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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,045 records · Page 58
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DOE OSTI2023

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ~ 0.94–0.99) for predicting single-component adsorption capacity in metal–organic frameworks (MOFs). Here, we consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

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

Magnetic field-induced non-trivial electronic topology in Fe3− x GeTe2

The anomalous Hall, Nernst, and thermal Hall coefficients of the itinerant ferromagnet Fe3−xGeTe2 display anomalies upon cooling that are consistent with a topological transition that could induce deviations with respect to the Wiedemann–Franz (WF) law. This law has not yet been validated for the anomalous transport variables, with recent experimental studies yielding material-dependent results. Nevertheless, the anomalous Hall and thermal Hall coefficients of Fe3−xGeTe2 are found, within our experimental accuracy, to satisfy the WF law for magnetic fields μ0H applied along its c axis. Remarkably, large anomalous transport is also observed for μ0H||a axis with the field aligned along the gradient of the chemical potential generated by thermal gradients or electrical currents, a configuration that should not lead to their observation. These anomalous planar quantities are found to not scale with the component of the planar magnetization (M||), showing instead a sharp decrease beyond μ0H||= 4 T or the field required to align the magnetic moments along μ0H||. We argue that chiral spin structures associated with Bloch domain walls lead to a field-dependent spin chirality that produces a novel type of topological transport in the absence of interaction between the magnetic field and electrical or thermal currents. Locally chiral spin structures are captured by our Monte Carlo simulations incorporating small Dzyaloshinskii–Moriya and biquadratic exchange interactions. These observations reveal not only a new way to detect and expose topological excitations, but also a new configuration for heat conversion that expands the current technological horizon for thermoelectric energy applications.

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

Self-Assembly and Phase Separation for Transport: A brief argument for the continued exploration of liquid crystal flows and electrodeposition in micro-gravity

Phase separation, interfacial tension gradients, and molecular self-assembly are all phenomena frequently observed when manipulating soft condensed matter systems on Earth. Depending on the system these processes can also be quite predictable. For instance, on Earth water droplets placed on hydrophobic surfaces will have contact angles > 90° with limited spread, contrary to their wetting behavior on hydrophilic surfaces. However, in an environment that is in a constant state of free-fall, where the gravitational field is reduced by 10%, such as on the International Space Station (ISS), buoyancy and its effect on fluid convection also become negligible. Fluid flow and phase behavior become less predictable. Thus, continuing the prior example, even if water droplets still remain in contact with a surface in microgravity (µg), the interface between the air and droplets will still remain significantly curved, appearing almost as if they were placed over completely nonwetting surfaces (Fig. 1a). Moreover, the negligible opposing buoyant force would also mean that if immiscible liquid droplets of a less dense character, or air bubbles even (Fig. 1b), were to be suspended within a larger water drop, these immiscible droplets or air bubbles would not migrate toward any one direction unless either artificially propelled by an external force or internal reaction inducing flow.

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

Modifying Li + and Anion Diffusivities in Polyacetal Electrolytes: A Pulsed-Field-Gradient NMR Study of Ion Self-Diffusion

Polyacetal electrolytes have been demonstrated as promising alternatives to liquid electrolytes and poly(ethylene oxide) (PEO) for rechargeable lithium-ion batteries; however, the relationship between polymer structure and ion motion is difficult to characterize. Here, we study structure-property trends in ion diffusion with respect to polymer composition for a systematic series of five polyacetals with varying ratios of ethylene oxide (EO) to methylene oxide (MO) units, denoted as P(xEO-yMO), and PEO. We first use 7 Li and 19 F pulsed-field-gradient NMR spectroscopy to measure cation and anion self-diffusion, respectively, in polymer/lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt mixtures. At 90 °C, we observe modest changes in Li + diffusivity across all polymer compositions, while anion (TFSI - ) self-diffusion coefficients decrease significantly with increasing MO content. At a given reduced temperature (T - T g ), all polyacetal electrolytes exhibit faster Li + self-diffusion than PEO. Intriguingly, P(EO-MO) and P(EO-2MO) also show slower TFSI - anion self-diffusion than PEO at a given reduced temperature. Molecular dynamics simulations reveal that shorter distances between acetal oxygen atoms (O-CH 2 -O) compared to ether oxygens (O-CH 2 -CH 2 -O) promote more diverse, often asymmetric, Li + coordination environments. Finally, Raman spectra reveal that anion-rich ion clusters in P(EO-MO) and P(EO-2MO) lead to decreased anion diffusivity, which along with increased cation diffusivity, support the viability of polyacetals as high-performance polymer electrolytes.

