentation spectrum-based molecular networking for the first time. This improved workflow was applied to soil samples from all seven ecosystems, including multiple depths and density fractions. Our findings demonstrate that ecosystem type plays a dominant role in shaping compositional differences in SOM. We also identified trends in the source of SOM compounds (e.g., microbial vs plantderived) across soil depth and density fractions, which are critical for understanding persistence and turnover of SOM. Our molecular networking analysis indicated that although many compounds are widespread across ecosystems, others are restricted to specific environments, such as wetlands. This underscores the utility of molecular-level data in elucidating the complexity of SOM composition and the environmental drivers that shape it. Such molecular-level insights can deepen our knowledge of biogeochemical SOM cycles.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Evolution of Mass and Physical Properties of Atmospheric Organic Aerosol under Solar Irradiance

Organic aerosol (OA) particles constitute a substantial fraction of sub-micron particulate mass in the atmosphere and play a critical role in climate system. OA undergoes dynamic aging processes in the atmosphere, with photolytic aging induced by ultraviolet solar irradiance being an important yet poorly characterized mechanism. Knowledge gaps persist regarding the role of volatility transformations during photolytic aging on the OA mass decay kinetics and the evolution of climate-relevant properties, such as hygroscopicity, hindering the model evaluation of OA spatiotemporal distributions and atmospheric budgets. In this study, we conduct isothermal photolytic aging experiments on both laboratory-generated secondary organic aerosols and ambient-collected particles from urban Atlanta, utilizing a high-sensitivity Quartz Crystal Microbalance. Our results reveal that photolytic aging reduces 40–66% of the low-volatility OA mass with lifetimes ranging from 8 to 200 hours under solar irradiance, and 44–92% of the photolytic mass loss is through slow evaporation of semi- or intermediate-volatile products, kinetically limited by their volatility. We observe up to ±50% changes in OA hygroscopicity with the transformation of fresh OA to photo-recalcitrant low-volatility products, associated with changes in oxygen-to-carbon ratio and molecular weight. A kinetic model incorporating photolytic volatility transformation provides a cohesive explanation for the observed photolysis-induced changes in mass, volatility, and hygroscopicity. Our results can help constrain model representation of the dynamic evolutions of mass and climate-relevant properties during photolytic aging processes of the ambient OA, improving our understanding of OA atmospheric behavior and climate impact.

Bai, Bin↗

Enhancing f -Element Separations with ADAAM-EH: The Impact of Phase Modifiers and a DGA Aqueous Complexant

Recent investigations have used a 2-ethylhexyl diamide amine (ADAAM-EH) for Am/Cm separations in combination with N,N,N ',N '-tetraethyldiglycolamide as an aqueous complexant to achieve an unprecedented separation factor of 41. The aim of this research effort is to understand the speciation of trivalent lanthanide (Ln) and actinide (An) ions in the organic phase of an ADAAM-EH extraction system, both with and without phase modifiers (PM) (1-octanol and tri-n-butyl phosphate (TBP)). Leveraging spectroscopic techniques in combination with distribution ratio measurements provides an understanding of organic phase f-element ligand complexation. In the absence of PM, Ln is extracted in a stoichiometric 1:1 [M(ADAAM-EH) 1 (NO 3 ) x (H 2 O) 1 ](NO 3 ) 3-x complex. The addition of 1-octanol at 20 vol % results in multiple species present. One of the species is the same as the no PM case, and the other species results in an increased -OH coordination to the inner sphere, potentially displacing some NO 3 . In the case of TBP, increasing concentration results in additional red-shifted bands in the UV-visible spectra, suggesting the complexation of additional ligands of either ADAAM-EH or TBP. Finally, the new system knowledge obtained by and spectroscopic experiments will provide benchmarking information for computational studies of the inner- and outer-sphere coordination environments of f-element cations and insights into ADAAM-EH adduct formation with PM, like 1-octanol and TBP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Radiation Effects on the Performance of Advanced Sulfur Monochloride Chlorination Processes

