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At least 109 records · Page 6

High-throughput computation of electric polarization in solids via Berry flux diagonalization

Electric polarization in the absence of an externally applied electric field is a key property of polar materials, but the standard interpolation-based ab initio approach to compute polarization differences within the modern theory of polarization presents challenges for automated high-throughput calculations. Berry flux diagonalization [J. Bonini et al., Phys. Rev. B 102, 045141 (2020)] has been proposed as an efficient and reliable alternative, though it has yet to be widely deployed. Here, we assess Berry flux diagonalization using ab initio calculations of a large set of materials, introducing and validating heuristics that ensure branch alignment with a minimal number of intermediate interpolated structures. Our automated implementation of Berry flux diagonalization succeeds in cases where prior interpolation-based workflows fail due to band-gap closures or branch ambiguities. Benchmarking with ab initio calculations of 176 candidate ferroelectrics, we demonstrate the efficacy of the approach on a broad range of insulating materials and obtain accurate effective polarization values with fewer interpolated structures than prior automated interpolation-based workflows. Our real-space heuristics that can predict gauge stability a priori from ionic displacements enable a general automated framework for reliable polarization calculations and efficient high-throughput screening of chemically and structurally diverse polar insulators. These results establish Berry flux diagonalization as a robust and efficient method to compute the effective polarization of solids and to accelerate the data-driven discovery of functional polar materials.

Poteshman, Abigail N. [University of Chicago, IL (

Nanoscale Bio-engineering Solutions for Space Exploration: The Nanopore Sequencer

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation, with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes.

Stolc, Viktor

Nanoscale Bioengineering Solutions for Space Exploration the Nanopore Sequencer

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation. with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes. http://phenomrph.arc.nasa.gov/index.php

Ioana, Cozmuta

Correlation of Band Bending and Ionic Losses in 1.68 eV Wide Band Gap Perovskite Solar Cells

Abstract Perovskite solar cells (PSCs) are promising for high‐efficiency tandem applications, but their long‐term stability, particularly due to ion migration, remains a challenge. Despite progress in stabilizing PSCs, they still fall short compared to mature technologies like silicon. This study explores how different piperazinium salt treatments using iodide, chloride, tosylate, and bistriflimide anions affect the energetics, carrier dynamics, and stability of 1.68 eV bandgap PSCs. Chloride‐based treatments achieved the highest power conversion efficiency (21.5%) and open‐circuit voltage (1.28 V), correlating with stronger band bending and n‐type character at the surface. At the same time, they showed reduced long‐term stability due to increased ionic losses. Tosylate‐treated devices offered the best balance, retaining 96.4% efficiency after 1000 h (ISOS‐LC‐1I). These findings suggest that targeted surface treatments can enhance both efficiency and stability in PSCs.

14 SOLAR ENERGY

Orthorhombic Structures as Inorganic Halide Perovskite Models for High-Throughput DFT Investigations

Although high-symmetry Pm-3m space group cubic models are computationally efficient for high-throughput density functional theory (DFT) calculations of inorganic ternary (ABX 3 ) halide perovskites (HPs), they frequently predict band gaps (E g ) that disagree with experiment. Conversely, while low-symmetry cubic polymorphous networks (PN) comprised of 160 to 320 atoms incur significantly greater computational cost, they predict E g ’s that are more closely aligned with experiment. Here, in this study, we compare the DFT total energies and E g ’s predicted by four high-symmetry structure models (Pnma orthorhombic, R3m trigonal, P4/mbm tetragonal, and Pm-3m cubic) to cubic PNs for 5 experimentally characterized ternary HPs and find that the orthorhombic model computes Eg’s with the smallest MAD of 0.23 eV relative to the PNs. Pair distribution functions and DFT-computed total energies show that octahedral tilting, which is present in the 20-atom orthorhombic and 160-atom cubic PN models but not in the 5-atom cubic models, stabilizes all 5 compositions in our benchmarking set. We also find that imposing PN constraints when generating and optimizing these orthorhombic structures by fixing the unit cell lattice vectors and displacing the atoms prior to ionic relaxation with DFT, which we call the orthorhombic surrogate model (OSM), lowers the MAD of E g predictions to 0.09 eV. Our OSM predicts the PN band gaps of an additional 95 theoretical inorganic ternary HPs with MAD of 0.08 eV, supporting its usage in high-throughput DFT investigations to closely estimate PN band gaps with much less computational expense.

