SEARCH · Engineering Papers

Results for “Ionic computing”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Cosolvent-tuned interactions in ionic liquids: A vibrational and quantum-chemical study of ethylene glycol ratio effects

Ionic liquids (ILs) are attractive media for CO 2 capture but remain limited by viscosity and cost. Blending ILs with ethylene glycol (EG) is a practical route to mitigate these constraints, yet the molecular origins of cosolvent effects and their dependence on composition are not well resolved. We combine Fourier-transform infrared (FT-IR) spectroscopy with quantum-chemical (DFT) analysis to elucidate how the IL:EG molar ratio modulates intermolecular interactions and electronic structure. Computed vibrational frequencies enable mode assignment and deconvolution of overlapping bands, revealing systematic, ratio-dependent shifts and broadenings in (i) EG O–H stretching, (ii) cation and EG C–H stretchings (imidazolium C2–H, C4–H, C5–H, methyl and ethyl groups, -CH2 of EG), (iii) anion signature modes (e.g., CN motifs), and (iv) EG C–O and C–C stretchings, consistent with the redistribution of hydrogen-bonding networks. Molecular electrostatic potential (MESP) maps quantify attenuation of extreme potential regions with increasing EG, indicating progressive screening of cation–anion electrostatic interactions. Quantum Theory of Atoms in Molecules (QTAIM) identifies emergent bond critical points between EG and the IL ions, while Reduced Density Gradient–Noncovalent Interaction (RDG–NCI) analysis differentiates strong directional hydrogen bonds from dispersive contacts across compositions. Together, these results show that EG fraction controls a switch from predominantly ion–ion to mixed ion–EG coordination, altering local polarity and polarizability that underlie the observed FT-IR trends. The framework provides composition–structure–spectrum relationships that can guide rational selection of IL:EG ratios to balance favorable molecular interactions with practical performance targets in scalable CO 2 capture systems.

DAC↗

DOE OSTI2025

Ligand-Functionalized Polymer Membranes for Selective Ion Separations

Selective ion separations are central to technologies spanning water purification, resource recovery, and clean energy. Conventional polymer membranes, which rely on steric hindrance or Donnan exclusion, struggle to discriminate between chemically similar ions in high-ionic-strength environments. Ligand-functionalized membranes offer a transformative strategy by embedding molecular recognition directly into polymer matrices, enabling selective complexation and transport. Here, this Viewpoint highlights the structure–function relationships underlying ligand-mediated ion separation, emphasizing the interplay of dehydration penalties, ligand coordination, and nanoscale confinement. We discuss design principles, denticity, donor identity, rigidity, and spatial organization, alongside the permeability–selectivity trade-off, multicomponent effects, and stability challenges. Finally, we outline emerging strategies, from bioinspired ligands to computationally guided design, that chart a path toward next-generation membranes for precise and energy-efficient ion separations.

ions↗

DOE OSTI2025

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Accurate Electron-Phonon Interactions from Advanced Density Functional Theory

Electron-phonon coupling (EPC) is key to understanding charge transport, band renormalization, and superconductivity in energy materials, including correlated transition-metal oxides, ferroelectric perovskites, optoelectronic semiconductors, and phonon-mediated superconductors. Although first-principles density functional theory (DFT)-based EPC calculations are used widely, their predictive power is limited by the accuracy, transferability, and efficiency of the underlying exchange-correlation functionals. These limitations become exacerbated in complex 𝑑- and 𝑓-electron materials, where beyond-DFT approaches and additional corrections, such as the Hubbard 𝑈, are commonly invoked. Here, using the examples of Co⁢O and Ni⁢O, we show how the 𝑟 2 SCAN density functional correctly captures strong EPC effects in transition-metal oxides without requiring the introduction of Hubbard 𝑈 parameters. We also find that 𝑟 2 SCAN successfully describes the subtle interplay between ionic and covalent bonding, and strong EPC effects in the low-temperature rhombohedral phase of the prototypical ferroelectric Ba⁢Ti⁢O 3 , without requiring Hubbard 𝑈 and intersite 𝑉 corrections. We further demonstrate the ability of 𝑟 2 SCAN to accurately model the EPC of the main-group semiconductor Ga⁢As and the phonon-mediated superconducting properties of Mg⁢B 2 , with reliable electronic bands and phonons. Our study establishes 𝑟 2 SCAN-based EPC as a transferable, parameter-free, and computationally efficient framework for predictive material-specific modeling of EPC in energy materials, and opens a practical route toward high-throughput screening of superconductors, thermoelectrics, optoelectronic semiconductors, and oxide electrodes and catalysts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Anion Photoelectron Spectroscopy and Ab Initio Studies of the UF – Anion

