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At least 145 records · Page 8

Synthesis of Nitro Compounds from Nitrogen Dioxide Captured in a Metal-Organic Framework

Increasing levels of air pollution are driving the need for the development of new processes that take “waste-to-chemicals”. Herein, we report the capture and conversion under ambient conditions of a major air pollutant, NO 2 , using a robust metal-organic framework (MOF) material, Zr-bptc (H 4 bptc = 3,3',5,5'-biphenyltetracarboxylic acid), comprising {Zr 6 (μ 3 -O) 4 (μ 3 -OH) 4 (COO) 12 } clusters linked by 4-connected bptc 4– ligands in an ftw topology. At 298 K, Zr-bptc shows exceptional stability and adsorption of NO 2 at both low (4.9 mmol g –1 at 10 mbar) and high pressures (13.8 mmol g –1 at 1.0 bar), as measured by isotherm experiments. Dynamic breakthrough experiments have confirmed the selective retention of NO 2 by Zr-bptc at low concentrations under both dry and wet conditions. The immobilized NO 2 can be readily transformed into valuable nitro compounds relevant to construction, agrochemical, and pharmaceutical industries. In situ crystallographic and spectroscopic studies reveal strong binding interactions of NO 2 to the {Zr 6 (μ 3 -O) 4 (μ 3 -OH) 4 (COO) 12 } cluster node. This study paves a circular pathway to enable the integration of nitrogen-based air pollutants into the production of fine chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solute-vacancy clustering in aluminum

In this study, we present an extensive first-principles database of solute-vacancy, homoatomic, heteroatomic solute-solute, and solute-solute-vacancy binding energies of relevant alloying elements in aluminum. We particularly focus on the systems with major alloying elements in aluminum, i.e., Cu, Mg, and Si. The computed binding energies of solute-vacancy, solute-solute pairs, and solute-solute-vacancy triplets agree with available experiments and theoretical results in literature. We consider physical factors such as solute size and formation energies of intermetallic compounds to correlate with binding energies. Systematic studies of the homoatomic solute-solute-vacancy and heteroatomic (Cu, Mg, or Si)-solute-vacancy complexes reveal the overarching effect of the vacancy in stabilizing solute-solute pairs. The binding energy database presented here elucidates the interaction between solute cluster and vacancy in aluminum, and it is expected to provide insight into the design of advanced Al alloys with tailored properties.

36 MATERIALS SCIENCE↗

Machine Learning Chemical Guidelines for Engineering Electronic Structures in Half-Heusler Thermoelectric Materials

Half-Heusler materials are strong candidates for thermoelectric applications due to their high weighted mobilities and power factors, which is known to be correlated to valley degeneracy in the electronic band structure. However, there are over 50 known semiconducting half-Heusler phases, and it is not clear how the chemical composition affects the electronic structure. While all the n-type electronic structures have their conduction band minimum at either the Γ - or X -point, there is more diversity in the p-type electronic structures, and the valence band maximum can be at either the Γ -, L -, or W -point. Here, we use high throughput computation and machine learning to compare the valence bands of known half-Heusler compounds and discover new chemical guidelines for promoting the highly degenerate W -point to the valence band maximum. We do this by constructing an “orbital phase diagram” to cluster the variety of electronic structures expressed by these phases into groups, based on the atomic orbitals that contribute most to their valence bands. Then, with the aid of machine learning, we develop new chemical rules that predict the location of the valence band maximum in each of the phases. These rules can be used to engineer band structures with band convergence and high valley degeneracy.

36 MATERIALS SCIENCE↗

Large adiabatic temperature change and magnetic frustration in triangular lattice antiferromagnet Dy 2 IrSi 3

While previous studies reveal that the formation of polycrystalline R 2 TX 3 (R = rare-earth, T = transition metal, X = p-block element) type compounds with T = Ir and Co is not achievable without deliberate introduction of atomic vacancies of Ir/Co and Si, here we report successful synthesis of Dy 2 IrSi 3 with fully stoichiometric ratio of constituent elements. An antiferromagnetic transition is manifested in the compound at 6.6 K where only about 50 % of Dy spins take part, while the rest remain in highly frustrated state due to edge-sharing triangular lattice geometry. The magnetic frustration is conclusively probed through magnetization, heat capacity and magnetocaloric study and the frustration parameter (f = |θ p |/T N , θ p , T N being Curie-Weiss and Néel temperatures, respectively) in this case is as large as ~ 3. An additional cluster-glass type transition at ~2.8 K observed in this system has likely been originated due to this magnetic frustration. The magnetocaloric effect reveals an adiabatic temperature change of ~7.5 K for 70 kOe magnetic field, which is one of the largest values reported in intermetallic compounds.

