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At least 217 records · Page 12

On-Demand Designing of Cathode Internal Surface Architecture for Dramatic Enhancement of SOFC Performance and Durability

This project is aimed to design and modify the internal surfaces of porous composite cathode from currently commercially viable Solid Oxide Fuel Cells (SOFCs), using additive manufacturing process of Atomic Layer Deposition (ALD). The material systems being investigated are commercial composite electrodes complex three-dimensional topographies. In term of the chemistry of the ALD layer applied on the internal surface of the porous cathode, this project has employed commercially relevant electrolyte, electrocatalyst and noble metal materials set. Such materials are fully compatible with the commercial fuel cells, and this project has developed special nanostructure on the surface of the commercial composite cathodes. The formation of the designed nanoarchitecture on the surface of SOFC cathode has been achieved through precise control of ALD parameters and their effect on overall cell performance and resultant electrochemical reaction mechanism of cathodes has been investigated through full cell electrochemical performance testing and nanostructure characterization by transmission electron microscopy (TEM). Under the support of this award, following has been achieved: (1). For cathode materials in solid oxide fuel cells (SOFCs), such as perovskite mixed conductor La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-x (LSCF), cation surface segregation and consequently losing conductivity and active sites for the oxygen reduction reaction (ORR) are problematic. To mitigate the cation segregation and enhance SOFC durability, further decorating the internal backbone surface using the desired electrocatalysts could be a promoting approach. Commonly, the cation segregation such as Sr is very volatile, so the effective surface decoration is ideally conformal. Nevertheless, the conformal surface coating would inevitably alter the ORR pathways that initially take place on the surface of the backbone. To reveal the impact of the conformal coating on both the catalytic activity and the conductivity of the cathode, the unary electrocatalyst of Pt or CoO x , was applied to the LSCF/SDC composite electrode of inherently functional SOFCs, respectively. Both ALD coating layers evolve strong interaction with the LSCF composite cathode. Upon operations, the Pt coating layer remains conformal on LSCF grain surfaces but turns into discrete particles on SDC grain surfaces. Meanwhile, CoO x conformal coating grows to be the discrete nanograins on both the LSCF and SDC grains. ALD coating of the cathode alone reduces the ohmic resistance up to 28 % for the entire cells. The increased conductivity induced by the ALD coating of Pt or CoO x is ascribed to different mechanisms. For the inherent functional SOFCs, the present study presents a novel and feasible approach to apply a conformal, dense coating layer on the surface of a mixed conductor, simultaneously increasing the conductivity and durability of the SOFC cathode. (2). High resistance of the oxygen electrode still significantly hinders the state-of-the-art Solid Oxide Fuel Cells (SOFCs). In particular, for an oxygen electrode consisting of mixed electronic and ionic conductors, such as perovskite lanthanum strontium cobalt ferrite (LSCF), it deteriorates due to its low chemical stability of the grain surface. Such degradation is often associated with the segregation of cations. To prevent the cation surface segregation and its resultant perovskite phase decomposition, we demonstrate a conformal ultra-thin (7-10 nm) surface heterogeneous coating layer consisting of subjacent discrete Pt nanoparticles capped with a superjacent fully dense conformal CoO x layer. The performance studies indicate the ALD coating reduces the cell series resistance by up to 40 %. The conformal CoO x layer consists of randomly orientated but single-layered nanograins, with high-density intergranular and surface grain boundaries serving as the electrochemical reaction sites and facilitating mass transport. The conformal coating layer appears to have successfully suppressed the Sr outward diffusion and confined the Sr enriched layer to a ~ 2 nm interface perovskite phase between the coating layer and the LSCF grain surface. Moreover, this ultra-thin Sr enriched perovskite layer presumably possesses high oxygen vacancy and high ionic conductivity and further imposes tensile strain to the LSCF grain surfaces. With the combination of a conformal CoO x nanoionics, Sr enriched layer, and its strained interface, the ALD coating induced surface layer is estimated to have a conductivity of ~ 1.27x10 4 S/cm, which is over two orders magnitude of that from LSCF at 750 ºC.

