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At least 595 records · Page 33

Lanthanide transport in angstrom-scale MoS 2 -based two-dimensional channels

Rare earth elements (REEs), critical to modern industry, are difficult to separate and purify, given their similar physicochemical properties originating from the lanthanide contraction. Here, we systematically study the transport of lanthanide ions (Ln 3+ ) in artificially confined angstrom-scale two-dimensional channels using MoS 2 -based building blocks in an aqueous environment. The results show that the uptake and permeability of Ln 3+ assume a well-defined volcano shape peaked at Sm 3+ . This transport behavior is rooted from the tradeoff between the barrier for dehydration and the strength of interactions of lanthanide ions in the confinement channels, reminiscent of the Sabatier principle. Molecular dynamics simulations reveal that Sm 3+ , with moderate hydration free energy and intermediate affinity for channel interaction, exhibit the smallest dehydration degree, consequently resulting in the highest permeability. Our work not only highlights the distinct mass transport properties under extreme confinement but also demonstrates the potential of dialing confinement dimension and chemistry for greener REEs separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

“Did you eat a MOLEcule today?” An Interactive Demonstration of Molecular Weight with Real-Time Breath Analysis Using Mass Spectrometry for All Ages

Although mass spectrometry is a widely used analytical tool, age-appropriate, interactive outreach activities for laboratory visitors, especially children, are lacking. Furthermore, the presented interactive demonstration, “Did you eat a MOLEcule today?”, introduces all ages to molecular weight concepts and mass spectrometry in a research laboratory, while connecting the concepts to real-world applications. Through real-time breath analysis, participants explore the concepts of molecular weight, electrostatic field manipulation of charged molecules, and analyte identification by mass analysis. This module is rapid and highly adaptable for outreach activities but also includes age- or classroom-appropriate variations to decrease or increase difficulty levels. The presented interactive demonstration has repeatedly been implemented, with over 2300 participants during six annual “Take Our Daughters & Sons to Work Day” and two corporate “Family Day” outreach activities, successfully engaging, exciting, and educating both kids and parents.

36 MATERIALS SCIENCE↗

Structure and Dynamics of Aqueous Electrolytes at Quartz (001) and (101) Surfaces

Here, understanding and describing reactivity at mineral-water interfaces such as ion adsorption, the kinetics of dissolution, or surface charge development depends on our ability to improve the accuracy of electrical double layer (EDL) models. While molecular dynamics (MD) simulations are routinely used to investigate the structure and energetics of adsorbed ions comprising the EDL, less attention is paid to their self-diffusion dynamics, which can uniquely inform on coupling to interfacial reactions. Here we use MD to investigate both the organization and diffusion dynamics of water and electrolyte ions (NaCl, KCl, CaCl 2 ) at hydroxylated quartz (001) and (101) surfaces, a comparison which allowed us to assess surface structural effects of corrugation and silanol density. We found that inner- versus outer-sphere complex formation depends on cation size and charge but not necessarily hydration energies. Participation of surface silanols in the hydration spheres of Na + and K + generally indicated their preference for inner-sphere complexation, but this depends strongly on the orientation of the surface considered through its influence over the organization and dynamics of adsorbed water layers. In particular, surface orientation substantially affects the diffusive behavior of the near-surface water. Na + was found to decrease the mobility of water in the first layer, consistent with an increasing frequency of hydrolysis implied by faster quartz dissolution rates observed in experiments via the well known salt effect. Our results are also in good agreement with the observed dissolution rate of quartz vs. surface adsorption strength measure by Dove and Nix. This study sets the stage for a forthcoming paper examining how the dynamics at quartz/electrolyte interfaces are influenced by externally applied electric fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Specific Ion Effects in Lanthanide–Amphiphile Structures at the Air–Water Interface and Their Implications for Selective Separation

The use of surfactants to attract dissolved ions to water surfaces and interfaces is an essential step in both solvent-based and solvent-free separation processes. Here, we have studied the interactions of lanthanide ions in the aqueous subphase with monolayers of dihexadecyl phosphate at air–water interfaces. With heavier lanthanides (atomic number Z ≥ 65) in the subphase, the floating layer can be compressed to an area/molecule of about half the molecular cross section, indicating bilayer formation. X-ray fluorescence and reflectivity data support this conclusion. In the presence of lighter lanthanides (Z < 65), only monolayers are observed. Subphase-concentration-dependent studies using Er 3+ (heavier) and Nd 3+ (lighter) lanthanides show a stepwise progression, with ions attaching to the monolayer only when the solution concentration is >3 × 10 –7 M. Above ~10 –5 M, bilayers form but only in the presence of the heavier lanthanide. Grazing incidence X-ray diffraction shows evidence of lateral ion–ion correlations in the bilayer structure but not in monolayers. Explicit solvent all-atom molecular dynamics simulations confirm the elevated ion–ion correlation in the bilayer system. This bilayer structure isolates heavier lanthanides but not lighter lanthanides from an aqueous solution and is therefore a potential mechanism for the selective separation of heavier lanthanides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monatomic ions influence substrate permeation across bacterial microcompartment shells