14 SOLAR ENERGY

Computationally Guided Development of Components for High Energy Density Solid-State Lithium-Sulfur Batteries

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria1. The performance metrics for eVTOL craft, such as specific energy, specific power, and safety, exceed those of electric automobiles by a factor of two to four. Current state-of-the-art (SOA) lithium-ion batteries are incapable of meeting the key performance criteria of energy and safety for eVTOL. Therefore, next generation advanced chemistries and designs must be developed to meet required performance metrics for electric aviation2. Beyond lithium-ion chemistries, such as lithium-sulfur, show promise in their high energy, while limitations exist in their power and cyclability due to low electrical conductivity and high intermediate solubility in organic liquid electrolytes. Several strategies to overcome the low electrical conductivity involve the use of selenium as a dopant in the active sulfur material, along with the incorporation of 2-dimensional electron-conducting holey-graphene to improve the composite cathodes electronic conductivity. Furthermore, combining this chemistry with a solid-electrolyte avoids the components’ dissolution issues3. However, the development of composite solid-state cathodes is non-trivial as several components must be intimately mixed so that the active component has sufficient access to both electrons and lithium ions to undergo full electrochemical conversion. Mathematical modeling of battery components can assist experimental design through a robust and rigorous combination of computational modeling techniques covering multiple length scales. The objective is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build and test solid state lithium-sulfur cells and packs. A NASA-based cross-organizational team of high-powered experts combined integrated computational predictive modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. This presentation will show a multiscale computational modeling approach that has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM modeling targets the 1-10 µm scale structures and provides electromechanical and grain interactions for predictive design guidelines for the manufacturing of solid-state components. Parameters such as particle size and volume fraction of the constituent materials were modeled and experimentally fabricated to optimize electrochemical performance through improved microstructure design. Experimental feedback was provided through ionic and electronic conductivity assessment and structural analysis of developed materials and cell components.

battery

Cathode Modeling of Solid-State Batteries

The search for safe, reliable, and compact high-capacity energy storage devices has led to increased interest in all-solid-state battery research. The use of solid electrolytes provides enhanced safety and durability due to their reduced flammability and increased mechanical strength compared to organic liquid electrolytes. Still, the use of solid electrolytes remains challenging. Computational modeling plays a substantial role in addressing these challenges. A particle dynamics electromechanical model for simulating electrochemical processes in a solid-state battery cathode will be presented. The model presents cathode microstructure at the particle level as a mixture of ionically conductive solid electrolyte particles, electrically conductive carbon additives, and cathodic reactant particles. After densification, the particle connectivity is analyzed to reconstruct the complex electric network connecting reactant particles with an anodic and cathodic current collectors through the electrolyte and carbon particles. The Kirchhoff’s matrix equation describing this electric network, is solved to obtain values of various critical parameters, such as the overall conductivity of the cathode for lithium ions and electrons, cathodic reactant material utilization, and the distribution of the electric current and voltages within the cathode. In addition, by representing the reactant particles as electrolyte or galvanic microcells governed by the Butler-Volmer electrochemical equation, the overall performance of battery cells during charge or discharge processes, respectively, can be predicted for a given cathodic powder composition. The presented model, executed on a high-performance computing architecture, essentially provides a valuable guidance in designing and developing future solid-state batteries.

solid-state battery

Computational Analysis of Anode and Cathode Structuring Effects on Charge and Discharge in Graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 Batteries

Structured electrodes (SEs) improve the rate capability of Lithium-ion batteries by engineering micrometer-scale electrolyte regions into the electrode, promoting rapid ionic transport. Prior research has focused on structuring one electrode (anode or cathode) with an analysis on either the charge or discharge performance. We present a holistic study using three-dimensional models to investigate the isolated effects of structuring either electrode and the combined effects of structuring both electrodes on the charge and discharge capacity of single-layer cells at 4 C and 6 C. Volumetric and gravimetric discharge energy density (Wh/L stack and Wh/kg stack ) and charge capacity (Ah/kg stack and Ah/L stack ) are evaluated for multi-layer pouch cell stacks. Pairing SE anodes with SE cathodes demonstrated improvements up to 15% in discharge Wh/kg stack and up to 33% in charge Ah/kg stack over a conventional cell; Energy required to charge per Ah/kg stack was improved by 13%–14%. SE cathodes paired with a conventional anode exhibited improvements of 0.3%–22% across all performance metrics evaluated. Conversely, pairing a SE anode with a conventional cathode demonstrated improved charge capacity up to 13% but showed a 2%–23% lower discharge energy density. The importance of aligning SEs in a cell from a performance and manufacturing perspective is also analyzed.

