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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Building Durable Multimetallic Electrocatalysts from Intermetallic Seeds

When combined with earth-abundant metals, Pt-based alloy nanoparticles (NPs) can be cost-effective electrocatalysts. However, these NPs can experience leaching of non-noble-metal components under harsh electrocatalytic conditions. In this work, the Skrabalak group has demonstrated a novel NP construct in which Pt-based random alloy surfaces are stabilized against non-noble-metal leaching by their deposition onto intermetallic seeds. These core@shell NPs are highly durable electrocatalysts, with the ability to tune catalytic performance by the core@shell architecture, surface alloy composition, and NP shape. This versatility was demonstrated in a model system in which random alloy (ra-) PtM surfaces were deposited onto ordered intermetallic (i-) PdCu seeds using seed-mediated co-reduction (SMCR). In the initial demonstration, ra-PtCu shells were deposited on i-PdCu seeds, with these core@shell NPs exhibiting higher specific and mass activities for the oxygen reduction reaction (ORR) when compared to similarly sized ra-PtCu NPs. These NPs also showed outstanding durability, maintaining ~85% in specific activity after 5000 cycles. Characterization of the NPs after use revealed minimal loss of Cu. The activity enhancement was attributed to the strained surface that arises from the lattice mismatch between the intermetallic core and random alloy surface. The outstanding durability was attributed to the ordered structure of the intermetallic core. The origin of this durability enhancement was investigated by classical molecular dynamics simulations, where Pt atoms were found to have a lower potential energy when deposited on an intermetallic core than when deposited on a random alloy core. Also, ordering of Cu atoms at the core@shell interface appears to enhance the overall binding between the core and the shell materials. Inspired by this initial demonstration, SMCR has been used to achieve shells of different random alloy compositions, PtM (M = Ni, Co, Cu, or Fe). This advance is significant because ligand effects vary as a function of PtM identity and Pt/M ratio. These features also influence the degree of surface strain imparted from the lattice mismatch between the core and shell materials. Like the initial demonstration, standout features of these core@shell NPs were high durability and resistance to non-noble metal leaching. Moving forward, efforts have been directed toward integrating shape-control to this core@shell NP construct. This integration is motivated by the shape-dependent catalytic performance of NPs derived from the selective expression of specific facets. Considering the initial i-PdCu@ra-PtCu system, NPs with a cubic shape have been achieved by judicious selection of capping ligands during SMCR. Evaluation of these NPs as catalysts for the electrooxidation of formic acid found that the nanocubic shape enhances catalytic performance compared to similar core@shell NPs with a spherical morphology. We envision that SMCR can be applied to other NP systems to achieve highly durable catalysts as the syntheses of monodisperse and shape-controlled intermetallic seeds are advanced. This Account highlights the role of intermetallic cores in providing more durable electrocatalysts. More broadly, the versatility of SMCR is highlighted as a route to integrate architecture, alloy surfaces, and shape within one NP system, and how this achievement is inspiring new high-performance and robust catalysts is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Importance of Engineered and Learned Molecular Representations in Predicting Organic Reactivity, Selectivity, and Chemical Properties

Machine-readable chemical structure representations are foundational in all attempts to harness machine learning for the prediction of reactivities, selectivities, and chemical properties directly from molecular structure. The featurization of discrete chemical structures into a continuous vector space is a critical phase undertaken before model selection, and the development of new ways to quantitatively encode molecules is an active area of research. Here, we highlight the application and suitability of different representations, from expert-guided “engineered” descriptors to automatically “learned” features, in different prediction tasks relevant to organic and organometallic chemistry, where differing amounts of training data are available. These tasks include statistical models of stereo- and enantioselectivity, thermochemistry, and kinetics developed using experimental and quantum chemical data. The use of expert-guided molecular descriptors provides an opportunity to incorporate chemical knowledge, domain expertise, and physical constraints into statistical modeling. In applications to stereoselective organic and organometallic catalysis, where data sets may be relatively small and 3D-geometries and conformations play an important role, mechanistically informed features can be used successfully to obtain predictive statistical models that are also chemically interpretable. We provide an overview of several recent applications of this approach to obtain quantitative models for reactivity and selectivity, where topological descriptors, quantum mechanical calculations of electronic and steric properties, along with conformational ensembles, all feature as essential ingredients of the molecular representations used. Alternatively, more flexible, general-purpose molecular representations such as attributed molecular graphs can be used with machine learning approaches to learn the complex relationship between a structure and prediction target. This approach has the potential to out-perform more traditional representation methods such as “hand-crafted” molecular descriptors, particularly as data set sizes grow. One area where this is particularly relevant is in the use of large sets of quantum mechanical data to train quantitative structure–property relationships. A general approach toward curating useful data sets and training highly accurate graph neural network models is discussed in the context of organic bond dissociation enthalpies, where this strategy outperforms regression using precomputed descriptors. Finally, we describe how graph neural network predictions can be incorporated into mechanistically informed statistical models of chemical reactivity and selectivity. Once trained, this approach avoids the expensive computational overhead associated with quantum mechanical calculations, while maintaining chemical interpretability. We illustrate examples for which fast predictions of bond dissociation enthalpy and of the identities of radicals formed through cleavage of a molecule’s weakest bond are used in simple physical models of site-selectivity and reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Engineering Catalyst–Electrolyte Microenvironments to Optimize the Activity and Selectivity for the Electrochemical Reduction of CO 2 on Cu and Ag