30 DIRECT ENERGY CONVERSION↗

Photo-Curing 3D Printing of Thermosetting Sacrificial Tooling for Fabricating Fiber-Reinforced Hollow Composites

Carbon fiber-reinforced hollow composites play a vital role in lightweighting modern cars and aircrafts. Fabrication of such hollow composites with seamless internal finish requires sacrificial tooling that can be used under pressure and high temperature. For the very first time, high performance sacrificial tooling that can be used to fabricate fiber-reinforced hollow composites is produced using photocuring 3D printing technology. This is achieved by developing UV-curable resins containing highly soluble yet hydrolysable acetal acrylate cross-linker and hydrophilic 4-acryloylmorpholine monomer. It is found that the cross-linker content greatly affects the printing speed. Further, the widely adopted UV post-curing method is found to have negligible impact on improving the thermal-mechanical properties of printed structures. Additionally, after thermal post-treatment, printed sacrificial tooling exhibits a heat deflection temperature of 112 °C at 0.455 MPa and an average coefficient of linear thermal expansion of 59 ppm °C -1 between 30 and 100 °C. As a result, printed tooling enables fabrication of carbon fiber-reinforced hollow composites with complex geometry, which shows a tensile strength of 802 MPa and an elastic modulus of 50.2 GPa.

36 MATERIALS SCIENCE↗

Land cover and space use influence coyote carnivory: evidence from stable-isotope analysis

For many species, the relationship between space use and diet composition is complex, with individuals adopting varying space use strategies such as territoriality to facilitate resource acquisition. Coyotes ( Canis latrans ) exhibit two disparate types of space use; defending mutually exclusive territories (residents) or moving nomadically across landscapes (transients). Resident coyotes have increased access to familiar food resources, thus improved foraging opportunities to compensate for the energetic costs of defending territories. Conversely, transients do not defend territories and are able to redirect energetic costs of territorial defense towards extensive movements in search of mates and breeding opportunities. These differences in space use attributed to different behavioral strategies likely influence foraging and ultimately diet composition, but these relationships have not been well studied. We investigated diet composition of resident and transient coyotes in the southeastern United States by pairing individual space use patterns with analysis of stable carbon (δ 13 C) and nitrogen (δ 15 N) isotope values to assess diet. During 2016–2017, we monitored 41 coyotes (26 residents, 15 transients) with GPS radio-collars along the Savannah River area in the southeastern United States. We observed a canopy effect on δ 13 C values and little anthropogenic food in coyote diets, suggesting 13 C enrichment is likely more influenced by reduced canopy cover than consumption of human foods. We also observed other land cover effects, such as agricultural cover and road density, on δ 15 N values as well as reduced space used by coyotes, suggesting that cover types and localized, resident-like space use can influence the degree of carnivory in coyotes. Finally, diets and niche space did not differ between resident and transient coyotes despite differences observed in the proportional contribution of potential food sources to their diets. Although our stable isotope mixing models detected differences between the diets of resident and transient coyotes, both relied mostly on mammalian prey (52.8%, SD = 15.9 for residents, 42.0%, SD = 15.6 for transients). Resident coyotes consumed more game birds (21.3%, SD = 11.6 vs 13.7%, SD = 8.8) and less fruit (10.5%, SD = 6.9 vs 21.3%, SD = 10.7) and insects (7.2%, SD = 4.7 vs 14.3%, SD = 8.5) than did transients. Our findings indicate that coyote populations fall on a feeding continuum of omnivory to carnivory in which variability in feeding strategies is influenced by land cover characteristics and space use behaviors.