Abstract Bacterial microcompartments (BMCs) are protein organelles consisting of an inner enzymatic core encased within a selectively permeable shell. BMC shells are modular, tractable architectures that can be repurposed with new interior enzymes for biomanufacturing purposes. The permeability of BMC shells is function-specific and regulated by biophysical properties of the shell subunits, especially its pores. We hypothesized that ions may interact with pore residues in a manner that influences the substrate permeation process. In vitro activity comparisons between native and broken BMCs demonstrated that increasing NaCl negatively affects permeation rates. Molecular dynamics simulations of the dominant shell protein (BMC-H) revealed that chloride ions preferentially occupy the positive pore, hindering substrate permeation, while sodium cations remain excluded. Overall, these results demonstrate that shell properties influence ion permeability and leverages the integration of experimental and computational techniques to improve our understanding of BMC shells towards their repurposing for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

Electron–Ion Covariance Reveals Geometry-Resolved Inner-Shell Spectra in CS 2 Photodissociation

The chemical shifts of inner-shell atomic orbitals are highly sensitive to chemical bonding and molecular structure. In evolving systems, however, the spectra of distinct molecular species and geometries overlap, obscuring the underlying chemical dynamics. Here we demonstrate the use of electron–ion covariance analysis to combine the structural sensitivity of Coulomb explosion imaging with inner-shell spectroscopy, yielding geometry-specific spectra of transient and product species. We apply this approach to the excited state dynamics of CS 2 probed by ionization above the S 2p edge. Electron–ion covariance with time- and momentum-selected S + and S 2+ ions isolates distinct S 2p photoelectron spectra for ground-state CS 2 , bent photoexcited CS 2 , the CS photoproduct, and bare atomic sulfur ─ species whose spectra overlap strongly in the channel-averaged measurement. Clear chemical shifts are observed in the covariance photoelectron spectrum for each of these species, all of which are consistent with high-level calculations. Here, by extracting the atomic S contribution to the photoelectron spectrum in a finely time-resolved manner we can disentangle this contribution to the overall time-resolved photoelectron spectrum as the photodissociation proceeds. These results demonstrate the promise of electron–ion covariance as a general approach to geometry-resolved inner-shell spectroscopy, opening a route to tracking structural evolution through chemical shifts in complex photoexcited molecules.

Ionization↗

Molecular Structure and Electron Affinity of Metal-Solvent Complexes: Insights from Density Functional Theory Simulations

A molecular level understanding of the structure and energetics of the monovalent and divalent metal ion complexes is of great importance for development of next-generation batteries. Here, Density Functional Theory (DFT) simulations at the ωb97xD/6-31 + G(d,p) level of theory are performed to investigate the interaction of metal ions (Li + , Na + , K + , Mg 2+ , Ca 2+ , Zn 2+ ) with 26 organic solvent molecules. The reduction energetics (electron affinity and reduction potential) and structural responses of the solvent molecules and the molecular complexes are discussed. The DFT calculations are carried out to investigate the structure, energetics and electron affinities of chelated complexes of water (H 2 O), tetrahydrofuran (THF) and di-methoxy ethane (DME) solvent molecules. Additionally, ab initio dynamic simulations (AIMD) at 298 K using atom centered density matrix propagation (ADMP) formalism are performed to understand the spontaneous structure formation upon electron attachment of the metal ion-solvent complexes. The ADMP simulations indicate the decomposition of Mg + -(DME) 3 complex via cleavage of C–O bond of one of the three DME molecules indicating irreversible decomposition of DME in the presence of the Mg + radical. We believe that the data collected as part of this investigation serves as a library of fundamental knowledge towards a deeper understanding of the electrode-electrolyte interfacial reactions.