A synergistic anion photoelectron spectroscopic and ab initio computational study of photodetachment of UF – is reported. The measurement determined a vertical detachment energy of 0.63(03) eV, which is consistent with a spinor-based relativistic coupled-cluster CCSD(T) value of 0.61 eV. The complex spectral features due to excited electronic states and vibrational progressions of UF are analyzed and assigned with the help of spin–orbit-coupled multireference perturbation theory and spinor-based relativistic coupled-cluster calculations. UF and UF – are confirmed to be dominated by ionic bonding. Furthermore, the usefulness of the spinor CCSD(T) approach is demonstrated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Using data-science approaches to unravel insights for enhanced transport of lithium ions in single-ion conducting polymer electrolyte

Solid polymer electrolytes have yet to achieve the an ionic conductivity > 1 mS/cm at room temperature for realistic applications. This target implies the need to reduce the effective energy barriers of ion transport in polymer electrolytes to around 20 kJ/mol. In this work, we combine information extracted from existing experimental results with theoretical calculations to provide insights into ion transport in single-ion conductors (SICs) with a focus on lithium ion SICs. Through the analysis of temperature-dependent ionic conductivity data obtained from the literature, we evaluate different methods of extracting energy barriers for lithium transport. The traditional Arrhenius fit to the temperature-dependent ionic conductivity data indicates that the Meyer-Neldel rule holds for SICs. However, the values of the fitting parameters remain unphysical. Our modified approach based on recent work (Macromolecules, 56, 15, 6051(2023)), which incorporates a fixed pre-exponential factor, reveals that the energy barriers exhibit temperature dependence over a wide range of temperatures. Using this approach, we identify a series of anions leading to the energy barriers less than 30 kJ/mol, which include trifluoromethane sulfonimide (TFSI), fluoromethane sulfonimide (FSI), and boron-based organic anions. In our efforts to design the next generation of anions, which can exhibit the energy barriers less than 20 kJ/mol, we focused on boron-containing SICs, and performed density functional theory (DFT) based calculations to connect the chemical structures via the binding energy of cation (lithium)-anion pairs with the experimentally derived effective energy barriers for ion transport. Not only have we identified a correlation between the binding energy and the energy barriers, but we also propose a strategy to design new boron-based anions by using the correlation. This combined approach involving experiments and theoretical calculations is capable of facilitating the identification of promising new anions, which can exhibit ionic conductivity $> 1$ mS/cm near room temperature, thereby expediting the development of novel superionic single-ion conducting polymer electrolytes. The published datasets include all the temperature-dependent ionic conductivity collected from the literature with literature DOIs, DFT calculated binding energies, and python scripts to analyze data, construct statistical models, and generate plots.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Photoresponsive Rotaxanes Switch Lipid Bilayer Neuromorphic Behavior with Light

A rotaxane consisting of a macrocycle ring with two azobenzene units mechanically interlocked onto a bolaamphiphilic axle was incorporated into droplet interface bilayers (DIBs). The azobenzene groups on the ring underwent quasi-reversible, photoisomerization-induced cycling between 1-E and 1-Z configurations when irradiated with 370 and 467 nm light, respectively, enabling programmable access to different history-dependent electrical behaviors from the same membrane. In the 1-E configuration, bilayers exhibited type-IIactive memristance that coincided with increasingly elevated ionic conduction, associated with progressively enhanced bilayer permeability during voltage cycling. In the 1-Z configuration, bilayers displayed type-I, passive memcapacitive behavior, reflecting tighter lipid packing and reduced ionic permeability. Photoswitching also yielded a nonvolatile, photoresponsive memcapacitor that could be modulated repetitively with negligible loss, likely via reversible changes in membrane thickness. Concurrent ohmic leakage currents across the membrane were less than 0.3%. These results agree with previous studies with increasing membrane permeability using photoswitchable rotaxanes and provide new insights into the coupling between volatile and nonvolatile memcapacitance during photoisomerization. More broadly, they demonstrate a new strategy for the manipulation of neuromorphic behaviors in soft materials using light, with implications for brain-inspired computation and sensing.