59 BASIC BIOLOGICAL SCIENCES↗

Sol–Gel‐Based Advanced Porous Silica Materials for Biomedical Applications

Abstract Porous silica‐based materials have burgeoning applications ranging from fillers and additives, to adsorbents, catalysts, and recently therapeutic agents and vaccines in nanomedicine. The preponderance of these materials is made by sol–gel processing wherein soluble silica precursors are reacted to form amorphous networks composed of siloxane bonds. The facile sol–gel approach allows for an unlimited variety of binary tertiary and more complex chemical compositions including organic ligands and networks resulting in so‐called organic–inorganic hybrid materials. Here, a brief review of the recent progress in sol–gel‐derived silica materials prepared as particles, thin films, biosilica/silica bioreplicas (of molecules, cells and organisms), and their related preparation, properties, and bioapplications is provided. First, it highlights the recent achievements of mesoporous silica nanoparticles in biomedical applications, including therapeutic agent delivery, multimodal imaging and theranostics, and bone tissue engineering and repair. Second, the research in evaporation‐induced self‐assembly (EISA)‐based mesostructured silica thin films and cell‐directed EISA in bio/nano interfaces for various bioapplications, such as bioactive coatings, biosensing, and living cell immobilization, has been reviewed. Third, the pioneering work in biomimetic silicification/immobilization of biomolecules and bio‐organisms and silica bioreplication of complex bio‐organisms is summarized. Finally, it is concluded with personal perspectives on the directions of future work on this field.

Lei, Qi↗

Micropolar deep material network

This study extends the Deep Material Network (DMN), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (Cosserat-type) constitutive behavior. This extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. While traditional, direct numerical simulation micropolar models effectively capture size effects by introducing extra local degrees of freedom, they bring significant computational challenges, particularly for multiscale analyses relevant to engineering applications. The micropolar DMN developed in this paper achieves high accuracy while significantly reducing computation time compared to micropolar direct numerical simulations. This advancement enables multiscale analyses and parameter studies that were previously impractical, such as high-cycle fatigue simulations and comprehensive investigations of internal length scale effects notably in size-dependent plastic response and the optimization of lattice structures. By uniting microstructure-sensitive modeling, physics-driven learning, and scalable surrogate modeling, the micropolar DMN paves the way for accelerated material design, large-scale parametric studies, and the reliable incorporation of size-dependent effects across a wide range of engineering applications, including optimization and next-generation composite design.

36 MATERIALS SCIENCE↗

Disulfonamide Ligands as f-Element Extractants from Alkaline High-Level Waste

Almost 100 million gallons of high level waste (HLW) has been generated from defense reprocessing programs to support nuclear weapons production. HLW is currently stored at the Hanford and Savannah River Sites (SRS) [1]. It contains radioactive components, such as {sup 137}Cs, {sup 99}Tc and {sup 90}Sr, as well as large amounts of non-radioactive species, including solvated cations and insoluble metal hydroxides. HLW has high concentration of soluble hydroxides ([OH{sup -}] = 2 M at SRS [2]), complexing inorganic anions ([NO{sub 3}{sup -}] ∼ 0.65 - 3.7 M at SRS [2]) and a high ionic strength. Even though the majority of actinide component in alkaline HLW is precipitated, studies of An(III) and Ln(III) complexation in highly alkaline solutions in the presence of high nitrate concentrations have showed that soluble nitrate complexes can be formed [3]. The current treatment of HLW at SRS currently consists of two processes: The Actinide Removal Process (ARP) and the Next-Generation Caustic-Side Solvent Extraction process (NG-CSSX). Strontium and actinides are removed by sorption on monosodium titanate through the Actinide Removal Process (ARP) commonly referred to as the alpha-strike step [4]. Then, cesium is selectively extracted from the alkaline media via the Caustic-Side Solvent Extraction (CSSX) process [5]. The CSSX solvent consists of a calix[4]arene-crown-6 extractant dissolved in an inert hydrocarbon matrix containing i) a solvent modifier (alkylphenoxy alcohol) which increases extractant solubility and prevents third phase formation, and ii) a suppressor (trioctylamine or guanidine) - that mitigates surfactant effects. The CSSX process removes {sup 137}Cs selectively and rapidly, yet the post- CSSX aqueous stream may still contain high amounts of An, thus requiring a second ARP treatment (referred to as 'alpha-finishing') for some tanks. Despite the success of the ARP process in removing Sr and An, it often represents the kinetic bottleneck of integrated processing, as it is slower than solvent extraction. Understanding the complexation of actinides by organic ligands that are compatible with the CSSX process could eventually lead to a combined caustic-side Cs/Sr/actinide extraction process with better economics due to a reduced amount of monosodium titanate and/or a shorter required contact time with titanate during ARP. This would ensure a low-activity waste (LAW) stream with no actinides without additional ARP processing post-CSSX. Disulfonamides were studied for extraction of Sm(III) from alkaline aqueous media of pH 10-14 into dichloromethane. Up to 82% of Sm(III) was extracted from solutions of pH 12.5 -13.5 and up to 84% from solutions of pH 10.5 - 11.5. These results show some resemblance with Am extraction results by calixarene ligands previously reported [10]. Kinetic studies demonstrated that even 5 min is enough to complete stripping, whereas extraction is time-limiting process and requires up to 20 h for efficient removal of Sm(III) from alkaline aqueous media. Determination of composition of complexes in solution after extraction by the equilibrium shift method showed a 1:1 Sm(III):dsa-2 complexation ratio for the extracted species.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗