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

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Origin of layered perovskite device efficiencies revealed by multidimensional time-of-flight spectroscopy

Mixtures of layered perovskite quantum wells with different sizes form prototypical light-harvesting antenna structures in solution-processed films. Gradients in the bandgaps and energy levels are established by concentrating the smallest and largest quantum wells near opposing electrodes in photovoltaic devices. Whereas short-range energy and charge carrier funneling behaviors have been observed in layered perovskites, our recent work suggests that such light-harvesting processes do not assist long-range charge transport due to carrier trapping at interfaces between quantum wells and interstitial organic spacer molecules. Here, we apply a two-pulse time-of-flight technique to a family of layered perovskite systems to explore the effects that interstitial organic molecules have on charge carrier dynamics. In these experiments, the first laser pulse initiates carrier drift within the active layer of a photovoltaic device, whereas the second pulse probes the transient concentrations of photoexcited carriers as they approach the electrodes. The instantaneous drift velocities determined with this method suggest that the rates of trap-induced carrier deceleration increase with the concentrations of organic spacer cations. Overall, our experimental results and model calculations suggest that the layered perovskite device efficiencies primarily reflect the dynamics of carrier trapping at interfaces between quantum wells and interstitial organic phases.

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

Dynamics of Glyceline and Interactions of Constituents: A Multitechnique NMR Study

In this work, the dynamics of the organic components of the deep eutectic solvent (DES) glyceline are analyzed using an array of complementary nuclear magnetic resonance (NMR) methods. Fast-Field Cycling 1 H relaxometry, Pulsed Field Gradient diffusion, Nuclear Overhauser Effect Spectroscopy (NOESY), 13 C NMR relaxation and pressure dependent NMR experiments are deployed to sample a range of frequencies and modes of motion of the glycerol and choline components of the DES. Generally, translational and rotational diffusion of glycerol are more rapid than those of choline while short range rotational motions observed from 13 C relaxation indicate slow local motion of glycerol at low choline chloride (ChCl) content. The rates of glycerol and choline local motions become more similar at higher ChCl. This result taken together with pressure dependent NMR studies show that the addition of ChCl makes it easier to disrupt glycerol packing. Finally, a relatively slow hydroxyl H-exchange process between glycerol and choline protons is deduced from the data. Consistent with this, NOESY results indicate relatively little direct H-bonding between glycerol and choline. These results suggest that the glycerol H-bonding network is disrupted as choline is added, but primarily in regions where there is intimate mixing of the two components. Thus, the local dynamics of most of the glycerol, resembles that of pure glycerol until substantial choline chloride is present.

13C NMR relaxation↗
DOE OSTI2021

Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials

Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects-their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches. Here, we present a reinforcement learning (RL) [Monte Carlo Tree Search (MCTS)] based on delayed rewards that allow for efficient search of the defect configurational space and allows us to identify optimal defect arrangements in low-dimensional materials. Using a representative case of two-dimensional MoS 2 , we demonstrate that the use of delayed rewards allows us to efficiently sample the defect configurational space and overcome the energy barrier for a wide range of defect concentrations (from 1.5 to 8% S vacancies)-the system evolves from an initial randomly distributed S vacancies to one with extended S line defects consistent with previous experimental studies. Detailed analysis in the feature space allows us to identify the optimal pathways for this defect transformation and arrangement. Comparison with other global optimization schemes like genetic algorithms suggests that the MCTS with delayed rewards takes fewer evaluations and arrives at a better quality of the solution. The implications of the various sampled defect configurations on the 2H to 1T phase transitions in MoS 2 are discussed. In this study, we introduce a RL strategy employing delayed rewards that can accelerate the inverse design of defects in materials for achieving targeted functionality.

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

Structural and Dynamic Heterogeneity of Deep Eutectic Solvents Composed of Choline Chloride and Ortho-Phenol Derivatives

Structural, thermal, and dynamic properties of four deep eutectic solvents comprising choline chloride paired with ortho-phenolic derivative hydrogen-bond donors were probed using experiments and molecular simulations. The hydrogen-bond donors include phenol, catechol, o-chlorophenol, and o-cresol, in a 3:1 mixture with the hydrogen-bond acceptor choline chloride. Density, viscosity, and pulsed-field gradient NMR diffusivity measurements were conducted over a range of temperatures. Classical and ab initio molecular dynamics simulation results match experimental data reasonably well. Furthermore, the simulation results were then used to perform a more detailed analysis of the local structure and dynamics of these systems.