25 ENERGY STORAGE↗

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗

Elastic Single-Ion Conducting Polymer Electrolytes: Toward a Versatile Approach for Intrinsically Stretchable Functional Polymers

Fabrication of stretchable functional polymeric materials usually relies on the physical adhesion between functional components and elastic polymers, while the interfacial resistance is a potential problem. Herein, a versatile approach on the molecular-level intrinsically stretchable polymer materials with defined functionality is reported. The single-ion conducting polymer electrolytes (SICPEs) were employed to demonstrate the proposed concept along with its potential application in stretchable batteries/electronics with improved energy efficiency and prolonged cell lifetime. The obtained membranes exhibit 88–252% elongation before breaking, and the mechanical properties are well adjustable. The galvanostatic test of the assembled cells using the obtained SICPE membrane exhibited a good cycling performance with a capacity retention of 81.5% after 100 cycles. The applicability of a proposed molecular-level design for intrinsically stretchable polymer materials is further demonstrated in other types of stretchable functional materials, including poly(vinylcarbazole)-based semiconducting polymers and poly(ethylene glycol)-based gas separation membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interactions of Oxide Surfaces with Water Revealed with Solid-State NMR Spectroscopy

Hydrous materials are ubiquitous in the natural environment and efforts have previously been made to investigate the structures and dynamics of hydrated surfaces for their key roles in various chemical and physical applications, with the help of theoretical modeling and microscopy techniques. However, an overall atomic-scale understanding of the water–solid interface, including the effect of water on surface ions, is still lacking. Herein, we employ ceria nanorods with different amounts of water as an example and demonstrate a new approach to explore the water–surface interactions by using solid-state NMR in combination with density functional theory. NMR shifts and relaxation time analysis provide detailed information on the local structure of oxygen ions and the nature of water motion on the surface: the amount of molecularly adsorbed water decreases rapidly with increasing temperature (from room temperature to 150 °C), whereas hydroxyl groups are stable up to 150 °C, and dynamic water molecules are found to instantaneously coordinate to the surface oxygen ions. Additionally, the applicability of dynamic nuclear polarization for selective detection of surface oxygen species is also compared to conventional NMR with surface selective isotopic-labeling: the optimal method depends on the feasibility of enrichment and the concentration of protons in the sample. These results provide new insight into the interfacial structure of hydrated oxide nanostructures, which is important to improve performance for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗

Electron-Transfer Activation of Thiophene

The research supported by contract FG02-90ER14146 from the U.S. Department of Energy to Thomas B. Rauchfuss is summarized. Seven research themes are described. The work on thiophenes identified pathways for desulfurization that are initiated by electron transfer or hydrolysis. Using similar half-sandwich platforms, a large family of molecular cyanometallate cages were prepared. These cages exhibit host-guest behavior, with a notable affinity for cesium ions. A series of investigations made pioneering contributions to the understanding of the catalytic properties of the hydrogenase enzymes. Work on molecular metal sulfides focused on elucidating hydrogen activation pathways, relevant to the corresponding reactions that are invoked for metal sulfide heterogeneous catalysts. The theme of proton-activated catalysis was continued with the elucidation of the effects of Bronsted acids and oxidation on inducing H2 activation by metal-amides. The proton-activation theme was shown to be a powerful vehicle for upgrading bio-derives substrates including sugars. The project concluded with emphasis on developing ligand platforms that facilitate the use of earth-abundant metals in homogeneous catalysis.

09 BIOMASS FUELS↗

Investigations of atomic and molecular processes of NBI-heated discharges in the MAST Upgrade Super-X divertor with implications for reactors

This experimental study presents an in-depth investigation of the performance of the MAST-U Super-X divertor during NBI-heated operation (up to 2.5 MW) focussing on volumetric ion sources and sinks as well as power losses during detachment. The particle balance and power loss analysis revealed the crucial role of Molecular Activated Recombination and Dissociation (MAR and MAD) ion sinks in divertor particle and power balance, which remain pronounced in the change from ohmic to higher power (NBI heated) L-mode conditions. The importance of MAR and MAD remains with double the absorbed NBI heating. MAD results in significant power dissipation (up to ${\sim} 20\%$ of $P_\textrm{SOL}$), mostly in the cold ($T_e \lt 5$ eV) detached region. Theoretical and experimental evidence is found for the potential contribution of $D^-$ to MAR and MAD, which warrants further study. These results suggest that MAR and MAD can be relevant in higher power conditions than the ohmic conditions studied previously. Post-processing reactor-scale simulations suggests that MAR and MAD can play a significant role in divertor physics and synthetic diagnostic signals of reactor-scale devices, which are currently underestimated in exhaust simulations. This raises implications for the accuracy of reactor-scale divertor simulations of particularly tightly baffled (alternative) divertor configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Femtosecond Laser Desorption Postionization MS vs ToF-SIMS Imaging for Uncovering Biomarkers Buried in Geological Samples