Advanced sulfur chloride-based chlorination technologies are being developed to enable efficient recycling of aluminum and zirconium-based materials used in the nuclear industry. However, the impacts of ionizing radiation on the performance of these sulfur chloride compounds are not well established, despite this being critical knowledge for assessing their feasibility and longevity under envisioned process conditions. Here, in the present article, we report on the effects of cobalt-60 gamma irradiation (≤ 5 MGy) on the aluminum alloy 6061 (AA6061-T6) chlorination yield in sulfur monochloride (S 2 Cl 2 ). Our findings indicate that, compared to nonirradiated solvent, radiation-induced changes in the chemical composition of S 2 Cl 2 —identified using Raman spectroscopy—afford an additional, dose-dependent exothermic process prior to the chlorination reaction’s typical thermodynamic behavior. We attribute this new process to reactions involving aluminum species (metal, oxide, or [oxy]hydroxides) and sulfur dichloride (SCl 2 ), an S 2 Cl 2 radiolysis product that accumulates with absorbed gamma dose, but is absent following an AA6061-T6 chlorination study. Despite the exothermicity of this new process, the overall yield of chlorination decreased with increasing preirradiation dose. Consequently, the chemical reactivity, specificity (aluminum metal vs aluminum passivation and corrosion layer constituents), and byproducts of SCl 2 must be more thoroughly evaluated to support the continued development of advanced S 2 Cl 2 chlorination technologies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

UV–Vis–NIR Reflectance Spectroscopy and Chemometrics for Monitoring Pu Directly on an Ion Exchange Column

Here, we present a fiber-optic UV–vis–NIR reflectance spectroscopy method for direct, noninvasive monitoring of Pu(IV) in a glass ion exchange column during dynamic loading and elution in a glovebox. A movable probe enables spatially resolved spectral acquisition along the column axis, capturing distinct features associated with Pu(IV) nitrate complexes during loading and free ions during elution. Principal component analysis was applied to extract the dominant spectral variance and resolve relative concentration profiles without requiring precise knowledge of optical penetration depth or species identity. This in situ approach reveals spatial gradients and speciation dynamics in real time, which provides actionable insight into Pu(IV) ion migration, resin saturation, and breakthrough behavior under evolving flow conditions. The method offers a practical, fiber-compatible strategy to monitor glass column–based separations for Pu and other lanthanides or actinides and to characterize metal–resin interactions in flow-through systems.

actinide↗

Impacts of Focused Ion Beam Processing on the Fabrication of Nanoscale Functionalized Probes

Herein, we examine the impact of Ga + ion kinetic energy and the target material type on the extent of ion implantation and structural damage in atomic force microscopy probes made of Al 2 O 3 and ZnO manufactured by focused ion beam (FIB) using scanning transmission electron microscopy and energy-dispersive X-ray mapping. Penetration of Ga into the Al 2 O 3 lattice induced structural distortions and amorphization. For ZnO probes, Ga is uniformly dispersed across the surface, resulting in the formation of distinct clusters. Atom probe tomography further validates the Ga distributions in Al 2 O 3 and ZnO nanoprobes. Complementary Monte Carlo simulations with the transport of ions in the matter program indicated that the introduction of Ga + prompts the generation of cation and anion vacancies, an occurrence more pronounced in Al 2 O 3 compared to ZnO. In conclusion, this study not only enriches the knowledge of ion-matter interactions, but also serves as a practical guide for the fabrication of nanoscale functionalized AFM probes.

Al2O3↗

Doubly Stereogenic Sandwich Frameworks: Diastereomeric Metallobiscorroles

A number of Group 6 metallobiscorrole sandwich compounds with square-antiprismatic coordination were separated into diastereomers by means of careful preparative thin-layer chromatography. The diastereomers differ with respect to the relative orientation of the corrole macrocycles, which are rotated approximately ± 45° or ± 135° relative to each other. The most clear-cut results were obtained for two tungsten corroles, W[TBCF 3 PC] 2 {TBCF 3 PC = meso-tris[3,5-bis(trifluoromethyl)phenyl]corrolato} and W[TDOMePC] 2 [TDOMePC = meso-tris(3,5-dimethoxyphenyl)corrolato], for which single-crystal X-ray structures were obtained for the 135° diastereomer; the existence of the 45° diastereomer was inferred by elimination and with support from DFT calculations. For Mo[TBCF 3 PC] 2 and W[TBCF 3 PC] 2 , both diastereomers were also fully characterized spectroscopically and their 1 H NMR spectra were essentially fully assigned. The fact that each diastereomer is chiral and exists as two enantiomers (which was previously demonstrated for the 135° form of a tungsten biscorrole) establishes the doubly stereogenic nature of the metallobiscorrole framework – to our knowledge, the first such demonstration for a sandwich compound.