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

Lattice Structure and Dynamics of Sparse Molecular Crystals: OsO 4 and RuO 4

OsO 4 and RuO 4 are molecular oxides with unique tetrameric structures and rare +8 oxidation states. Accurately modeling their properties remains challenging for density functional theory (DFT) due to weak intertetramer interactions, which standard functionals fail to capture. Here, in this work, we show that the van der Waals (vdW)-corrected density functional (vdW-DF-optB86b) provides structural parameters that are much closer to experimental values than the standard generalized gradient approximation, with volume predictions that fall within the experimentally observed range. Phonon band structure analysis shows that the inclusion of vdW interactions stabilizes soft phonon modes, highlighting the importance of dispersion corrections for accurate predictions of lattice dynamics. Experimental measurements of the phonon density of states for OsO 4 , obtained via inelastic neutron scattering, demonstrate good agreement with our vdW-DF-optB86b calculations. These results validate OsO 4 and RuO 4 as valuable benchmarks for structural and vibrational calculations via vdW-corrected DFT methods and offer insights for studying the broader class of sparse molecular materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Accurate prediction of core-level spectra of radicals at density functional theory cost via square gradient minimization and recoupling of mixed configurations

State-specific orbital optimized approaches are more accurate at predicting core-level spectra than traditional linear-response protocols, but their utility had been restricted due to the risk of "variational collapse" down to the ground state. We employ the recently developed square gradient minimization algorithm to reliably avoid variational collapse and study the effectiveness of orbital optimized density functional theory (DFT) at predicting second period element 1s core-level spectra of open-shell systems. Several density functionals (including SCAN, B3LYP, and ωB97X-D3) are found to predict excitation energies from the core to singly occupied levels with high accuracy (≤0.3 eV RMS error) against available experimental data. Higher excited states are, however, more challenging by virtue of being intrinsically multiconfigurational. We thus present a configuration interaction inspired route to self-consistently recouple single determinant mixed configurations obtained from DFT, in order to obtain approximate doublet states. This recoupling scheme is used to predict the C K-edge spectra of the allyl radical, the O K-edge spectra of CO + , and the N K-edge of NO 2 with high accuracy relative to experiment, indicating substantial promise in using this approach for the computation of core-level spectra for doublet species [vs more traditional time dependent DFT, equation of motion coupled cluster singles and doubles (EOM-CCSD), or using unrecoupled mixed configurations]. Finally, we also present general guidelines for computing core-excited states from orbital optimized DFT.

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

Study of Self-Interaction Errors in Density Functional Calculations of Magnetic Exchange Coupling Constants Using Three Self-Interaction Correction Methods

We examine the role of self-interaction errors (SIE) removal on the evaluation of magnetic exchange coupling constants. In particular we analyze the effect of scaling down the self-interaction-correction (SIC) for three non-empirical density functional approximations (DFAs) namely, the local spin density approximation, the Perdew-Burke-Ernzerhof generalized gradient approximation, and recent SCAN family of meta-GGA functionals. To this end, we employ three one-electron SIC methods: Perdew-Zunger [Perdew, J. P.; Zunger, A. Phys. Rev. B, 1981, 23, 5048] SIC, the orbitalwise scaled SIC method [Vydrov, O. A. et al., J. Chem. Phys. 2006, 124, 094108], and the recent local scaling method [Zope, R. R. et al., J. Chem. Phys. 2019, 151, 214108]. We compute the magnetic exchange coupling constants using the spin projection and non projection approaches for sets of molecules composed of dinuclear and polynuclear H-He models, organic radical molecules, and chlorocuprate, and compare these results against accurate theories and experiment. Our results show that for the systems that mainly consist of single electron regions, PZSIC performs well but for more complex organic systems and the chlorcuprates, an overcorrecting tendency of PZSIC combined with the DFAs utilized in this work is more pronounced, and in such cases LSIC with kinetic energy density ratio performs better than PZSIC. Furthermore, analysis of the results in terms of SIC corrections to the density and to the total energy shows that both density and energy correction are required to obtain an improved prediction of magnetic exchange couplings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Halide Substitution Effects on Lithium-Ion Diffusion in Protonated Antiperovskites