We report the electrochemical reduction of carbon dioxide (CO 2 R) driven by renewably generated electricity (e.g., solar and wind) offers a promising means for reusing the CO 2 released during the production of cement, steel, and aluminum as well as the production of ammonia and methanol. If CO 2 could be removed from the atmosphere at acceptable costs (i.e., <$100/t of CO 2 ), then CO 2 R could be used to produce carbon-containing chemicals and fuels in a fully sustainable manner. Economic considerations dictate that CO 2 R current densities must be in the range of 0.1 to 1 A/cm 2 and selectivity toward the targeted product must be high in order to minimize separation costs. Industrially relevant operating conditions can be achieved by using gas diffusion electrodes (GDEs) to maximize the transport of species to and from the cathode and combining such electrodes with a solid-electrolyte membrane by eliminating the ohmic losses associated with liquid electrolytes. Additionally, high product selectivity can be attained by careful tuning of the microenvironment near the catalyst surface (e.g., the pH, the concentrations of CO 2 and H 2 O, and the identities of the cations in the double layer adjacent to the catalyst surface).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Controlling Symmetry Breaking Charge Transfer in BODIPY Pairs

Symmetry breaking charge transfer (SBCT) is a process in which a pair of identical chromophores absorb a photon and use its energy to transfer an electron from one chromophore to the other, breaking the symmetry of the chromophore pair. This excited state phenomenon is observed in photosynthetic organisms where it enables efficient formation of separated charges that ultimately catalyze biosynthesis. SBCT has also been proposed as a means for developing photovoltaics and photocatalytic systems that operate with minimal energy loss. It is known that SBCT in both biological and artificial systems is in part made possible by the local environment in which it occurs, which can move to stabilize the asymmetric SBCT state. However, how environmental degrees of freedom act in concert with steric and structural constraints placed on a chromophore pair to dictate its ability to generate long-lived charge pairs via SBCT remain open topics of investigation. In this work we compare a broad series of dipyrrin dimers that are linked by distinct bridging groups to discern how the spatial separation and mutual orientation of linked chromophores and the structural flexibility of their linker each impact SBCT efficiency. Across this material set, we observe a general trend that SBCT is accelerated as the spatial separation between dimer chromophores decreases, consistent with the expectation that the electronic coupling between these units varies exponentially with their separation. However, one key observation is that the rate of charge recombination following SBCT was found to slow with decreasing interchromophore separation, rather than speed up. This stems from an enhancement of the dimers’ structural rigidity due to increasing steric repulsion as the length of their linker shrinks. This rigidity further inhibits charge recombination in systems where symmetry has already enforced zero HOMO-LUMO overlap. Additionally, for the forward transfer the active torsion is shown to increase LUMO-LUMO coupling, allowing for faster SBCT within bridging groups. Further, by understanding trends for how rates of SBCT and charge recombination depend on a dimer’s internal structure and their environment, we identify design guidelines for creating artificial systems for driving sustained light-induced charge separation. Such systems can find application in solar energy technologies and photocatalytic applications but can serve as a model for light-induced charge separation in biological systems.