Heterogeneous Composition of Oxygen-Evolving Complexes in Crystal Structures of Dark-Adapted Photosystem II

Photosystem II (PSII) is a homodimeric protein complex that catalyzes water oxidation at the oxygen-evolving complex (OEC), a heterocubanoid calcium-tetra-manganese cluster. Here, we analyze the omit electron-density peaks of the OEC’s metal ions in five X-ray free-electron laser PSII structures at a resolution between 2.15 Å and 1.95 Å. The omit peaks can be described by the total number of electrons and approximated by the variance of electron density distribution when the distributions are spherically symmetric. We show that the number of electrons of metal centers are different in the two OECs of PSII dimers, implying that either the oxidation states and/or occupancies of individual metal ions are different in the two monomers. In either case, we find that the two OECs of dark-adapted PSII dimers in crystals are not fully synchronized in the same expected S 1 state. Differences in redox states of the OEC in PSII only partially account for the observation that the electron densities integrate to a smaller number of electrons than expected. Differences between the determined and expected relative electron numbers are much larger than the estimated errors, indicating heterogeneity in the OEC composition. Here, the reported findings suggest that two OECs of dark-adapted PSII crystals are typically not fully synchronized in the S 1 state and likely generate heterogeneity in the crystallographical data of PSII intermediate structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiscale porosity characterization in additively manufactured polymer nanocomposites using micro-computed tomography

Extrusion-based additive manufacturing (AM) of polymer composites exhibits complex thermally driven phenomena that introduce severe discontinuities in the internal structure across length scales, especially voids or porosity. This study utilizes a high-throughput porosity characterization technique to analyze large datasets from numerous micro-computed tomography (mu CT) scans to capture the influence of AM print parameters on the size, shape, and location of porosity across multiple print layers (up to a few cm) on fused granular fabrication (FGF) printers. The materials investigated include nanocomposite formulations based on commercially relevant nylon-12 and polyether ketone ketone (PEKK) materials comprising nano- or micro- sized fillers. The estimated global porosity follows an inverse linear correlation against the bulk density of the printed samples. Increasing the extrusion multiplier (EM) and the nozzle temperature while decreasing the print speeds reduces the global porosity. Outlier analyses (local porosity morphology) show that faster print speeds and higher extrusion rates result in long, slender inter-layer voids, while lower nozzle temperatures lead to large, symmetrical, inter-bead voids (at the bead junction). Lack of active chamber temperature increases inter-layer and intra-bead voids with a two-fold increase in global porosity. Overall, the micro filler-reinforced composites exhibit higher global porosity than nanofiller-reinforced composites, which is attributed to the increased mismatch in the thermal expansion coefficient between the filler and the polymers used in the study.

