Ab Initio Model Research Articles

Exploring low-cost high energy NASICON cathodes for sodium-ion batteriesviaa combined machine-learning,ab initio, and experimental approach

This study demonstrated the fusion of machine-learning,ab initio, and experimental approaches model to develop new NASICON type cathodes including Na3.5MnV0.5Ti0.5(PO4)3, Na3.5MnV0.5Fe0.5(PO4)3, and Na3.5MnV0.5Al0.5(PO4)3for SIBs.

Thermoelectric properties of Pnma and R3m GeS and GeSe

A fully ab initio modelling workflow is used to predict the thermoelectric figure of merit ZT of the Pnma and R3m phases of GeS and GeSe. Our results suggest that n-type GeSe may be a good partner for p-type SnSe in a thermoelectric couple.

Crystal phase engineering of silicene by Sn-modified Ag(111).

The synthesis of silicene by direct growth on silver is characterized by the formation of multiple phases and domains, posing severe constraints on the spatial charge conduction towards a technological transfer of silicene to electronic transport devices. Here we engineer the silicene/silver interface by two schemes, namely, either through decoration by Sn atoms, forming an Ag2Sn surface alloy, or by buffering the interface with a stanene layer. Whereas in both cases Raman spectra confirm the typical features as expected from silicene, by electron diffraction we observe that a very well-ordered single-phase 4 × 4 monolayer silicene is stabilized by the decorated surface, while the buffered interface exhibits a sharp phase at all silicon coverages. Both interfaces also stabilize the ordered growth of a phase in the multilayer range, featuring a single rotational domain. Theoretical ab initio models are used to investigate low-buckled silicene phases (4 × 4 and a competing one) and various structures, supporting the experimental findings. This study provides new and promising technology routes to manipulate the silicene structure by controlled phase selection and single-crystal silicene growth on a wafer-scale.

Non-volatile resistive switching mechanism in single-layer MoS2 memristors: insights from ab initio modelling of Au and MoS2 interfaces.

Non-volatile memristive devices based on two-dimensional (2D) layered materials provide an attractive alternative to conventional flash memory chips. Single-layer semiconductors, such as monolayer molybdenum disulphide (ML-MoS2), enable the aggressive downscaling of devices towards greater system integration density. The "atomristor", the most compact device to date, has been shown to undergo a resistive switching between its high-resistance (HRS) and low-resistance (LRS) states of several orders of magnitude. The main hypothesis behind its working mechanism relies on the migration of sulphur vacancies in the proximity of the metal contact during device operation, thus inducing the variation of the Schottky barrier at the metal-semiconductor interface. However, the interface physics is not yet fully understood: other hypotheses were proposed, involving the migration of metal atoms from the electrode. In this work, we aim to elucidate the mechanism of the resistive switching in the atomristor. We carry out density functional theory (DFT) simulations on model Au and ML-MoS2 interfaces with and without the presence of point defects, either vacancies or substitutions. To construct realistic interfaces, we combine DFT with Green's function surface simulations. Our findings reveal that it is not the mere presence of S vacancies but rather the migration of Au atoms from the electrode to MoS2 that modulate the interface barrier. Indeed, Au atoms act as conductive "bridges", thus facilitating the flow of charge between the two materials.

Planar Gliding and Vacancy Condensation: The Role of Dislocations in the Chemomechanical Degradation of Layered Transition-Metal Oxides

Stacking faults driven by dislocations have been observed in layered transition-metal oxide cathodes both in cycled and uncycled materials. The reversibility of stacking-sequence changes directly impacts the material performance. Irreversible glide due to lattice invariance or local compositional changes can initiate a catastrophic sequence of degradation mechanisms. In this study we compare the chemomechanical properties of LiCoO2 and LiNiO2 by combining density functional theory and anisotropic linear elasticity theory. We calculate stacking fault energies as a function of Li content and quantify the extent to which excess Ni hinders stacking-sequence changes. We then characterize screw dislocations, which mediate stacking-sequence changes, and find a peculiarly compliant behavior of LiNiO2 due to the interaction of Jahn–Teller distortions with the dislocation strain field. Finally, we analyze the tendency of vacancies to segregate along dislocation lines. This study represents the first instance of explicit ab initio atomistic dislocation models in layered oxides and paves the way for the understanding and optimization of the chemomechanical behavior of cathode active materials during battery operation.