25 ENERGY STORAGE

Atomistic Insights into Lithium–Glyme Solvate Ionic Liquids: Effects of Chain Length and Anion Coordination

For this study, mixtures of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in diglyme (G2), triglyme (G3) and tetraglyme (G4) at solvate ionic liquid (SIL) concentrations were investigated using classical molecular dynamics (cMD) simulations with a physically motivated force-field specifically developed for modeling these systems. The structural and dynamical properties of the mixtures were computed and analyzed. Lithium solvation shells, radial distribution functions, and X-ray structure factors were studied across the different SIL systems. Translational diffusion and rotational relaxation times were also evaluated, exhibiting similar trends with increasing glyme chain length. The results are consistent with experimental data and in good agreement with previous computational studies on G3 and G4. These findings validate the accuracy of the force field in modeling glyme systems and its use for describing the [Li(G2) 4/3 ][TFSI] mixture. Additionally, the thermal and electrochemical stability of these electrolytes were systematically examined. The thermal stability appears to be governed by cooperative interactions among glyme molecules, while the electrochemical stability is primarily influenced by Li + -anion interactions, which vary significantly with glyme chain length. Overall, the study sheds light on the crucial role of the anion in these glyme-based SILs and offers valuable insights into Li + -glyme systems at SIL concentrations, highlighting their promise as potential Li-ion battery electrolytes.

anions

From Structured Solvents to Hybrid Materials (SS2HM) for Chemically Selective Capture and Electromagnetic Release of CO 2 : Mechanisms, Stability and Interfaces (Final Report)

The goal of this research program was to develop high capacity sorbents amenable for alternative regeneration approaches for direct air capture (DAC) of CO 2 . In particular, the research aimed to develop an understanding of CO 2 binding mechanism, thermal and oxidative stability, and regeneration energetics of functionalized ionic liquids (ILs), deep eutectic solvents (DESs), and porous materials. ILs and DESs are high-dielectric solvents with structural tunability that permits the rational-design for energy-efficient regeneration approaches based on electromagnetic (EM) field and moisture-swing. By further incorporating these solvents into polymeric capsules and other structural supports, multi-scale interfaces for targeted CO 2 and energy transfers were achieved. Aspects related to CO 2 capacity, selectivity, stability, dielectric properties, and binding energies were examined through experimental and computational design to identify molecular descriptors to inform future design of structured solvents and hybrid materials for DAC. Enclosed final report details the key findings, science advancements, and workforce development efforts from this project.

36 MATERIALS SCIENCE

Molecular Dynamics Simulations of Liquid and Polymer Electrolytes for Energy Storage Devices

Advancing beyond current lithium-ion technology is necessary in order to enable energy storage devices for electric airplanes. Electrolyte stability is a key limiting factor, yet the design of improved electrolytes remains a formidable challenge. Molecular dynamics (MD) simulations are a powerful tool for studying electrolytes, since they can be used to evaluate structural, thermodynamic, and transport properties, and can provide molecular-level detail often inaccessible to experimental techniques. Our computational materials groups at the NASA Ames Research Center has developed models and methods to accurately simulate both liquid and polymer electrolytes.We report the results from atomistic MD simulations of several electrolyte materials, with lithium salts dissolved in ionic liquids, dimethoxyethane (DME), and polyethylene oxide (PEO). For improved accuracy, we employ polarizable models, where each atom is given an environment-dependent atomic dipole. The simulations accurately predict bulk transport properties, including viscosity, diffusion, and ionic conductivity, in quantitative agreement with available experimental data. Moreover, the simulations provide important insights into the solvation structure of the lithium ions.We also report the results from coarse-grained MD simulations of polyanion electrolytes. In order to more efficiently capture the longer length- and time-scales of these systems, we employ a generic bead-spring model. These simulations provide important insight into how the polymer chain architecture and ionic interaction strengths affect the ionic aggregation behavior and cation dynamics. Despite the simplicity of the model, the simulations yield qualitative agreement with experimental data for similar systems.

Abbott, Lauren J.

Study of the extra-ionic electron distributions in semi-metallic structures by nuclear quadrupole resonance techniques

A straightforward self-consistent method was developed to estimate solid state electrostatic potentials, fields and field gradients in ionic solids. The method is a direct practical application of basic electrostatics to solid state and also helps in the understanding of the principles of crystal structure. The necessary mathematical equations, derived from first principles, were presented and the systematic computational procedure developed to arrive at the solid state electrostatic field gradients values was given.

Murty, A. N.

Theoretical study of the bonding of Nb(2+) to CH2, C2H2, and C2H4

The bonding of Nb(2+) with CH2, C2H2, and C2H4 is studied by using electronic structure calculations that include high levels of electron correlation. The binding energy for NbCH2(2+) is in good agreement with the lower bound determined from the reaction with CH4 but is significantly smaller than the value determined from the binding energy and ionization potential of NbCH2(+). The calculations and a new interpretation of the experiment indicate that the larger value is in error primarily because the ionization potential of NbCH2(+) determined from bracketing charge-exchange reactions is too small. The computed binding energy of NbC2H2(2+) is in good agreement with experiment. The calculations show that the bonding is predominantly covalent in character for both NbCH2(2+) and NbC2H2(2+), whereas for NbC2H4(2+) the electronic states that are predominantly ionic and covalent are nearly degenerate. The trend in binding energies, CH2 greater than C2H2 greater than C2H4, is consistent with the energy required to prepare the ligands for bonding.