droplet interface bilayers↗

DOE OSTI2025

Understanding and design of interstitial oxygen conductors

Highly efficient oxygen-active materials that react with, absorb, and transport oxygen is essential for fuel cells, electrolyzers and related applications. While vacancy-mediated oxygen-ion conductors have long been the focus of research, they are limited by high migration barriers at intermediate temperatures (400–600 °C), which hinder their practical applications. In contrast, interstitial oxygen conductors exhibit significantly lower migration barriers enabling higher ionic conductivity at lower temperatures. This review systematically examines both well-established and recently identified families of interstitial oxygen-ion conductors, focusing on how their unique structural motifs such as corner-sharing polyhedral frameworks, isolated polyhedral, and cage-like architectures, facilitate low migration barriers through interstitial and/or interstitialcy diffusion mechanisms. A central discussion of this review focuses on the evolution of design strategies, from targeted donor doping, element screening, to physical-intuition descriptor material screening and machine learning approach, which leverage computational tools to explore vast chemical spaces in search for new interstitial conductors. The success of these strategies demonstrates that a significant, largely unexplored space remains for discovering high-performing interstitial oxygen conductors. Crucial features enabling high-performance interstitial oxygen diffusion include the availability of electrons for oxygen reduction and sufficient structural flexibility with accessible volume for interstitial accommodation and migration. This review concludes with a forward-looking perspective, proposing a knowledge-driven methodology that integrates current understanding with data-centric approaches to identify promising interstitial oxygen conductors outside traditional search paradigms. These approaches are expected to significantly accelerate the development of high-performance interstitial oxygen conductors for a variety of oxygen-active applications, ultimately paving the way for more efficient and sustainable energy technologies.

Interstitial oxygen conductors↗

DOE OSTI2024

Effects of Nonequilibrium Atomic Structure on Ionic Diffusivity in LLZO: A Classical and Machine Learning Molecular Dynamics Study

To improve the performance of electrochemical devices, it is essential to understand the effects of nonequilibrium motifs in solids, such as grain boundaries, amorphous phases, and highly strained regions, on atomic-scale transport and stability. Molecular dynamics simulations are used to explore the combined effect of far-from-equilibrium atomic structures and the choice of interatomic potential on ionic diffusivity predictions for Li 7 La 3 Zr 2 O 12 (LLZO), a promising solid electrolyte for all-solid-state batteries. Amorphization and high strain are considered using both classical Buckingham interatomic potentials and machine learning force fields. Here we find that both crystalline expansion and amorphization tend to slow diffusion, although the different physical encodings in the two potentials impact the properties in different ways. We trace these variations to a combination of structural and transport factors, the contributions of which are deconvoluted computationally. Graph-based analysis reveals that the variations for amorphous LLZO arise from the connectivity of diffusion pathways within the predicted structures, which generally correlates with diffusivity and is notably higher for structures generated by the machine learning force fields. Our study provides additional insight into the relationship between atomic structure and diffusivity in LLZO, while also highlighting the need for care in choosing and validating potentials to simulate far from equilibrium structures.

25 ENERGY STORAGE↗

DOE OSTI2024

Electrochemical grand potential-based phase-field simulation of electric field-assisted sintering

Here, an electrochemical grand potential functional was proposed to describe the sintering of an ionic ceramic green body. The resultant phase-field description enables simulation of the consolidation of an arbitrary number of granular particles and their interactions with the surrounding void phase. The model includes the effects of charged vacancies and the associated interactions between internal and applied electric fields. Defect segregation to grain boundaries is also accounted for, as well as enhanced interfacial defect mobilities. The model was parameterized for Y 2 O 3 . Simulations of two-particle systems showed that the applied electric field had an increasingly important impact on neck growth as particle size increased. A sudden rapid increase in temperature occurred for larger field strengths, which has been reported to be correlated to the onset of a flash event in flash sintering. Simulations of many particles showed that internal heat generation by Joule heating was localized at particle–particle contacts (grain boundaries), even though their conductivities were lower than nearby internal particle-void interfaces. A percolative path for ionic charge across the green body and the ceramic sintered solid was thus defined, accelerating the Joule heating process as the porosity of the green body is removed.

36 MATERIALS SCIENCE↗

NASA NTRS1975

Calculated diffusion coefficients and the growth rate of olivine in a basalt magma

Concentration gradients in glass adjacent to skeletal olivines in a basalt have been examined by electron probe. The glass is depleted in Mg, Fe, and Cr and enriched in Si, Al, Na, and Ca relative to that far from olivine. Ionic diffusion coefficients for the glass compositions are calculated from temperature, ionic radius and melt viscosity, using the Stokes-Einstein relation. At 1170 C, the diffusion coefficient of Mg(2+) ions in the basalt is 4.5 billionths sq cm per sec. Comparison with measured diffusion coefficients in a mugearite suggests this value may be 16 times too small. The concentration gradient data and the diffusion coefficients are used to calculate instantaneous olivine growth rates. Growth necessarily preceded emplacement such that the composition of the crystals plus the enclosing glass need not be that of a melt. The computed olivine growth rates are compatible with the rate of crystallization deduced for the Skaegaard intrusion.