Microscopic insight into structural and optical properties of glassy TeO2 derived from finite-cluster ab initio modelling

The paper reports on theoretical analysis of structural and non-linear optical properties of different size and shape TeO2 clusters using ab initio hybrid functional approximation to density functional theory. The obtained structural properties reveal uncommon structural units for crystal, which are common for amorphous tellurium oxide glass. The pair distribution function reproduces the experimental data in very good agreement, as well as the calculated phonon density and the Raman spectra. The finite field method was applied to evaluate the values of third order nonlinear susceptibility. The obtained values are in line with experimental data. This opens possibility to use such clusters to analyze the structural organization, vibrational and dielectric properties of the tellurium oxide glass.

Predicting Material Properties of Methane Hydrates with Cubic Crystal Structure Using Molecular Simulations

AbstractFormation of gas hydrates is an important feature of water systems. It occurs undesirably in natural gas pipelines, but also in deep‐sea deposits and unfreezing permafrost. However, the natural occurrence is of particular interest because methane hydrates have one of the highest energy densities of all naturally occurring forms of methane. Therefore, an accurate description of its thermodynamic properties is required. In this work, we demonstrate how the material properties of methane hydrate can be more easily calculated compared to ab initio methods. Furthermore, it is shown how the material properties depend on the cage occupancy by using the comparably fast self‐consistent‐charge density‐functional tight‐binding (SCC‐DFTB) method. The cell potential is calculated and compared to a numerical as well as an ab initio model, and is in good agreement with the literature.

XANES Studies of Zinc Tin Oxide Films Deposited by Atomic Layer Deposition: Revealing Process-Structure Relationships for Amorphous Oxide Semiconductors

Amorphous oxide semiconductors have grown in technological relevance in displays, information technology, energy, and catalysis. Recent research efforts have converged on the need to develop design principles for the electronic structure of these materials. Here, we systematically vary the cation composition and annealing temperatures of zinc tin oxide films using atomic layer deposition (ALD) and study their process-structure relationships with synchrotron X-ray absorption near-edge spectroscopy (XANES). Measurements of the O K-edge, Sn M-edge, and Zn L-edge are analyzed with ab initio and nonlinear statistical modeling to understand the changes in geometric and electronic structure of the films. A key finding from this approach is the ability to measure the changes in the relative contribution of the Zn and Sn s orbitals to the density of states near the conduction band minimum. Furthermore, we identify and delineate critical process-structure design principles when working with amorphous oxide semiconductor (AOS) material systems: (1) use of complementary diffraction and absorption spectroscopy techniques to characterize the as-deposited coordination environment; (2) accounting for gradual and abrupt changes in coordination environment as a function of processing parameters (stoichiometry, annealing, etc.); (3) revealing and exploiting the relevant knowledge and interdependence of coordination environments, orbital hybridizations, the density of states, and band structures. In the future, this multimodal X-ray analysis and modeling framework can be applied to understand the process-structure relationships needed to optimize AOS performance in devices.

Liquid-Liquid Transition in Water from First Principles.

A long-standing question in water research is the possibility that supercooled liquid water can undergo a liquid-liquid phase transition (LLT) into high- and low-density liquids. We used several complementary molecular simulation techniques to evaluate the possibility of an LLT in an abinitio neural network model of water trained on density functional theory calculations with the SCAN exchange correlation functional. We conclusively show the existence of a first-order LLT and an associated critical point in the SCAN description of water, representing the first definitive computational evidence for an LLT in water from first principles.

In silico identification and characterization of potential druggable targets among hypothetical proteins of Leptospira interrogans serovar Copenhageni: a comprehensive bioinformatics approach