36 MATERIALS SCIENCE↗

Softening of dd excitation in the resonant inelastic x-ray scattering spectra as a signature of Hund's coupling in nickelates

We investigate the effects of Hund's coupling on the resonant x-ray absorption spectra of the recently discovered family of layered nickelate superconductors. We contrast two scenarios depending on the relative strength of the ratio of the effective Hund's coupling ( J H ) to the crystal fields ( Δ ) in these systems. We carry out the cluster and DFT + DMFT simulations of the RIXS signal at the Ni L edge for different values of Hund's coupling. We find the latter dominates for the parent compound while the former becomes important for sufficiently large doping. Our results are consistent with the observations of a softening of a RIXS peak as a function of doping by Rossi [], only when the Hund coupling is sizable. To interpret the results, we separate the theoretical RIXS signal into spin conserving and nonspin conserving channels and conclude that the infinite layer nickelates are in a regime where Δ and J compete effectively and suggest further experimental tests of the theory. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Tri-Level Linear Programming Model for Automatic Load Shedding Using Spectral Clustering

Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shedding areas have been predefined by grid operators, they have remained fixed, and may be sub-optimal due to dynamic operating conditions. In this work, a distributed tri-level linear programming model for automatic load shedding to avoid system islanding is presented. Preventing islanding is preferred because it reduces the need for additional load shedding besides the disconnection of transmission lines between islands. This is crucial as maintaining the local generation-demand balance is necessary to preserve frequency stability. Furthermore, uneven distribution of generation resources among islands can lead to increased load shedding, causing economic and reliability challenges. This issue is further compounded in modern power systems heavily dependent on non-dispatchable resources like wind and solar. The upper-level model uses complex power flow measurements to determine the system areas to shed load depending on actual operating conditions using a spectral clustering approach. The mid-level model estimates the area system state, while the lower-level model determines the locations and load values to be shed. The solution is practical and promising for real-world applications.

Baquedano-Aguilar, Mario D.↗

High-Accuracy Semiempirical Quantum Models Based on a Minimal Training Set

A great need exists for computationally efficient quantum simulation approaches that can achieve an accuracy similar to high-level theories at a fraction of the computational cost. In this regard, we have leveraged a machine-learned interaction potential based on Chebyshev polynomials to improve density functional tight binding (DFTB) models for organic materials. The benefit of our approach is two-fold: (1) many-body interactions can be corrected for in a systematic and rapidly tunable process, and (2) high-level quantum accuracy for a broad range of compounds can be achieved with ~0.3% of data required for one advanced deep learning potential. Our model exhibits both transferability and extensibility through comparison to quantum chemical results for organic clusters, solid carbon phases, and molecular crystal phase stability rankings. Overall, our efforts thus allow for high-throughput physical and chemical predictions with up to coupled-cluster accuracy for systems that are computationally intractable with standard approaches.

36 MATERIALS SCIENCE↗

The critical role of soil moisture in compound hazards

Soil moisture regulates the exchange of energy, water, and carbon across land–vegetation–atmosphere interfaces. Extremes in soil moisture can amplify natural hazards through interactions with diverse Earth system processes. Despite its mechanistic importance, soil moisture remains underrepresented in hazard research and predictive frameworks. Here, in this study, we review our current understanding of the role of soil moisture in the evolution and onset of diverse compound hazards by synthesizing the latest findings from observational and modelling studies. We highlight key soil moisture mechanisms, including atmospheric feedbacks that amplify drought–heatwave–wildfire events, precipitation couplings that promote clustered storms, and threshold responses that drive vegetation die-offs, trigger landslides, and induce flooding. Persistent challenges in observational data, model representation and operational implementation have limited the integration of soil moisture into hazard early-warning systems. Addressing these gaps through advances in observations, data assimilation, and physics-based and data-driven modelling will enhance hazard prediction and preparedness in a rapidly changing world.