14 SOLAR ENERGY↗
DOE OSTI2022

Hydrated Anions: From Clusters to Bulk Solution with Quasi-Chemical Theory

The interactions of hydrated ions with molecular and macromolecular solution and interface partners are strong on a chemical energy scale. Here we recount the foremost ab initio theory for the evaluation of the hydration free energies of ions, namely, quasi-chemical theory (QCT). We focus on anions, particularly halides but also the hydroxide anion, because they have been outstanding challenges for all theories. For example, this work supports understanding the high selectivity for F – over Cl – in fluoride-selective ion channels despite the identical charge and the size similarity of these ions. QCT is built by the identification of inner-shell clusters, separate treatment of those clusters, and then the integration of those results into the broader-scale solution environment. Recent work has focused on a close comparison with mass-spectrometric measurements of ion-hydration equilibria. We delineate how ab initio molecular dynamics (AIMD) calculations on ion-hydration clusters, elementary statistical thermodynamics, and electronic structure calculations on cluster structures sampled from the AIMD calculations obtain just the free energies extracted from the cluster experiments. That theory–experiment comparison has not been attempted before the work discussed here, but the agreement is excellent with moderate computational effort. This agreement reinforces both theory and experiment and provides a numerically accurate inner-shell contribution to QCT. The inner-shell complexes involving heavier halides display strikingly asymmetric hydration clusters. Asymmetric hydration structures can be problematic for the evaluation of the QCT outer-shell contribution with the polarizable continuum model (PCM). Nevertheless, QCT provides a favorable setting for the exploitation of PCM when the inner-shell material shields the ion from the outer solution environment. For the more asymmetrically hydrated, and thus less effectively shielded, heavier halide ions clustered with waters, the PCM is less satisfactory. We therefore investigate an inverse procedure in which the inner-shell structures are sampled from readily available AIMD calculations on the bulk solutions. This inverse procedure is a remarkable improvement; our final results are in close agreement with a standard tabulation of hydration free energies, and the final composite results are independent of the coordination number on the chemical energy scale of relevance, as they should be. Finally, a comparison of anion hydration structure in clusters and bulk solutions from AIMD simulations emphasize some differences: the asymmetries of bulk solution inner-shell structures are moderated compared with clusters but are still present, and inner hydration shells fill to slightly higher average coordination numbers in bulk solution than in clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Truncating 2D Framework Materials Down to a Single Pore: Synthetic Approaches and Opportunities

Here, in this Accounts article, we summarize our recent work on truncating conjugated two-dimensional framework materials down to a single pore, or a single macrocycle. Conjugated 2D architectures have emerged as one of the most synthetically adaptable motifs for coupling semiconductivity and porosity in metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). However, despite their prevalence, 2D architectures have several limitations. In particular, the strong interlayer π–π stacking can limit both processability and the accessibility of internal active sites. We have found that simple macrocycles preserve key aspects of 2D framework structure and function, including porosity and out-of-plane electrical conductivity, while providing improved processability, surface tunability, and mass transport properties. In this article, we first describe our synthetic approach and general design considerations. Specifically, we show how ditopic analogues of the tritopic ligands commonly found in the synthesis of 2D MOFs and COFs can be used to achieve a diverse library of conjugated macrocycles that resemble fragments of semiconducting frameworks in both form and function. The length of the peripheral side chains, the size of the aromatic core, and the solubility of intermediates are all key variables in favoring selective macrocycle formation over undesired linear polymers and oligomers. Next, we highlight the unique advantages that macrocycles provide, including improved processability, atomically precise surface tunability, and greater active site accessibility. In particular, the identity of the peripheral side chains dramatically impacts both solubility and colloidal stability as well as crystal size and morphology. We further show how the solution processability and nanoscale dimensions of macrocycles can simplify electronic device fabrication and improve electrochemical performance. Finally, we end with a forward-looking discussion on how macrocycles offer a unique bridge between conjugated molecules and extended frameworks, enabling new application areas and fundamental science.

charge transport↗
DOE OSTI2021

Single Quadrupole Multiple Fragment Ion Monitoring Quantitative Mass Spectrometry