Donaldson, C. H.↗

DOE OSTI2024

Cascade CO 2 Insertion in Carbanion Ionic Liquids Driven by Structure Rearrangement

The CO 2 chemisorption in state-of-the-art sorbents based on oxide/hydroxide/amine moieties is driven by strong chemical bonding formation in the carbonate/bicarbonate/carbamate products, which in turn leads to high energy input in sorbent regeneration. In addition, the CO 2 uptake capacity was limited by the active sites’ utilization efficiency, with each active site incorporating one CO 2 molecule or less. In this work, a new concept and generation of sorbent was developed to achieve cascade insertion of multiple CO 2 molecules by leveraging structure rearrangement as the driving force, leading to in situ generation of extra CO 2 -binding sites and significantly reduced energy input for CO 2 release. The designed ionic liquids (ILs) containing carbanions with conjugated and asymmetric structure, deprotonated (methylsulfonyl)acetonitrile ([MSA]) anion, allowed the cascade insertion of two CO 2 molecules via consecutive C–C and O–C bond formations. The proton transfer and structure rearrangement of the carboxylic acid intermediates played critical roles in stabilizing the first integrated CO 2 and generating extra electron-rich oxygen sites for the insertion of the second CO 2 . The structure variation and reaction pathway were confirmed by operando spectroscopy, magnetic resonance spectroscopy (NMR), mass spectroscopy, and computational chemistry. The energy input in sorbent regeneration could be further reduced by harnessing the phase-changing behavior of the carbanion salts in ether solutions upon reacting with CO 2 , avoiding the energy consumption in heating the solvent. In conclusion, the fundamental insights obtained herein provide a promising approach to greatly improve the CO 2 sorption performance via sophisticated molecular-scale structural engineering of the sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1981

Transport, charge exchange and loss of energetic heavy ions in the earth's radiation belts - Applicability and limitations of theory

Computer simulations of processes which control the relative abundances of ions in the trapping regions of geospace are compared with observations from discriminating ion detectors. Energy losses due to Coulomb collisions between ions and exospheric neutrals are considered, along with charge exchange losses and internal charge exchanges. The time evolution of energetic ion fluxes of equatorially mirroring ions under radial diffusion is modelled to include geomagnetic and geoelectric fluctutations. Limits to the validity of diffusion transport theory are discussed, and the simulation is noted to contain provisions for six ionic charge states and the source effect on the radiation belt oxygen ion distributions. Comparisons are made with ion flux data gathered on Explorer 45 and ISEE-1 spacecraft and results indicate that internal charge exchanges cause the radiation belt ion charge state to be independent of source charge rate characteristics, and relative charge state distribution is independent of the radially diffusive transport rate below the charge state redistribution zone.

Spjeldvik, W. N.↗

DOE OSTI2025

Constructing Water‐Stable Porous Organic Salts via Suppressed Proton Integration Using Fluorinated Tetrazole Tectons

Porous organic salts (POSs) are an emerging class of materials with ordered ionic architectures, offering excellent proton transfer and water uptake properties. However, conventional POS synthesis via strong acid–base neutralization (e.g., ─SO₃H and ─NH₂) leads to extensive hydrogen bonding with water, compromising stability in aqueous and water-lean environments. Here, we address this challenge by designing POSs with hydrophobic porous channels and minimal hydrogen bonding formation. Our key innovation is the use of fluorinated tetrazole as a weak acid tecton and a tetra-substituted imidazole precursor devoid of active protons as the base. Single-crystal analysis and computational modeling reveal that the structural integrity of the synthesized POSs arises primarily from cation–anion interactions, with water confined as clusters in the pores, independent of hydrogen bonding with the scaffold. Robustness of the POS structure under aqueous and water-lean conditions is confirmed by X-ray and neutron scattering, as well as computational modeling, confirming preserved packing and crystal structures. The stability of POS is further demonstrated in aqueous iodine capture, with imidazolium cations and C–F functionalizations serving as strong adsorption sites. As a result, the approach developed herein further pushes the boundary of POS materials to withstand both aqueous and water-lean conditions.