Leptospirosis is one of the neglected zoonosis, affecting human and animal populations worldwide. Reliable effective therapeutics and concerns to look for more research into the molecular analysis of its genome is therefore needed. In the genomic pool of the Leptospira interrogans many hypothetical proteins are still uncharacterized. In the current research, we performed extensive in silico analysis to prioritize the potential hypothetical proteins of L. interrogans serovar Copenhageni via stepwise reducing the available hypothetical proteins (Total 3606) of the assembly to only 15, based on non-homologous to homosapien, essential, functional, virulent, cellular localization. Out of them, only two proteins WP_000898918.1 (Hypothetical Protein 1) & WP_001014594.1 (Hypothetical Protein 2) were found druggable and involved in protein-protein interaction network. The 3 D structures of these two target proteins were predicted via ab initio homology modeling followed by structures refinement and validation, as no structures were available till date. The analysis also revealed that the functional domains, families and protein-protein interacting partners identified in both proteins are crucial for the survival of the bacteria. The binding cavities were predicted for both the proteins through blind and specific protein-ligand docking with their respective ligands and inhibitors and were found to be in accordance with the druggable sites predicted by DoGSiteScorer. The docking interactions were found within the active functional domains for both the proteins while for Hypothetical Protein 2, the same residues were involved in interactions with Cytidine-5'-triphosphate in blind and specific docking. Furthermore, the simulations of molecular dynamics and free binding energy revealed the stable substrate binding and efficient binding energies, and were in accordance to our docking results. The work predicted two unique hypothetical proteins of L. interrogans as a potential druggable targets for designing of inhibitors for them. Communicated by Ramaswamy H. Sarma

Moisture Dependent Degradation Rate of Silicone in LED Optical Housing Material—Ab-Initio Modelling

Degradation of LED housings which make up of polydimethylsiloxanes (PDMS) in outdoor applications has been one of the rising concerns as they reduce the overall lifetime of the LED leading to cost and safety issues. The primary stressors for such LED degradation were found to be humidity and light emitted from the LED dice. The degradation mechanisms are hydrolysis and condensation of PDMS which themselves are interdependent. The degradation rate was also found to be dependent on the humidity level. This work identifies these dependencies, using ab-initio density functional theory and molecular dynamics simulation, and the results agree with the reported experimental data. From the detail understanding of the degradation mechanisms and the identification of the rate determining factors which are moisture level and the level of light absorption in PDMS, acceleration models commonly used for extrapolation are questioned, and new quality indexes of the PDMS are also identified to ensure the durability of LEDs in outdoor applications. Testing method to evaluate these new quality indexes is also proposed.

Effect of amphiphilic environment on the solution structure of mouse TSPO translocator protein

The translocator protein (TSPO) is a ubiquitous transmembrane protein of great pharmacological interest thanks to its high affinity to many drug ligands. The only high-resolution 3D-structure known for mammalian TSPO was obtained by NMR for the mouse mTSPO in DPC detergent only in presence of the high-affinity PK 11195 ligand. An atomic structure of free-ligand mTSPO is still missing to better understand the interaction of ligands with mTSPO and their effects on the protein conformation.Here, we decipher the solution structures of the recombinant mTSPO without ligand both in (i) SDS, the detergent used to extract and purify the protein from E. coli inclusion bodies, and (ii) DPC, the detergent used to solve the PK 11195-binding mTSPO NMR structure.We report partially refolded and less flexible mTSPO helices in DPC compared to SDS. Besides, DPC stabilizes the tertiary structure of mTSPO, as shown by a higher intrinsic Trp fluorescence and changes in indole environment.We evaluate by SEC-MALLS that ∼135 SDS and ∼100 DPC molecules are bound to mTSPO. SEC-small-angle X-ray (SAXS) and neutron (SANS) scattering confirm a larger mTSPO-detergent complex in SDS than in DPC. Using the contrast-matching technique in SEC-SANS, we demonstrate that mTSPO conformation is more compact and less flexible in DPC than in SDS. Combining ab initio modeling with SANS, we confirm that mTSPO conformation is less elongated in DPC than in SDS. However, the free-ligand mTSPO envelope in DPC is not as compact as the PK 11195-binding protein NMR structure, the ligand stiffening the protein.

Using deep-learning predictions of inter-residue distances for model validation.

Determination of protein structures typically entails building a model that satisfies the collected experimental observations and its deposition in the Protein Data Bank. Experimental limitations can lead to unavoidable uncertainties during the process of model building, which result in the introduction of errors into the deposited model. Many metrics are available for model validation, but most are limited to consideration of the physico-chemical aspects of the model or its match to the experimental data. The latest advances in the field of deep learning have enabled the increasingly accurate prediction of inter-residue distances, an advance which has played a pivotal role in the recent improvements observed in the field of protein ab initio modelling. Here, new validation methods are presented based on the use of these precise inter-residue distance predictions, which are compared with the distances observed in the protein model. Sequence-register errors are particularly clearly detected and the register shifts required for their correction can be reliably determined. The method is available in the ConKit package (https://www.conkit.org).