The study of lipid molecular fossils by traditional biomarker analysis requires bulk sample crushing, followed by solvent extraction, and then the analysis of the extract by gas chromatography-mass spectrometry (GC–MS). This traditional analysis mixes all organic compounds in the sample regardless of their origins, with a loss of information on the spatial distribution of organic molecules within the sample. These shortcomings can be overcome using the chemical mapping of intact samples. Spectroscopic techniques such as UV fluorescence or Raman spectroscopy, laser ablation inductively coupled plasma mass spectrometry, and time-of-flight secondary ion mass spectrometry (ToF-SIMS) are among those elemental and molecular mapping techniques. This study employed femtosecond (fs) laser ablation combined with single-photon ionization, a method called fs-laser desorption postionization mass spectrometry (fs-LDPI-MS). In this work, a pulsed ~75 fs, 800 nm laser was used to ablate the geological sample, which was then photoionized after a few microseconds by a pulsed 7.9 eV vacuum ultraviolet laser. An organic carbon-rich geological sample was used for this study to map hydrocarbon biomarkers in sediments that were previously studied by GC–MS. The petrography of this sample was examined by optical and fluorescence microscopy. It is demonstrated here that fs-LDPI-MS combined with petrography for multimodal imaging can expose buried compounds within the sample via in situ layer removal. When used in conjunction with traditional organic geochemical analysis, this method has the potential to determine the spatial distribution of organic biomarkers in geological material. Finally, fs-LDPI-MS imaging data are compared with ToF-SIMS imaging that is commonly used for such studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural mechanisms of TRPV6 inhibition by ruthenium red and econazole

TRPV6 is a calcium-selective ion channel implicated in epithelial Ca 2+ uptake. TRPV6 inhibitors are needed for the treatment of a broad range of diseases associated with disturbed calcium homeostasis, including cancers. Here we combine cryo-EM, calcium imaging, and mutagenesis to explore molecular bases of human TRPV6 inhibition by the antifungal drug econazole and the universal ion channel blocker ruthenium red (RR). Econazole binds to an allosteric site at the channel’s periphery, where it replaces a lipid. In contrast, RR inhibits TRPV6 by binding in the middle of the ion channel’s selectivity filter and plugging its pore like a bottle cork. Despite different binding site locations, both inhibitors induce similar conformational changes in the channel resulting in closure of the gate formed by S6 helices bundle crossing. The uncovered molecular mechanisms of TRPV6 inhibition can guide the design of a new generation of clinically useful inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

Origins of Lithium/Sodium Reverse Permeability Selectivity in 12-Crown-4-Functionalized Polymer Membranes

Direct lithium extraction via membrane separations has been fundamentally limited by lack of monovalent ion selectivity exhibited by conventional polymeric membranes, particularly between sodium and lithium ions. Recently, a 12- Crown-4-functionalized polynorbornene membrane was shown to have the largest lithium/sodium permeability selectivity observed in a fully aqueous system to date. Using atomistic molecular dynamics simulations, we reveal that this selectivity is due to strong interactions between sodium ions and 12-Crown-4 moieties, which reduce sodium ion diffusivity while leaving lithium ion mobility relatively unaffected. Furthermore, the ion diffusivities in the membrane, when scaled by their respective solution diffusivities and free ion fractions, can be collapsed to an almost universal relationship depending on solvent volume fraction.

36 MATERIALS SCIENCE↗

Hydrogen migration in inner-shell ionized halogenated cyclic hydrocarbons

Abstract We have studied the fragmentation of the brominated cyclic hydrocarbons bromocyclo-propane, bromocyclo-butane, and bromocyclo-pentane upon Br(3 d ) and C(1 s ) inner-shell ionization using coincidence ion momentum imaging. We observe a substantial yield of CH 3 + fragments, whose formation requires intramolecular hydrogen (or proton) migration, that increases with molecular size, which contrasts with prior observations of hydrogen migration in linear hydrocarbon molecules. Furthermore, by inspecting the fragment ion momentum correlations of three-body fragmentation channels, we conclude that CH x + fragments (with x = 0, …, 3) with an increasing number of hydrogens are more likely to be produced via sequential fragmentation pathways. Overall trends in the molecular-size-dependence of the experimentally observed kinetic energy releases and fragment kinetic energies are explained with the help of classical Coulomb explosion simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