36 MATERIALS SCIENCE↗

Dissecting the structural heterogeneity of proteins by native mass spectrometry

Abstract A single gene yields many forms of proteins via combinations of posttranscriptional/posttranslational modifications. Proteins also fold into higher‐order structures and interact with other molecules. The combined molecular diversity leads to the heterogeneity of proteins that manifests as distinct phenotypes. Structural biology has generated vast amounts of data, effectively enabling accurate structural prediction by computational methods. However, structures are often obtained heterologously under homogeneous states in vitro. The lack of native heterogeneity under cellular context creates challenges in precisely connecting the structural data to phenotypes. Mass spectrometry (MS) based proteomics methods can profile proteome composition of complex biological samples. Most MS methods follow the “bottom‐up” approach, which denatures and digests proteins into short peptide fragments for ease of detection. Coupled with chemical biology approaches, higher‐order structures can be probed via incorporation of covalent labels on native proteins that are maintained at the peptide level. Alternatively, native MS follows the “top‐down” approach and directly analyzes intact proteins under nondenaturing conditions. Various tandem MS activation methods can dissect the intact proteins for in‐depth structural elucidation. Herein, we review recent native MS applications for characterizing heterogeneous samples, including proteins binding to mixtures of ligands, homo/hetero‐complexes with varying stoichiometry, intrinsically disordered proteins with dynamic conformations, glycoprotein complexes with mixed modification states, and active membrane protein complexes in near‐native membrane environments. We summarize the benefits, challenges, and ongoing developments in native MS, with the hope to demonstrate an emerging technology that complements other tools by filling the knowledge gaps in understanding the molecular heterogeneity of proteins.

59 BASIC BIOLOGICAL SCIENCES↗

FREDA: A Web Application for the Processing, Analysis, and Visualization of Fourier‐Transform Mass Spectrometry Data

The high-resolution measurement capability of Fourier-transform mass spectrometry (FT-MS) has made it a necessity for exploring the molecular composition of complex organic mixtures, like soil, plant, aquatic, and petroleum samples. This demand has driven a need for informatics tools to explore and analyze FT-MS data in a robust and reproducible manner. FREDA is an interactive web application developed to enable spectrometrists to format, process, and explore their FT-MS data without the need for statistical programming expertise. FREDA was built to explore outputs from a molecular identification tool, like CoreMS, and provide a suite of methods to filter data, compute chemical properties of peaks, statistically compare samples and groups of samples, conduct exploratory data analysis, and download the results with a report detailing all steps conducted. To demonstrate the utility of FREDA, an example analysis was conducted using FT-MS data from a soil microbiology study of samples collected in two different soil depths at the Sphagnum bog forest north of Grand Rapids, Minnesota. Differences between the two depths are observed using Kendrick, Gibbs free energy, and van Krevelen plots. G-tests are used to quantify a significant difference between the groups. All analyses and plotting are conducted using only the FREDA application. FREDA is an open-source and readily available web application that allows users to explore and make statistically valid conclusions about their FT-MS data. The application is available online (https://map.emsl.pnnl.gov/app/freda) with a tutorial web series (https://youtu.be/k5HLE2kNSBY?si=yB6sGoyvzxrFf5MP) and freely accessible code on Github (https://github.com/EMSL-Computing/FREDA).

47 OTHER INSTRUMENTATION↗

Microstructure and corrosion of CrFeMnV multi-principal element alloy

In this study, a multi-principal element alloy consisting of equiatomic concentrations of Cr, Fe, Mn, and V was produced by arc melting. The combination of X-ray diffraction, scanning electron microscopy and energy-dispersive X-ray spectroscopy indicated that the CrFeMnV MPEA was comprised of a BCC matrix with a dispersion of a secondary phase. Cyclic potentiodynamic polarization tests in 0.6M NaCl revealed high corrosion resistance – superior to that of stainless steel 304L, as evident from high breakdown and repassivation potentials. X-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry provided insight into the formed multi-layer surface film after constant immersion and potentiostatic conditioning.

36 MATERIALS SCIENCE↗

A Novel Zwitterionic Chromatography Approach to Separate Lithium from Unconventional Resources

Lithium (Li) is a key element for clean energy technologies, and, accordingly, the global lithium demand has been increasing rapidly. Therefore, to meet the Li demand and maintain supply chain stability, it is critical to develop efficient lithium extraction technologies that allow exploitation of unconventional lithium resources, such as geothermal brines and inland brine streams. However, the recovery of Li from these resources is challenging due to low Li concentration, low ratios of Li/Na, Li/Mg, or Li/Ca, and complex feed compositions. To address this, we introduced a new Direct Lithium Extraction (DLE) process using Zwitterionic Chromatography (ZIC) to separate Li from other salts. Since salts are partitioned on ZIC under water elution, no reagent chemicals are needed, and the Li separation is not limited by the adsorption capacity. We prepared 13 different zwitterionic (ZI) resins to investigate the salt retention on various ZI groups and then screened out promising sorbents for efficient Li separation. It was found that salt retention was synergistically affected by the pore size and ZI configurations. Using carboxybetaine (QAC3CA) sorbents, multicomponent separations showed that Li can be partitioned from divalent salts or Na with selectivities of 1.8 or 1.9, respectively. Although the selectivity is relatively low, in real brine tests, Li was separated from Ca and Mg with 79.2 % yield, showing the potential for a continuous process to achieve high productivity and high yield. Simulation studies suggest the salt elution mechanism is related to the hydration reaction energy and the effective hydrated radius of cations.