Single quadrupole mass spectrometry (MS) with enhanced in-source multiple fragment ion monitoring was designed to perform high sensitivity quantitative mass analyses. Enhanced in-source fragmentation amplifies fragmentation from traditional soft electrospray ionization producing fragment ions that have been found to be identical to those generated in tandem MS. We have combined enhanced in-source fragmentation data with criteria established by the European Union Commission Directive 2002/657/EC for electron ionization single quadrupole quantitative analysis to perform quantitative analyses. These experiments were performed on multiple types of complex samples that included a mixture of 50 standards, as well as cell and plasma extracts. The dynamic range for these quantitative analyses was comparable to triple quadrupole multiple reaction monitoring (MRM) analyses at up to 5 orders of magnitude with the cell and plasma extracts showing similar matrix effects across both platforms. Amino acid and fatty acid measurements performed from certified NIST 1950 plasma with isotopically labeled standards demonstrated accuracy in the range of 91–110% for the amino acids, 76–129% for the fatty acids, and good precision (coefficient of variation <10%). To enhance specificity, a newly developed correlated ion monitoring algorithm was designed to facilitate these analyses. This algorithm autonomously processes, aligns, filters, and compiles multiple ions within one chromatogram enabling both precursor and in-source fragment ions to be correlated within a single chromatogram, also enabling the detection of coeluting species based on precursor and fragment ion ratios. Single quadrupole instrumentation can provide MRM level quantitative performance by monitoring/correlating precursor and fragment ions facilitating high sensitivity analysis on existing single quadrupole instrumentation that are generally inexpensive, easy to operate, and technically less complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Trace Impurities Identified as Forensic Signatures in CMX-5 Fuel Pellets Using X-ray Spectroscopic Techniques

We report that small-particle analysis is a highly promising emerging forensic tool for analysis of interdicted special nuclear materials. Integration of microstructural, morphological, compositional, and molecular impurity signatures could provide significant advancements in forensic capabilities. We have applied rapid, high-sensitivity, hard X-ray synchrotron chemical imaging to analyze impurity signatures in two differently fabricated fuel pellets from the 5th Collaborative Materials Exercise (CMX5) of the IAEA Nuclear Forensics International Working Group. The spatial distributions, chemical compositions, and morphological and molecular characteristics of impurities were evaluated using X-ray absorption near-edge structure (XANES) and X-ray fluorescence chemical imaging to discover principal impurities, their granularity, particle sizes, modes of occurrence (distinct grains vs incorporation in the UO 2 lattice), and sources and mechanisms of incorporation. Differences in UO 2+x stoichiometry were detected at the microscale in nominally identical UO 2 ceramics (CMX5-A and CMX5-B), implying the presence of multiple UO 2 host phases with characteristic microstructures and feedstock compositions. Al, Fe, Ni, W, and Zr impurities and integrated impurity signature analysis identified distinctly different pellet synthesis and processing methods. For example, two different Al, W, and Zr populations in the CMX5-B sample indicated a more complex processing history than the CMX5-A sample. K-edge XANES measurements reveal both metallic and oxide forms of Fe and Ni but with different proportions between each sample. Altogether, these observations suggest multiple sources of impurities, including fabrication (e.g., force-sieving) and feedstock (mineral oxides). This study demonstrates the potential of synchrotron techniques to integrate different signatures across length scales (angstrom to micrometer) to detect and differentiate between contrasting UO 2 fuel fabrication techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The NanoSIMS-HR: The Next Generation of High Spatial Resolution Dynamic SIMS

The high lateral resolution and sensitivity of the NanoSIMS 50 and 50L series of dynamic SIMS instruments have enabled numerous scientific advances over the past 25 years. Here, in this study, we report on the NanoSIMS-HR, the first major upgrade to the series, and analytical tests in a suite of sample types, including an aluminum sample containing silicon crystals, microalgae, and plant roots colonized with a symbiotic fungus. Significant improvements have been made in the Cs + ion source, high voltage (HV) control, stage reproducibility, and other aspects of the instrument that affect performance. The modified design of the NanoSIMS-HR thermal-ionization Cs + source enables a 5 pA primary ion beam to be focused into a 100 nm spot, a ~2.5-fold increase compared to Cs + sources on previous instruments (~2 pA at 100 nm). The brightness of the new Cs + source enables an ultimate lateral resolution as high as 30 nm and improved detection limits for a given analysis area. Sample stage movement accuracy is higher than 500 nm, enabling many-fold higher throughput automated analyses. With the new HV control, the primary ion beam impact energy can be reduced from 16 to 2 keV, which enables higher depth resolution during depth profiling (a 2-fold improvement), albeit with a 5-fold decrease in lateral resolution. In the NanoSIMS-HR, the secondary ion column and detection system are identical to those used in the previous series, and the isotopic analysis performance is as precise as in previous NanoSIMS instruments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗
DOE OSTI2026

Thermal Gradient Effects on Redox Evolution and Volatility-Driven Fractionation in Ternary U/Ce/Cs Condensates