Perturbation approach to improve the angular tolerance of high-Q resonances in metasurfaces.

The interest in highqualityfactor (high-Q) resonances in metasurfaces has been rekindled with the rise of the bound states in the continuum (BIC) paradigm, which describes resonances with apparently limitlessly high quality-factors (Q-factors). The application of BICs in realistic systems requires the consideration of the angular tolerance of resonances, however, which is an issue that has not yet been addressed. Here, we develop an ab-initio model, based on temporal coupled mode theory, to describe the angular tolerance of distributed resonances in metasurfaces that support both BICs and guided mode resonances (GMRs). We then discuss the idea of a metasurface with a perturbed unit cell, similar to a supercell, as an alternative approach for achieving high-Q resonances and we use the model to compare the two. We find that, while sharing the high-Q advantage of BIC resonances, perturbed structures feature higher angular tolerance due to band planarization. This observation suggests that such structures offer a route toward high-Q resonances that are more suitable for applications.

Nucleation Rate Theory for Coordination Number: Elucidating Water-Mediated Formation of a Zigzag Na2SO4 Morphology.

Predicting and controlling nanostructure formation during nucleation can pave the way to synthesizing novel energy materials via crystallization. However, such control over nucleation and crystallization remains challenging due to an inadequate understanding of critical factors that govern evolving atomistic structures and dynamics. Herein, we utilize coordination number as a reaction coordinate and rate theory to investigate how sodium sulfate, commonly known as a phase-change energy material, nucleates in a supersaturated aqueous solution. In conjunction with ab initio and force field-based molecular dynamics simulation, the rate theoretical analysis reveals that sodium sulfate from an initially dissolved metastable state transits to a heterogeneous mixture of prenucleated clusters and finally to a large cylindrical zigzag morphology. Measurements of Raman spectra and their ab initio modeling confirm that this nucleated morphology contains a few waters for every sulfate. Rate processes such as solvent exchange and desolvation exhibit high sensitivity to the evolving prenucleation/nucleation structures, providing a means to distinguish between critical nucleation precursors. Desolvation and forming the first-shell interionic coordination structure via monomer-by-monomer addition around sulfates are found to explain the formation of large nuclei. Thus, a detailed understanding of the step-by-step structure formation across scales has been achieved. This can be leveraged to predict nucleation-related structures and dynamics and potentially control the synthesis of novel phase-change materials for energy applications.

Nuclear physics uncertainties in light hypernuclei

The energy levels of light hypernuclei are experimentally accessible observables that contain valuable information about the interaction between hyperons and nucleons. In this work we study strangeness $S = -1$ systems $^{3,4}_\Lambda$H and $^{4,5}_\Lambda$He using the ab initio no-core shell model (NCSM) with realistic interactions obtained from chiral effective field theory ($\chi$EFT). In particular, we quantify the finite precision of theoretical predictions that can be attributed to nuclear physics uncertainties. We study both the convergence of the solution of the many-body problem (method uncertainty) and the regulator- and calibration data-dependence of the nuclear $\chi$EFT Hamiltonian (model uncertainty). For the former, we implement infrared correction formulas and extrapolate finite-space NCSM results to infinite model space. We then use Bayesian parameter estimation to quantify the resulting method uncertainties. For the latter, we employ a family of 42 realistic Hamiltonians and measure the standard deviation of predictions while keeping the leading-order hyperon-nucleon interaction fixed. Following this procedure we find that model uncertainties of ground-state $\Lambda$ separation energies amount to $\sim 20(100)$ keV in $^3_\Lambda$H($^4_\Lambda$H,He) and $\sim 400$ keV in $^5_\Lambda$He. Method uncertainties are comparable in magnitude for the $^4_\Lambda$H,He $1^+$ excited states and $^5_\Lambda$He, which are computed in limited model spaces, but otherwise much smaller. This knowledge of expected theoretical precision is crucial for the use of binding energies of light hypernuclei to infer the elusive hyperon-nucleon interaction.