critical minerals↗

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation, and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to ‘omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Furthermore, thus far, BP4NTA group members have aimed to establish consensus on NTA-related terms and concepts, and to create consistency in reporting practices by providing resources on a public website, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing Electrochemical Mg-Ion Activity in MgCr 2– x V x O 4 Spinel Oxides

Mg migration in oxide spinels is impeded by strong affinity between divalent Mg and oxygen, suggesting a necessity of exploring new chemistry of solid lattices for functional Mg-ion electrode materials. Cationic mobility with a suitable activation energy in Cr spinels is Tn. evidenced by theoretical and experimental results, while redox potentials of V are appropriate to operate with currently limited candidates of '''c" nonaqueous electrolytes. By controlling the structure, composition, and complexity, a largely solid-solution MgCrVO 4 spinel was synthesized, which, unlike nanocornposites, can bring together the advantages of each transition metal in the lattice. The spinel was successfully synthesized by a simple solid-state reaction with minor inactive Cr- or V-rich components, which was confirmed via 25 Mg MAS NMR and high-resolution X-ray diffraction analyses. A thermally and anodically stable Mg(TPFA) 2 /triglyme electrolyte was utilized for high-temperature electrochemistry and lowering kinetic barriers at and across interfaces so as to observe intercalation behavior of Mg in the designed lattice. Multimodal characterization confirmed an apparent bulk demagnesiation from MgCrVO 4 with partial reversibility by probing evolution of the local and long-range structure as well as vanadium and chromium electronic states within the lattice. Furthermore, characterization experiments also provided a direct evidence for (de)intercalation reactions that occurred without any major competitive conversion reactions or insertion of protons into the lattice, except for the formation of a surface rock salt phase upon charge. These findings in Mg-ion activity expand opportunities to design Mg spinel oxide materials while highlighting the need to identify the origins of reversibility challenges due to, but not limited to, phase stability, particularly for the charged states, barriers at the interface, electrolyte stabilities, and desolvation phenomena, collectively hindering practical use as cathode materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics and exposomics studies is to fully characterize the small molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversi-ty present within the metabolome and exposome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials (“standards”), which are not available for most molecules. Computational quantum chemis-try methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alter-native route for building reference libraries, i.e., in silico libraries for “standards-free” identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solu-tion. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectros-copy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics and exposomics studies. We expect this review will inspire researchers in the field of small molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Metabolism↗

Eutectic Processing of Semiconductor Colloidal Nanocrystals for Energy Applications

Colloidal semiconductor nanocrystals (NCs) offer a costeffective platform for light-energy conversion in X-ray scintillators, photovoltaics, lasers, and display technologies. Yet, device-relevant NCs often require complex heterostructured compositions, where lattice imperfections compromise the efficiency and stability of photoconversion processes. Here, we show that a simple synthetic detour through a eutectic state of II−VI semiconductor NCs (e.g., CdSe, ZnSe) with halide salts (e.g., CdCl 2 , ZnCl 2 ) overcomes this limitation by melting and reconstructing NC lattices into defect-free alloyed and core/shell architectures. Applied to ternary CdSeTe NCs, this process produces downconverters with record brightness and minimal line widths, delivering a 3-fold increase in film-side external quantum efficiency of commercial CdTe photovoltaic modules (First Solar Inc.). Meanwhile, eutectic processing of CdSe-based core/shell emitters yields an 8-fold enhancement in their photoluminescence stability under backlight operation, addressing the reliability bottleneck for display technologies. Together, these findings establish eutectic NC processing as a scalable route to efficient, durable photoconversion materials for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