Understanding how thermal history influences redox evolution and chemical fractionation is essential for characterizing high-temperature condensation in complex materials, including nuclear debris. Here, we tested the hypothesis that distinct thermal regimes in a plasma flow reactor influence redox pathways and elemental partitioning in ternary U/Ce/Cs systems. A configurable plasma flow reactor was modified with an external tube furnace to impose two distinct thermal gradients: continuous ambient cooling and a furnace-assisted thermal hold-up near 1400 K followed by rapid cooling. Transmission electron microscopy characterized phase identity, morphology, and nanoscale element distributions, while inductively coupled plasma-mass spectrometry quantified bulk elemental ratios. Across both thermal regimes, uranium and cerium condensed as UO 2 and CeO 2 as dominant refractory oxide products. Uranium partially oxidized to α-UO 3 during extended ambient cooling, while furnace-assisted hold-up preserved UO 2 and produced partial reduction of cerium to Ce 2 O 3 . Cesium remained volatile upstream and condensed later in the reactor, forming Cs 2 O and Cs-uranate phases with the highest incorporation after thermal hold-up. Bulk ICP-MS measurements supported these observations. U/Ce ratios remained comparatively stable and Cs displayed delayed and apparent transient enrichment that matched the nanoscale measurements. This integrated approach provides a quantitative method for linking thermal gradients to redox evolution and volatility-driven fractionation. These results show how the plasma flow reactor can identify where equilibrium descriptions remain adequate and where kinetic effects from residence time and temperature history must be considered when interpreting condensation behavior in multicomponent systems.

and nuclear chemistry↗
DOE OSTI2026

Position-Specific Carbon Isotope Fingerprinting of Fluorinated Organics and Degradation Products

Fluorinated organic compounds are of growing environmental and forensic relevance due to their widespread use in pharmaceuticals, agrochemicals, and consumer products, their environmental persistence, and potential ecological and human health impacts. Elucidating their sources and transformation pathways is therefore a major focus of current research. Stable carbon isotope analysis provides a powerful approach for tracing molecular origins and linking parent compounds to degradation products. Recent isotope measurements have largely relied on mass-spectrometry techniques, which provide only an average isotope ratio across a compound. In this work, we employ a novel nuclear magnetic resonance (NMR) spectroscopy tool to determine position-specific carbon isotope ratios ( 13 C/ 12 C) in organofluorine compounds and their degradation products. This approach enables isotope measurements without combustion or extensive purification and, crucially, resolves ratios at individual carbon positions rather than bulk averages. The resulting intramolecular isotope fingerprints are unique to a molecule’s source. Applied to selected pharmaceuticals and pesticides, these fingerprints allow discrimination of chemically identical compounds. Moreover, we show that the 13 C/ 12 C signature at the fluorinated carbon persists through degradation, demonstrated for lansoprazole and fipronil. The 19 F NMR data produced for the 13 C/ 12 C analyses are also well suited for impurity profiling, providing an additional dimension for fingerprinting fluorinated organics. These findings suggest that position-specific isotope analysis can serve as part of a broader suite of tools for source characterization of organofluorine compounds and their breakdown derivatives, with potential applications in product validation, forensics, and linking these compounds to their breakdown products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Comparison of the Forward and Reverse Photocycle Dynamics of Two Highly Similar Canonical Red/Green Cyanobacteriochromes Reveals Unexpected Differences

Cyanobacteriochromes (CBCRs) are cyanobacterial photoreceptors that exhibit photochromism between two states: a thermally stable dark-adapted state and a metastable light-adapted state with bound linear tetrapyrrole (bilin) chromophores possessing 15Z and 15E configurations, respectively. The photodynamics of canonical red/green CBCRs have been extensively studied; however, the time scales of their excited-state lifetimes and subsequent ground-state evolution rates widely differ and, at present, remain difficult to predict. Here, we compare the photodynamics of two closely related red/green CBCRs that have substantial sequence identity (~68%) and similar chromophore environments: AnPixJg2 from Anabaena sp. PCC 7120 and NpR6012g4 from Nostoc punctiforme. Using broadband transient absorption spectroscopy on the primary (125 fs to 7 ns) and secondary (7 ns to 10 ms) time scales together with global analysis modeling, our studies revealed that AnPixJg2 and NpR6012g4 have comparable quantum yields for initiating the forward ( 15Z P r → 15E P g ) and reverse ( 15E P g → 15Z P r ) reactions, which proceed through monotonic and nonmonotonic mechanisms, respectively. In addition to small discrepancies in the kinetics, the secondary reverse dynamics resolved unique features for each domain: intermediate shunts in NpR6012g4 and a Meta-Gf intermediate red-shifted from the 15Z P r photoproduct in AnPixJg2. Altogether, this study supports the conclusion that sequence similarity is a useful criterion for predicting pathways of the light-induced evolution and quantum yield of generating primary intermediate Φ p within subfamilies of CBCRs, but more studies are still needed to develop a comprehensive molecular level understanding of these processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Cofactor Complexes of DesD, a Model Enzyme in the Virulence-related NIS Synthetase Family