Fluorinated tecton↗

NASA NTRS2017

Small Ion Channel Linking Molecular Simulations and Electrophysiology

Ion channels are pore-forming protein assemblies that mediate the transport of small ions across cell membranes. Otherwise, membrane bilayers would be almost impermeable to ions incapable to traverse the low dielectric constant, hydrophobic membrane core. Ion channels are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses, cardiac functions, muscle contraction and apoptosis. On the other extreme of biological complexity, viral ion channels (viroporins) influence many stages of the virus infection cycle either through regulating virus replication, such as entry, assembly and release or modulating the electrochemical balance in the subcellular compartments of host cells. Ion channels were crucial components of protocells. Their emergence facilitated adaptation of nascent life to different environmental conditions. The earliest ion channels must have been much simpler than most of their modern ancestors. Viral channels are among only a few naturally occurring models to study the structure, function and evolution of primordial channels. Experimental studies of these properties are difficult and often unreliable. In principle, computational methods, and molecular dynamics (MD) simulations in particular, can aid in providing information about both the structure and the function of ion channels. However, MD suffers from its own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. It is, therefore, essential to determine the reliability of MD simulations. We propose to do so on the basis of two criteria. One is channel stability on time scales that extend for several microseconds or longer. The other is the ability to reproduce the measured ionic conductance as a function of applied voltage. If both the stability and the calculated ionic conductance are satisfactory it will greatly increase our confidence that the structure and the function of a channel are described sufficiently accurately. To our knowledge, long time scale stability (approx.10 micro-sec) and the correct electrophysiology have been shown so far for only one channel - the synthetic LS3 hexamer). In this presentation, this approach will be discussed in application to two viral channels - Vpu, encoded by the HIV-1 genome and p7 of hepatitis C.

Pohorille, Andrzej↗

DOE OSTI2025

An Atomistic Study of Reactivity in Solid-State Electrolyte Interphase Formation for Li/Li7P3S11

Lithium metal batteries offer superior volumetric and gravimetric specific capacities compared to those based on traditional graphite anodes. Although advancements in solid-state electrolytes address safety concerns, challenges remain, particularly regarding interphase formation in lithium metal anodes. This work presents a computational framework based on high-throughput first-principles density functional theory and machine-learning interatomic potentials (MLIPs) including automated iterative, active learning to enable robust computational exploration of interphase formation between lithium metal anodes and an inorganic solid-state electrolyte. As a demonstration, we apply the framework to a Li/Li7P3S11 interface and find that it accurately identifies the experimentally observed, thermodynamically stable interphase products as well as their overall spatial arrangement within a heterogeneous, amorphous layered structure, with Li2S domains of nanocrystallinity. Our simulations show two stages, a fast and slow diffusion reaction regime, that corroborate the relative phase formation rate of Li x P, Li2S, and Li3P. Using the Onsager transport theory, we capture time-dependent ionic diffusion within the reacting interface, including cross-correlation effects. We found that cross-correlation effects between Li-P and P-S ionic motion significantly influence P-ion diffusion, making it highly sensitive to the local environment and potentially leading to "kinetic trapping" of Li-P phases. The passivation of the interface is shown as the ionic fluxes all approach zero, effectively halting interphase growth.

Diffusion↗

DOE OSTI2026

The structure, composition, and performance impact of a YSZ-GDC interdiffusion layer in solid oxide electrolysis cells

This study provides a combined experimental and computational investigation into the structure and impact of the cation interdiffusion layer that appears at the gadolinium doped ceria (GDC)/yttria stabilized zirconia (YSZ) interface in solid oxide electrolysis cells (SOECs). Scanning transmission electron microscopy (STEM) illustrates that a ∼0.4 μm interdiffusion layer (IDL) with an intermixed cation distribution and fine grain size forms upon sintering. STEM identifies that the interdiffusion layer exists in the cubic fluorite structure despite changes in cation composition. The interdiffusion layer microstructure formed during sintering does not change during SOEC testing at either 1.3V or heightened voltage pulse testing. Modeling predicts that ionic conductivity may decrease in the interdiffusion layer due to Coulombic trapping between mobile oxygen vacancies and excess Gd 3+ acceptor dopants. Yet, the density and continuous nature of the layer should benefit cell stability by substantially reducing the formation of SrZrO 3 , which is corroborated by STEM and Synchrotron X-ray diffraction (XRD). We conclude that the interdiffusion layer acts as a beneficial barrier to Sr diffusion, when operating in a regime where electrolyte void formation is not observed.

organic↗

DOE OSTI2025

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