Aromatic compounds↗

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↗

Delta/Lambda Chirality: From Enantiomers to Diastereomers in Heterometallic Complexes with Chelating Ligands

The Δ/Λ chirality observed in octahedral molecules with chelating ligands represents the major group of “chiral-at-metal” complexes. Upon shifting from mononuclear to polynuclear systems with multiple (≥2) chiral centers, not only enantiomers but also diastereomers should be considered. We present the first, to the best of our knowledge, diastereomeric pairs Δ,Δ,Δ/Λ,Λ,Λ (1) and Δ,Δ,Λ/ Λ,Λ,Δ (2) of the pentanuclear assembly [Mn II (ptac) 3 −Na- Co III (acac) 3 −Na-Mn II (ptac) 3 ] (ptac = 1,1,1-trifluoro-5,5-dimethyl- 2,4-hexanedionate; acac = acetylacetonate). Diastereomers 1 and 2 were isolated in pure form and found to exhibit distinctly different structural characteristics. Importantly, for compounds that are applied as single-source precursors for the quaternary oxide cathode material P2−Na 0.67 Mn 0.67 Co 0.33 O 2 , the diastereomers revealed different thermal behaviors in terms of volatility and thermal stability. Unambiguous assignment of the Mn and Co positions in both diastereomers has been confirmed by the synchrotron X-ray resonant diffraction technique. Oxidation states of metal ions have been verified by the synchrotron X-ray fluorescence spectroscopy. The diastereomerization between 1 and 2 is not taking place in the solid state (crystal-to-crystal), as well as in the gas phase. The transformation between two diastereomers was observed in the solutions of noncoordinating solvents and was related to the polarities of the solvents and diastereomeric molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Universal Reversible Hydrogen Potential for Electrocatalytic Ammonia Splitting Reactions in Nonaqueous Solvents from Unified pH Measurements

In this work, we introduce a new approach of using differential potentiometric measurements in four nonaqueous solvents─MeCN, THF, DMF, and PC─to determine the universal pH abs H 2 O values aligned to the aqueous pH scale for dilute NH 4 + /NH 3 solutions. Knowledge of the pH abs H 2 O values allows simple determination of the reversible hydrogen potential in any given solvent relative to the aqueous standard hydrogen electrode (SHE) and, most importantly, ensures comparability across different solvents. As an independent method, Open Circuit Potenial measurements were carried out in the same solvents titrated with NH 4 + /NH 3 to obtain alternative values for the reversible hydrogen potential in these solvents. The close agreement of these two methods, as well as calculated potentials from literature values when available, substantiates the new, simpler, and more robust approach to determine the reversible hydrogen potential introduced here. We further use the reversible hydrogen potential values established here to report, for the first time, the overpotential for ammonia oxidation as a function of solvent, with a recently discovered ruthenium catalyst.

ammonia↗

Excitation Wavelength-Dependent Emission from Americium(III) in Mineral Acid Solutions

The photoluminescence behavior of trivalent americium, Am(III), in mineral acid solutions is reported under direct-metal excitation at seven high-energy wavelengths in the ultraviolet and visible regions (378-512 nm). This study revealed a dependence of the Am(III)-based visible emission profile on the chosen excitation wavelength. For example, excitation at the more common wavelength of 504 nm produces the two expected emission bands: one at approximately 600 nm (5D1' to 7F0') and another at 690 nm (5D1' to 7F1'). When the excitation wavelength is shifted to 398 nm (targeting the 5D3', 5H7' from 7F0' transitions), the emission occurs almost exclusively at 600 nm. This behavior is unexpected and potentially highlights fundamental knowledge gaps in the current understanding of the intraconfigurational 5f-5f electronic transitions that give rise to Am(III) photoluminescence. Although a full interpretation of these results is limited by the incomplete understanding of Am(III) speciation in mineral acid systems, this study explores several potential explanations for the observed behavior and challenges the widely held assumption of a single emissive Am(III) species.