The understudied nonribosomal-peptide-synthetase-independent siderophore (NIS) synthetase family has been increasingly associated with virulence in bacterial species due to its key role in the synthesis of hydroxamate and carboxylate "stealth" siderophores. We have identified a model family member, DesD, from Streptomyces coelicolor , to structurally characterize using a combination of a wild-type and a Arg306Gln variant in apo , cofactor product AMP-bound, and cofactor reactant ATP-bound complexes. The kinetics in the family has been limited by solubility and reporter assays, so we have developed a label-free kinetics assay utilizing a single-injection isothermal-titration-calorimetry-based method. We report second-order rate constants that are 50 times higher than the previous estimations for DesD. Our Arg306Gln DesD variant was also tested under identical buffer and substrate conditions, and its undetectable activity was confirmed. These are the first reported structures for DesD, and they describe the critical cofactor coordination. This is also the first label-free assay to unambiguously determine the kinetics for an NIS synthetase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Lithium thiostannate spinels: air-stable cubic semiconductors.

Lithium chalcogenide materials have been studied less than other alkali metal analogs and are of interest as ion conductors and semiconductors capable of thermal neutron detection. Herein, we describe the structural, thermal, magnetic, electronic, and ionic properties of a new family of cubic lithium thiospinels Li2MSn3S8 (M = Mg, Fe, Mn, Ni, Co) and Li1.66CuSn3.33S8. All compounds crystallize in the Fd (3) over barm space group and exhibit site occupancy disorder with Sn and M on the octahedral site for M = Mg, Fe, Mn, Ni, Co. The Li1.66CuSn3.33S8 compound also exhibits occupancy disorder on the tetrahedral sites between Li and Cu, as well as on the octahedral sites between Li and Sn. We demonstrate the ability to tune the physical properties of the compounds by changing their composition. By tuning the identity of the transition metal in the structure, the optical band gaps can vary between 0.91(2) and 2.19(2) eV, and electrical resistivities between 2.8 x 10(3) Omega-cm and 2.2 x 10(7)Omega-cm can be achieved. Density functional theory calculations for Li2MgSn3S8 and Li1.66CuSn3.33S8 suggest that both materials have indirect band gaps and significantly dispersive conduction bands. A bandwidth dispersion of 0.75 and 0.70 eV along the Gamma -> M direction in the conduction band are predicted for Li2MgSn3S8 and Li1.66CuSn3.33S8, respectively, with an electron effective mass of 0.49 and 0.55 m(e) at the Gamma point. The hole effective mass in the valence band is calculated to be 1.25 me at the M point and 0.75 me at the L point for Li2MgSn3S8 and Li1.66CuSn3.33S8, respectively. The ionic/electronic conductivity of each compound was determined using AC electrochemical impedance spectroscopy.

Quintero, Michael A.↗
DOE OSTI2021

Lowering the Activation Barriers for Lithium-Ion Conductivity through Orientational Disorder in the Cyanide Argyrodite Li6PS5CN