Li, Chuxuan [University of California, Los Angeles↗

Structure and magnetism across the Sr 2- x Ba x NiOsO 6 phase diagram: Understanding magnetic superexchange between first and third row transition metal ions

The crystal chemistry and magnetism of compositions in the Sr 2-x Ba x NiOsO 6 phase diagram have been investigated to better understand the superexchange interactions between 3d and 5d transition metal ions. Compositions with x ​< ​1.35 crystallize with the double perovskite structure, while those with x ​> ​1.83 crystallize in a trigonal structure that is a cation ordered variant of the 6H hexagonal perovskite structure. The Sr-rich double perovskites undergo a cubic to tetragonal distortion upon cooling that is driven by out-of-phase octahedral tilting. The tetragonal distortion occurs upon cooling below 650 ​K in Sr 2 NiOsO 6 . The temperature of this transition decreases as the barium content increases and is completely suppressed for x ​≥ ​1.2. All compositions in the double perovskite region become spin glasses below T g ​≈ ​40 ​K, due to the competition between ferromagnetic Ni–Os and antiferromagnetic Ni–Ni and Os–Os superexchange interactions. The double perovskite compositions that are rich in barium, like Sr 0.8 Ba 1.2 NiOsO 6 show some signs of magnetic ordering in small clusters, but the presence of Ba/Sr disorder inhibits long-range magnetic order. Trigonal Ba 2 NiOsO 6 orders ferrimagnetically below T C ​= ​108 ​K. In conclusion, the magnetic structure of this compound contains ferromagnetic ~180° Ni–O–Os interactions and antiferromagnetic ~90° Ni–O–Os interactions, both in agreement with the Goodenough-Kanamori rules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of plasma on physical properties of water: nanocrystalline-to-amorphous phase transition and improving produce washing

Recently is was discovered in various applications that many physical and chemical properties of water change their temperature dependence between about 35 and 60 degrees Celsius. In particular, heat conductance, light absorption, and surface tension all change their temperature dependence. These drastic changes were associated with water gradually changing its mesoscopic structure: while at the higher temperatures water is a uniform media (amorphous state), at the temperatures below transition it consists of many nano-to-micro-scale clusters (crystalline state). This transition is similar to the second order phase transition. In the present paper we show that treating water with non-thermal plasma (adding plasma-created active compounds) can lower the temperature of the transition and thus cause a significant change in such physical quantities as surface tension, viscosity, freezing rate, and wettability and washability. We present analytical estimates of the transition temperature shift based on the Debye-Hückel theory. We discuss the produce-washing experiments that illustrate the predicted effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effects of Plasma on Physical Properties of Water: Nanocrystalline-to-Amorphous Phase Transition and Improving Produce Washing

Washing fresh produce using Plasma-activated water recently became a promising eco-friendly alternative to using chemical additives such as Chlorine. We discuss the produce-washing experiments that illustrate that addition of plasma to washing water is a multi-faced phenomena. Not only it increases the sterilization ability of water by killing pathogens, but it also has improved washibility: the ability to remove pathogens from the cleaning surface. We propose an explanation of these features based on the recently discoveries that many physical and chemical properties of water change their temperature dependence between about 35 and 60 degrees Celsius. In particular, heat conductance, light absorption, and surface tension all change their temperature dependence. These drastic changes were associated with water gradually changing its mesoscopic structure: while at the higher temperatures water is a uniform media (amorphous state), at the temperatures below transition it consists of many nano-to-micro-scale clusters (crystalline state). This transition is similar to the second order phase transition. In the present paper we propose that treating water with non-thermal plasma (adding plasma-created active compounds) can lower the temperature of the transition and thus cause a significant change in such physical quantities as surface tension, viscosity, freezing rate, and wettability and washability.

He, Jinjie↗

Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors

Secondary metabolites (SMs) are biologically active small molecules, many of which are medically valuable. Fungal genomes contain vast numbers of SM biosynthetic gene clusters (BGCs) with unknown products, suggesting that huge numbers of valuable SMs remain to be discovered. It is challenging, however, to identify SM BGCs, among the millions present in fungi, that produce useful compounds. One solution is resistance gene-guided genome mining, which takes advantage of the fact that some BGCs contain a gene encoding a resistant version of the protein targeted by the compound produced by the BGC. The bioinformatic signature of such BGCs is that they contain an allele of an essential gene with no SM biosynthetic function, and there is a second allele elsewhere in the genome. We have developed a computer-assisted approach to resistance gene-guided genome mining that allows users to query large databases for BGCs that putatively make compounds that have targets of therapeutic interest. Working with the MycoCosm genome database, we have applied this approach to look for SM BGCs that target the proteasome β6 subunit, the target of the proteasome inhibitor fellutamide B, or HMG-CoA reductase, the target of cholesterol reducing therapeutics such as lovastatin. Our approach proved effective, finding known fellutamide and lovastatin BGCs as well as fellutamide- and lovastatin-related BGCs with variations in the SM genes that suggest they may produce structural variants of fellutamides and lovastatin. Gratifyingly, we also found BGCs that are not closely related to lovastatin BGCs but putatively produce novel HMG-CoA reductase inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