Solid-state electrolytes (SSEs) for all-solid-state lithium-ion batteries are generating intense interest because these batteries can improve the safety and performance compared with devices fabricated with conventional, flammable liquid electrolytes. In these SSEs, it has been suggested that Li + ion diffusion in the grain boundaries is hindered and is a critical determinant of the overall ionic conductivity (σ). However, Li + ion diffusivities in the grain (D G ) and the grain boundary (D GB ) are difficult to determine experimentally, with few techniques capable of distinguishing the individual contributions. Here, we distinguished the D G and D GB for the protonated lithium antiperovskites (pLiAPs) SSEs: Li 2 OHCl, Li 2 OHBr, Li 2 OHF 0.1 Cl 0.9 , Li 2 OHF 0.1 Br 0.9 , and Li 2 OHCl 0.3 7Br 0.63 . The measurements were obtained directly from 7 Li pulsed-field gradient nuclear magnetic resonance (PFG-NMR) at 353 K. The 7 Li PFG-NMR echo profiles were composed of two primary components with additional secondary oscillatory components – the so-called NMR diffraction phenomenon. The length scale separating the two main components corresponds to a diffusion length of ~1.7 µm, which is thought to be the average grain size (by diameter). The short-range (≤ 1.7 µm) diffusion component associated with D G (≈10 -11 m 2 /s) varied minimally with halide substitution, while the long-range (≥ 1.7 µm) component D GB (≈10 -12 to 10 -15 m 2 /s) was highly sensitive to the substitution of halides and closely correlated with s. In addition, from the comparison of the ratio D GB /D G to D t (the Li + ion diffusion coefficient estimated from the rotational correlation time, t c ), it was determined that the contribution of D G to σ is negligible; 0.01 ~ 0.04 in the pLiAPs studied here. Finally, these insights provide fundamental understanding of the halide substitution effects on Li + ion grain versus grain boundary diffusion, and suggest that careful engineering of the grain boundaries at the microscopic level is necessary to achieve high-performance pLiAP SSEs.

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

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Selective permeation up a chemical potential gradient to enable an unusual solvent purification modality

The need for energy-efficient recovery of organic solutes from aqueous streams is becoming more urgent as chemical manufacturing transitions toward nonconventional and bio-based feedstocks and processes. In addition to this, many aqueous waste streams contain recalcitrant organic contaminants, such as pharmaceuticals, industrial solvents, and personal care products, that must be removed prior to reuse. We observe that rigid carbon membrane materials can remove and concentrate organic contaminants via an unusual liquid-phase membrane permeation modality. Surprisingly, detailed thermodynamic calculations on the chemical potential of the organic contaminant reveal that the organic species has a higher chemical potential on the permeate side of the membrane than on the feed side of the membrane. This unusual observation challenges conventional membrane transport theory that posits that all permeating species move from high chemical potential states to lower chemical potential states. Based on experimental measurements, we hypothesize that the organic is concentrated in the membrane relative to water via favorable binding interactions between the organic and the carbon membrane. The concentrated organic is then swept through the membrane via the bulk flow of water in a modality known as “sorp-vection.” We highlight via simplified nonequilibrium thermodynamic models that this “uphill” chemical potential permeation of the organic does not result in second-law violations and can be deduced via measurements of the organic and water sorption and diffusion rates into the carbon membrane. Moreover, this work identifies the need to consider such nonidealities when incorporating unique, rigid materials for the separations of aqueous waste streams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Chemical and Electronic Properties of Stability-Enhanced, Mixed Ir-TiO x Oxygen Evolution Reaction Catalysts