Bauschlicher, Charles W., Jr.

Simulating Droplet-Resolved Haze and Cloud Chemistry Forming Secondary Organic Aerosols in Turbulent Conditions within Laboratory and Cloud Parcels

Most of our existing knowledge of cloud chemistry in regards to forming secondary organic aerosols (SOA) is based on measurements in bulk aqueous solutions. However, SOA reaction kinetics derived from bulk solution measurements might differ from the kinetics in actual cloud droplets, since turbulent mixing and ionic strengths, and ratio of surface area to volume in individual cloud droplets might vary substantially from bulk solutions in the real atmosphere. Three-dimensional models at various scales have been used to simulate aqueous chemistry. However, most of these models do not resolve turbulence down to the smallest length scales of 1 mm and do not simulate cloud chemistry in individual cloud droplets due to large computational costs. Here we incorporate the formation of isoprene epoxydiol SOA (IEPOX-SOA) in individual droplets within a one-dimensional explicit mixing parcel model (EMPM-Chem). We apply EMPM-Chem to simulate turbulence and droplet-resolved IEPOX-SOA formation using a configuration based on the Michigan Tech Pi chamber. We find that the dissolution of IEPOX gases is weighted more towards larger cloud droplets due to their large liquid water content (compared to smaller droplets), while the conversion of dissolved IEPOX to IEPOX-SOA is much greater within smaller deliquesced haze particles due to their higher acidity and ionic strengths compared to cloud droplets. We also find that as droplet residence times increase in the chamber, e.g., due to increasing ammonium bisulfate seed aerosol injection rates and/or increasing heights of the chamber, formation of IEPOX-SOA increases substantially. Thus, our EMPM-Chem model could be used to design future cloud chambers to maximize SOA production from cloud chemistry. We also apply the EMPM-Chem model to simulate how IEPOX-SOA formation evolves in individual cloud droplets within rising cloudy parcels in the atmosphere. We find that as subsaturated air is entrained into and turbulently mixed with the cloud parcel, evaporation causes a reduction in droplet sizes, which leads to corresponding increases in per droplet ionic strength and acidity. Increased droplet acidity in turn greatly accelerates the kinetics of IEPOX-SOA formation. In conclusion, our results provide key insights into single-cloud-droplet chemistry, suggesting that entrainment mixing may be an important process that increases SOA formation in the real atmosphere.

54 ENVIRONMENTAL SCIENCES

Photoelectron escape from the ionosphere of Jupiter

Photoelectron escape fluxes and ambient electron heating from the Jovian ionosphere are computed as a function of local time and latitude. Several differences for the fluxes expected from a hydrogen atmosphere, rather than a terrestrial type of atmosphere, are described, including an increase in structure in the energy spectra due to the paucity of ionic states entering the photo-ionization processes and lower escape fluxes above 10 eV than were expected from a simple scaling of earth fluxes.

Swartz, W. E.

Nonvolatile Ionic Two-Terminal Memory Device

Conceptual solid-state memory device nonvolatile and erasable and has only two terminals. Proposed device based on two effects: thermal phase transition and reversible intercalation of ions. Transfer of sodium ions between source of ions and electrical switching element increases or decreases electrical conductance of element, turning switch "on" or "off". Used in digital computers and neural-network computers. In neural networks, many small, densely packed switches function as erasable, nonvolatile synaptic elements.

Williams, Roger M.

Structural origin of disorder-induced ion conduction in NaFePO 4 cathode materials

Diffusion in NaFePO 4 can be enhanced through amorphization. Based on computations using DFT and machine learning potentials, we ascribe this phenomenon to the formation of less constrained Na-ion environments upon disordering. Most modern battery technologies depend on solid-state crystalline cathode materials. However, some of these materials are constrained by the low ionic conductivity of their most stable phases. An example of this is maricite (NaFePO 4 ). Interestingly, experiments have shown that maricite can improve its rate capability through disordering (amorphization). However, experimental characterization of amorphous cathode materials remains a major challenge, hindering a clear understanding of the structural origin of the disorder-induced improvement in sodium-ion mobility. To address this, we here employ molecular dynamics simulations by first training a machine learning potential for NaFePO 4 based on the atomic cluster expansion approach and a batch active learning potential parameterization scheme. This potential is then applied to explore the structural and dynamical properties of NaFePO 4 glasses as cathode materials. Specifically, we investigate the effect of glass structure on sodium-ion diffusion, revealing the relative influences of short-range and medium-range order features. We find significant heterogeneity in sodium-ion diffusivity in the glass, with fast-conducting ions residing in less constrained atomic environments with fewer P and Fe neighbors. These more mobile ions are also surrounded by larger ring-type structures. Overall, the results and developed approach present promising avenues for developing high-performance glassy cathodes for next-generation batteries.

Christensen, Rasmus