Development of LpxH Inhibitors Chelating the Active Site Dimanganese Metal Cluster of LpxH

Abstract Despite the widespread emergence of multidrug‐resistant nosocomial Gram‐negative bacterial infections and the major public health threat it brings, no new class of antibiotics for Gram‐negative pathogens has been approved over the past five decades. Therefore, there is an urgent medical need for developing effective novel antibiotics against multidrug‐resistant Gram‐negative pathogens by targeting previously unexploited pathways in these bacteria. To fulfill this crucial need, we have been investigating a series of sulfonyl piperazine compounds targeting LpxH, a dimanganese‐containing UDP‐2,3‐diacylglucosamine hydrolase in the lipid A biosynthetic pathway, as novel antibiotics against clinically important Gram‐negative pathogens. Inspired by a detailed structural analysis of our previous LpxH inhibitors in complex with K. pneumoniae LpxH ( Kp LpxH), here we report the development and structural validation of the first‐in‐class sulfonyl piperazine LpxH inhibitors, JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ), that achieve chelation of the active site dimanganese cluster of Kp LpxH. The chelation of the dimanganese cluster significantly improves the potency of JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ). We expect that further optimization of these proof‐of‐concept dimanganese‐chelating LpxH inhibitors will ultimately lead to the development of more potent LpxH inhibitors for targeting multidrug‐resistant Gram‐negative pathogens.

Pharmacology & Pharmacy↗

Intrinsic Bonding and Reactivity of Actinide Clusters Poster

The effect of electronic structure on chemical bonding and reactivity is one of the most important questions in the field of chemistry. Insight into chemical bond formation involving elements that contain f electrons (i.e., the lanthanides and actinides) is critical for solving specific technical challenges, such as development of advanced nuclear fuel cycles and efficient rare earth separations, as well as a broader understanding of bonding across the entire periodic table. The primary technique for studying the fundamentals of lanthanide and actinide bonding is crystallization of metal-ligand compounds followed by structural determination with X-rays and comparison to theory with computational chemistry. While this procedure has yielded significant insights for a wide variety of elements, it is challenging to apply to the heavier trans-uranic actinides such as berkelium and californium because of limited material availability, significant radioactivity, and poorly understood chemical reactivity of these elements. We hypothesize that by forming actinide-ligand clusters in a mass spectrometer and probing their reactivity in the gas-phase, many of the challenges associated with studying the heavier trans-uranic elements can be circumvented. This project will develop a capability to address a wide range of actinide bonding and reactivity phenomena, increasing Idaho National Laboratory’s capability to address fundamental questions at the forefront of heavy element chemical and molecular science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects’ hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

59 BASIC BIOLOGICAL SCIENCES↗

Alkali Counterion-Dependent Crystallization of Uranium(IV)–Chloro Structural Units

The synthesis, structural characterization, and spectroscopic properties of five tetravalent uranium (U) phases including Li 6 [U 4 (μ 3 -O) 2 Cl 18 (H 2 O) 2 ]·10H 2 O (1), [U(H 2 O) 4 Cl 4 ] (2), [U(H 2 O) 4 Cl 4 ]·KCl (3), Rb 2 UCl 6 (4), and Cs 2 UCl 6 (5) are reported. Notably, a change in the U 4+ solid-state structural unit was observed based on the identity of the alkali counterion used in the synthesis. Li 1+ yielded a tetranuclear oxo-bridged cluster, [U 4 (μ 3 -O) 2 Cl 18 (H 2 O) 2 ] 6– , Na 1+ and K 1+ yielded two structurally distinct [U(H 2 O) 4 Cl 4 ] complexes, and Rb 1+ and Cs 1+ resulted in [UCl 6 ] 2– as the dominant phases. The spectroscopic properties of the compounds were analyzed using Raman and UV–vis–NIR absorption spectroscopy. The UV–vis–NIR spectra of compounds 1–5 exhibited transitions consistent with uranium in the +4 oxidation state. Clear differences in the absorption band splitting were observed and are likely attributed to differences in metal ion coordination, crystal field effects, and outer sphere interactions Overall, this work demonstrates the utility of noncovalent interactions in tuning the crystallization of various metal complexes from otherwise identical reaction solutions and provides further evidence that counterions impact the composition and structure of actinide complexes isolated in the solid state. In this way, this work affords important insight into directing and controlling the structure of actinide complexes and clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