Americium↗

Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials

Using knowledge from statistical thermodynamics and crystallography, we develop an image–image translation model, called SorbIIT, that uses three-dimensional grids of adsorbate–adsorbent interaction energies as input to predict the spatially resolved loading surface of nanoporous materials over a broad range of temperatures and pressures. SorbIIT consists of a closed-form differential model for loading-surface prediction and a U-Net to generate spatial differential distributions from the energy grids. SorbIIT is trained using the energy grids and adsorbate distributions (obtained from high-throughput simulations) of 50 synthesized and 70 hypothetical zeolites and applied for predicting the adsorption of carbon dioxide, hydrogen sulfide, n-butane, 2-methylpropane, krypton, and xenon in other zeolites from 256 to 400 K. In conclusion, employing a quadratic isotherm model for the local differentiation, SorbIIT yields mean R 2 values of 0.998 for total adsorption and 0.6904 for local adsorption with a resolution of 0.2 Å, and a value of 0.721 for the structural similarity of the local loading distribution.

Sun, Yangzesheng↗

Density Functional Tight-Binding Models for Band Structures of Transition-Metal Alloys and Surfaces across the d -Block

First-principles electronic structure simulations are an invaluable tool for understanding chemical bonding and reactions. While machine-learning models such as interatomic potentials significantly accelerate the exploration of potential energy surfaces, electronic structure information is generally lost. Particularly in the field of heterogeneous catalysis, simulated electron band structures provide fundamental insights into catalytic reactivity. This ab initio knowledge is preserved in semiempirical methods such as density functional tight binding (DFTB), which extend the accessible computational length and time scales beyond first-principles approaches. In this paper here we present Shell-Optimized Atomic Confinement (SOAC) DFTB electronic-part-only parametrizations for bulk and surface band structures of all d-block transition metals that enable efficient predictions of electronic descriptors for large structures or high-throughput studies on complex systems outside the computational reach of density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗

Determining the N -Representability of a Reduced Density Matrix via Unitary Evolution and Stochastic Sampling

The N-representability problem consists in determining whether, for a given p-body matrix, there exists at least one N-body density matrix from which the p-body matrix can be obtained by contraction, that is, if the given matrix is a p-body reduced density matrix (p-RDM). The knowledge of all necessary and sufficient conditions for a p-body matrix to be N-representable allows the constrained minimization of a many-body Hamiltonian expectation value with respect to the p-body density matrix and, thus, the determination of its exact ground state. However, the number of constraints that complete the N-representability conditions grows exponentially with system size, and hence, the procedure quickly becomes intractable for practical applications. This work introduces a hybrid quantum-stochastic algorithm to effectively replace the N-representability conditions. The algorithm consists of applying to an initial N-body density matrix a sequence of unitary evolution operators constructed from a stochastic process that successively approaches the reduced state of the density matrix on a p-body subsystem, represented by a p-RDM, to a target p-body matrix, potentially a p-RDM. The generators of the evolution operators follow the well-known adaptive derivative-assembled pseudo-Trotter method (ADAPT), while the stochastic component is implemented by using a simulated annealing process. The resulting algorithm is independent of any underlying Hamiltonian, and it can be used to decide whether a given p-body matrix is N-representable, establishing a criterion to determine its quality and correcting it. We apply the proposed hybrid ADAPT algorithm to alleged reduced density matrices from a quantum chemistry electronic Hamiltonian, from the reduced Bardeen–Cooper–Schrieffer model with constant pairing, and from the Heisenberg XXZ spin model. In all cases, the proposed method behaves as expected for 1-RDMs and 2-RDMs, evolving the initial matrices toward different targets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Confusion-Driven Machine Learning of Structural Phases of a Flexible, Magnetic Stockmayer Polymer

We use a semisupervised, neural-network-based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chains of magnetic colloidal nanoparticles characterized by dipole–dipole and Lennard-Jones interactions. As input for the neural network, we use the particle positions and magnetic dipole moments of equilibrium polymer configurations, which we generate via replica-exchange Wang–Landau simulations. We demonstrate that by measuring the classification accuracy of neural networks, we can effectively identify transition points between multiple structural phases without any prior knowledge of their existence or location. We corroborate our findings by investigating relevant conventional order parameters. Our study furthermore examines previously unexplored low-temperature regions of the phase diagram, where we find new structural transitions between highly ordered helicoidal polymer configurations.

36 MATERIALS SCIENCE↗