Confinement of the Triplet States in π-Conjugated BODIPY Dimers Linked with Ethynylene or Butadiynylene Bridges: A Different View on the Effect of Symmetry.

Understanding the impact of the excited state wavefunction confinement is crucial for the engineering of the photophysical properties and applications of organic chromophores. In the present contribution, the localization of the triplet state wavefunctions of some symmetric ethyne/butadiyne bridged BODIPY dimers and asymmetric BODIPY derivatives presenting extended π-conjugation frameworks is studied with time-resolved electron paramagnetic resonance spectroscopy and time-dependent density functional theory computations. Based on the Zero Field Splitting D parameters, we conclude that the triplet state wavefunctions are highly localized on one BODIPY unit in the symmetric dimers, which is consistent with the ab initio modelling that finds delocalized triplet state destabilized by 12-14 kcal mol-1 as compared to its localized counterpart. The result provides a new insight into the study of triplet excited state confinement and the design of molecular wires or photosensitizers for photovoltaics and photocatalysis.

Confinement of the Triplet States in π‐Conjugated BODIPY Dimers Linked with Ethynylene or Butadiynylene Bridges: A Different View on the Effect of Symmetry

AbstractUnderstanding the impact of the excited state wavefunction confinement is crucial for the engineering of the photophysical properties and applications of organic chromophores. In the present contribution, the localization of the triplet state wavefunctions of some symmetric ethyne/butadiyne bridged BODIPY dimers and asymmetric BODIPY derivatives presenting extended π‐conjugation frameworks is studied with time‐resolved electron paramagnetic resonance spectroscopy and time‐dependent density functional theory computations. Based on the Zero Field Splitting D parameters, we conclude that the triplet state wavefunctions are highly localized on one BODIPY unit in the symmetric dimers, which is consistent with the ab initio modelling that finds delocalized triplet state destabilized by 12–14 kcal mol−1 as compared to its localized counterpart. The result provides a new insight into the study of triplet excited state confinement and the design of molecular wires or photosensitizers for photovoltaics and photocatalysis.

Protein Structure Prediction with AlphaFold2, How it Works, Limitations and Solution for Less number of Homotypic and Large number of Heterotypic Contacts

Knowing the protein structure helps us to investigate diseases in human beings related to abnormal or impaired folded proteins. This research provides a solution for how to identify the misbalance of homotypic and heterotypic contacts on the sequential stage. There are two methods of protein structure prediction, template based and Ab-initio models. Template based model matches the given sequence with the original sequence. Whereas, Ab-initio calculates the weight of the given sequence and identifies whether it is balanced or not. If the sequence is not in balance, it can be labeled as on the initial stage by calculating its weight. In this research, future directions to researchers are provided as how to achieve maximum accuracy in protein structure prediction.

Computational Approaches to Alkaline Anion-Exchange Membranes for Fuel Cell Applications.

Anion-exchange membranes (AEMs) are key components in relatively novel technologies such as alkaline exchange-based membrane fuel cells and AEM-based water electrolyzers. The application of AEMs in these processes is made possible in an alkaline environment, where hydroxide ions (OH-) play the role of charge carriers in the presence of an electrocatalyst and an AEM acts as an electrical insulator blocking the transport of electrons, thereby preventing circuit break. Thus, a good AEM would allow the selective transport of OH- while preventing fuel (e.g., hydrogen, alcohol) crossover. These issues are the subjects of in-depth studies of AEMs-both experimental and theoretical studies-with particular emphasis on the ionic conductivity, ion exchange capacity, fuel crossover, durability, stability, and cell performance properties of AEMs. In this review article, the computational approaches used to investigate the properties of AEMs are discussed. The different modeling length scales are microscopic, mesoscopic, and macroscopic. The microscopic scale entails the ab initio and quantum mechanical modeling of alkaline AEMs. The mesoscopic scale entails using molecular dynamics simulations and other techniques to assess the alkaline electrolyte diffusion in AEMs, OH- transport and chemical degradation in AEMs, ion exchange capacity of an AEM, as well as morphological microstructures. This review shows that computational approaches can be used to investigate different properties of AEMs and sheds light on how the different computational domains can be deployed to investigate AEM properties.