Rapid advancements in safe and high-energy-density energy storage are predicated on identifying new solid-state ion conductors with low activation energies and high ionic conductivities for all-solid-state battery technologies. Halide argyrodites are among some of the top candidates for solid-state electrolytes, as they can achieve ionic conductivities that approach liquid electrolytes. Incorporating dynamic pseudohalide species in argyrodite solid electrolytes presents an exciting opportunity to exploit lattice dynamics as a design principle to modulate the ion conduction properties of solid-state ion conductors. In the present study, we have prepared the new argyrodite Li 6 PS 5 CN containing orientationally disordered cyanide ions. The new cyanide argyrodite Li 6 PS 5 CN exhibits an activation barrier to Li-ion transport of 471 ± 25 meV and a room-temperature ionic conductivity of 6(2) × 10 –5 S cm –1 in comparison to the activation barrier of 502 ± 16 meV and an ionic conductivity of 2.3(1) × 10 –4 S cm –1 measured for the bromide analogue Li 6 PS 5 Br. Structural studies of both compounds by high-resolution X-ray diffraction indicate that Li 6 PS 5 CN and Li 6 PS 5 Br adopt nearly identical crystal structures with similar lattice parameters, which indicates that lower activation barriers in Li 6 PS 5 CN arise due to the cyanide ion itself rather than due to changes in the geometry of conduction pathways in the local lithium environment. The orientational disorder of the quadrupolar cyanide ion in Li 6 PS 5 CN points to a complex interplay of lattice polarizability and molecular dynamics that lower the activation barrier for lithium-ion conductivity in the cyanide argyrodite.

25 ENERGY STORAGE↗
DOE OSTI2022

Delineating the Roles of Mn, Al, and Co by Comparing Three Layered Oxide Cathodes with the Same Nickel Content of 70% for Lithium-Ion Batteries

High-nickel layered oxides continue to prevail in the energy storage market as the frontmost cathode candidates for next-generation lithium-ion batteries. Demand and development of LiNi 1–x–y Mn x Co y O 2 (NMC) and LiNi 1–x–y Co x Al y O 2 (NCA) cathodes are rampantly increasing, particularly for the electric vehicle (EV) industry. However, the continued presence of cobalt in NMC and NCA cathodes raises global concerns due to geopolitical and ethical issues attributed to Co sourcing. We herein introduce a novel cobalt-free, high-nickel cathode LiNi 0.7 Mn 0.25 Al 0.05 O 2 (NMA70) and benchmark it against Co-containing LiNi 0.7 Mn 0.15 Co 0.15 O 2 (NMC70) as well as Co- and Al-free LiNi 0.7 Mn 0.3 O 2 (NM70) cathodes with equivalent 70% Ni contents that are all synthesized in-house. NMA70 displays a high initial C/10 capacity of 210 mA h g –1 , matching that of NMC70 in half cells with a cutoff voltage of 4.5 V. NMA70 also exhibits an impressive high-voltage full cell cycling performance with a cutoff voltage of 4.4 V with a nearly identical capacity retention of 83% compared to that of 82% for NMC70 after 300 cycles. Postmortem X-ray photoelectron spectroscopy (XPS), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), and electron energy loss spectroscopy (EELS) analyses indicate a thinner cathode–electrolyte interface (CEI) developed in NMA70 compared to that in NM70 and unveil a more robust solid-electrolyte interface (SEI) passivation on the graphite anode among all samples. The benefits of Al doping are additionally highlighted with enhanced high-voltage CEI and thermal stabilities in NMA70. Furthermore, this work assesses the roles of Mn, Al, and Co to demonstrate both the practicality and feasibility of synthesizing cobalt-free, high-nickel cathodes that are promising alternatives to current NMC- and NCA-based cathodes.

25 ENERGY STORAGE↗
DOE OSTI2022

Tuning Magnetic Symmetry and Properties in the Olivine Series Li 1–x Fe x Mn 1–x PO 4 through Selective Delithiation

In this work, we present the first in-depth study of the nuclear and magnetic structures of the fully lithiated LiFe x Mn 1–x PO 4 solid solutions as well as the partially delithiated Li 1– xFe x Mn 1–x PO 4 series using neutron powder diffraction. By using a weak oxidizing solution that only oxidizes Fe 2+ , we find that lithium can be removed from these olivines in a stepwise manner. Representational analysis was performed on the observed magnetic reflections and found that the lithiated solid solutions order in the magnetic space group Pnma', which is identical to triphylite (LiFePO 4 ). We report that, even when removing 20% of the lithium from the hcp lattice, the magnetic structure changes and multiple magnetic contributions are needed to fully encompass the observed magnetic order. We find that the partially delithiated x = 0.2 and 0.3 have a magnetic structure P2 1 '/n11, and when x surpasses 0.3, the magnetic structure changes to P2 1 2 1 2 1 . We give a detailed report on the effect of delithiation on magnetic order, bond distances/angles, and the super- and supersuperexchange interactions in the material. The symmetries of the magnetic order of these solid solutions are then discussed with regard to their potential as ferrotoroidic candidates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