Iridium has emerged as the leading catalyst material for the anodic oxygen evolution reaction (OER) in acidic media. Often, iridium is mixed with more stable materials such as titanium. For these materials, the electronic structure of titanium plays a crucial role since with varying degrees of oxidation titanium transforms to semiconducting or even insulating phases. Yet, the electronic properties of mixed Ir-TiO x catalysts have never been systematically studied. In this study, we correlate the catalytic performance of mixed Ir-TiO x -based OER catalysts with the electronic structure of the surface layers. For this, a thin film material library with a 20-70 at. % Ir (Ir/[Ir + Ti]) compositional gradient was prepared. We used inductively coupled plasma mass spectrometry to test the OER activity and stability of the set of mixed Ir-TiO x catalyst candidate materials. Complementary, Ti L 2,3 - and O K-edge X-ray absorption spectroscopy and depth-dependent X-ray photoelectron spectroscopy measurements were performed to correlate the catalytic performance with the composition and electronic property profiles of these mixed Ir-TiO x OER anode catalysts. The spectroscopic analysis reveals that titanium is present as an intermixed matrix of semiconductive but stable TiO 2 , conductive but less stable titanium-suboxides (TiO x ), and highly conductive but highly unstable metallic Ti(0). The extent of the titanium oxidation strongly depends on the titanium content, with a lower degree of oxidation observed for lower titanium (and thus higher iridium) contents. For an iridium loading of 70 at. %, the respective mixed Ir-TiO x catalyst showed a similar OER activity to that of the pure metallic iridium (1.74 vs 1.59 VRHE, respectively) but with a 71% lower iridium dissolution rate relative to the pure metallic iridium. This demonstrates the stabilization effect of titanium addition while maintaining high OER activity.

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

Higher Ion Selectivity with Lower Energy Usage Promoted by Electro-osmotic Flow in the Transport through Conical Nanopores

The tradeoff between selectivity and throughput presents fundamental challenges to improve desalination and charge storage, salinity gradient-based energy harvesting, memory device/circuit development, and so forth. The well-known ion-current rectification and the recently resolved time-dependent transport hysteresis in conical nanopores or asymmetric nanointerfaces offer new opportunities for the selective transport of matter. This report shows that electro-osmotic flow (EOF) is an overlooked factor that increases ion selectivity while maintaining enhanced transport throughput in rectified nanoscale electrokinetic transport. The increased selectivity originates primarily from the suppression of anion flux by the fluid flow in the opposite direction under the applied electrical field. By solving the Poisson and Nernst–Planck (PNP) equations without and with coupled Navier–Stokes (PNP–NS) equations, the EOF effects on cation and anion transport are unequivocally revealed in asymmetric nanopipettes. The flux of cations and anions as well as the transference number and flow velocity are elucidated using the models and boundary conditions validated by previous experiments. A dimensionless parameter, radius over the Debye length, reveals optimal ion selectivity and energy cost at intermediate ion concentrations and nanopore sizes, up to hundreds of millimolars and tens of nanometers under time-dependent potential stimulus. Furthermore, the fundamental insights into EOF at nanointerfaces suggest new routes/strategies for better separation, analysis, and energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Investigating trends in actinide covalency and magnetism with 35/37 Cl SSNMR spectroscopy and first-principles calculations

Solid-state NMR (SSNMR) spectroscopy is a powerful technique for studying actinide chemistry but has been significantly limited due to the complex paramagnetism, and radiological hazards presented by these materials. Lanthanide and actinide salts often feature magnetic ordering and can be paramagnetic, ferromagnetic, or antiferromagnetic depending on temperature and electronic structure. Paramagnetic interactions can manifest in SSNMR both as secular spectral shifts and/or couplings as well as contributions from non-secular relaxation. Both effects can be directly measured with NMR and used to extrapolate rich chemical information such as coordination environments, bonding characteristics, local molecular dynamics, and correlation times. Typically, these studies are carried out on high-γ and highly abundant NMR-active isotopes (e.g., 1 H, 6/7 Li, 19 F, 23 Na, etc.) or on enriched rare isotopes (e.g., 2 H and 17 O), which can be expensive. Herein, we present a facile methodology to measure the 35/37 Cl electric-field gradient (EFG) and paramagnetic shift anisotropy (SA) tensor components using static wideline SSNMR measurements of LaCl 3 , NdCl 3 , UCl 3 , and UCl 4 . The static powder spectra were measured with both 35 Cl and 37 Cl SSNMR to increase the fidelity of the extracted tensor parameters. Variable temperature NMR of a select case confirms the Curie–Weiss paramagnetism. Relaxation measurements of both nuclei further corroborate observations owing to the paramagnetic relaxation enhancement and reveal simultaneous quadrupolar relaxation mechanisms. Density functional theory (DFT) calculations using Hubbard U corrections to the uranium valence orbitals show excellent agreement with experimental EFG tensor parameters and help describe the bonding characteristics in these lanthanide and actinide systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