Ground-state Structure Research Articles

Thermodynamics of phase stability and disorder in Inter-Lanthanide ternary ABO3 oxides from first principles

Inter-lanthanide ternary oxides (IL-ABO3) find application in various technological fields due to their diverse properties and flexible chemistries that are readily synthesizable in multiple crystal structures. Here, we investigate the chemistry-dependent thermodynamic formability and the tendency to disorder for IL-ABO3 (A, B = La–Lu) compounds having different structures using density functional theory. We reproduce the previously observed relationship between the IL-ABO3 crystal structure and difference in the A and B ionic radii. We investigate the formation of metastable phases, finding a region of IL-ABO3 chemistries with rich metastability in a small energy interval. We analyze the influence of disordering on the stability of the ground state structures, correlating the propensity for disorder with the energy difference between different cation orderings. Our results provide fundamental insights into the phase stability of IL-ABO3, the energetics of their metastable structures, and their tendency to disorder, paving the way towards their broader technological applicability.

Structural evolution, electronic and magnetic properties investigation of V3Sin− (n = 14–18) clusters based on photoelectron spectroscopy and density functional theory calculations

Silicon clusters doped with a transition metal (TM) atom have been intensively studied due to their novel properties and superior stability for possible usage as building blocks of future nanoelectronics. Besides the selection of the doped element, introducing the number of dopant atoms as another dimension adds versatility to tuning the cluster properties. However, there are few studies of silicon clusters doped with multiple TM atoms. Here, we present a study of V3Sin− (n = 14–18) by combining high-resolution photoelectron spectroscopy (PES) measurements with a search of their global minimum energy structures based on a homemade genetic algorithm coupled with density functional theory (DFT) for energy calculations. The simulated photoelectron spectra of the putative global minimum structures are in fair agreement with the experimental ones, which gives evidence for their authenticity as the ground-state structures. In these clusters the three V atoms always bond with each other and form an acute triangle, which can be seen as a nanoscale analogue of phase segregation in the bulk. For the size range n = 14–17, each of the ground-state structures has a silicon basket-like structure with the vanadium triangle inside, while V3Si18− has a baseball-mitt-like structure almost completely encapsulating the V3 triangle. The average binding energy of TMSin− (TM = V1, V2, V3) indicates that the more V atoms are doped the more stable the clusters are. Among these clusters, only V3Si14− have a total magnetic moment of 2 μB, making it a potential structural unit for magnetic storage devices. Mulliken population analysis and the electron spin density show that V atoms at different positions have different contributions to the total magnetic moments, and d electrons in V atoms contribute the most.

Targeting high symmetry in structure predictions by biasing the potential energy surface

Ground-state structures found in nature are, in many cases, of high symmetry. But structure prediction methods typically render only a small fraction of high-symmetry structures. Especially for large crystalline unit cells, there are many low-energy defect structures. For this reason, methods have been developed where either preferentially high-symmetry structures are used as input or where the whole structural search is done within a certain symmetry group. In both cases, it is necessary to specify the correct symmetry group beforehand. However, it can in general not be predicted which symmetry group is the correct one leading to the ground state. For this reason, we introduce a potential energy biasing scheme that favors symmetry and where it is not necessary to specify any symmetry group beforehand. On this biased potential energy surface, high-symmetry structures will be found much faster than on an unbiased surface and independently of the symmetry group to which they belong. For our two test cases, i.e., a ${C}_{60}$ fullerene and bulk silicon carbide, we get speedups of 25 and 63. In our data, we also find a clear correlation between the similarity of the atomic environments and the energy. In low-energy structures, all the atoms of a species tend to have similar environments.

Deciphering the Impact of Helium Tagging on Flexible Molecules: Probing Microsolvation Effects of Protonated Acetylene by Quantum Configurational Entropy

Helium, the lightest and most weakly interacting noble gas, is well-known for its unsurpassed chemical inertness. In many applications of helium in experimental techniques, such as tagging, messenger, or nanodroplet isolation action spectroscopy of molecules or complexes, it is assumed that the interaction of helium with the respective species, and thus the resulting interaction-induced perturbation, is small enough not to affect their structure and dynamics. Here, we probe the impact of one up to many attached helium atoms on protonated acetylene─an important nonclassical carbocation subject to three-center two-electron bonding in its ground state structure─using highly accurate interaction potentials in conjunction with entropy-based higher-order nonlinear correlation analysis. In particular, using neural network potentials at CCSD(T) accuracy, we disclose the specific structural perturbations due to the tagging of C2H3+ with up to 20 He atoms at a temperature of 1 K. Analysis reveals that microsolvation by helium influences the structure of C2H3+ noticeably, while our investigation of the quantum configurational information entropy additionally shows that correlations between individual orientational degrees of freedom are affected as a function of cluster size. In particular, it is found that the most probable bridge-like structure of the ro-vibrational quantum ground state of C2H3+, which is nonplanar and trans-bent in contrast to the perfectly planar equilibrium structure, becomes increasingly more localized upon adding helium atoms. The remarkably nonlinear behavior of the angular correlations as a function of cluster size is traced back to the buildup of the quantum microsolvation shell that enhances anisotropy up to NHe = 6 while more and more isotropic solvation takes over beyond six. Our approach is general and thus sets the stage to investigate the salient effects on the structure of flexible molecules due to tagging beyond the specific case.

Profiling the off-center atomic displacements in CuCl at finite temperatures with a deep-learning potential

Cuprous halides ($\mathrm{Cu}X$, $X=\mathrm{Cl}$, Br, or I) have been extensively investigated in the literature, but there still exist debates on whether the ground-state structures of $\mathrm{Cu}X$ are zinc blende. By performing molecular dynamics simulations at finite temperatures with a newly developed accurate deep-learning potential for CuCl, we find that, in the absence of accurate exchange interactions, there exist collective off-center displacements of Cu, leading to the formation of large complex Cu cluster structures. However, these cluster structures are unstable once exchange interactions are properly included. Nevertheless, due to strong anharmonicity, thermal fluctuations could also lead to sizable off-center Cu displacements, resulting in instantaneous small Cu clusters. Still, these cluster configurations are not stable or metastable in the ground state. We thus unambiguously demonstrate that, although anharmonic off-center displacements of Cu are present in CuCl at finite temperatures, zinc blende is still the thermodynamically most favorable phase. These insights are critical to the understanding of liquidlike anharmonic behavior of Cu atoms in various Cu-containing compounds, which impacts a number of important properties such as thermal conductivity, ferroelectricity, and superconductivity.

Ground states and magnonics in orthogonally coupled symmetric all-antiferromagnetic junctions

In this paper, the rich ground-state structure of orthogonally coupled symmetric all-antiferromagnetic junctions with easy-plane anisotropy is reported. A spin reorientation process rather than the traditional spin flop (SF) occurs, resulting in a phase in which N\'eel vectors preserve the mirror-reflection symmetry (termed MRS phase). The phase transitions in the ground state between SF and MRS phases can be either first or second order. After disturbed by external stimuli, magnons with different parities emerge. For in-plane dc fields, no couplings between magnons occur. When dc fields become oblique, coherent couplings between magnons with opposite parity emerge, leading to anticrossings in resonance frequencies. However, self-hybridization among magnons with the same parity never happens. More interestingly, spin waves based on MRS phases are linearly polarized and their polarization directions can be fine controlled.

Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network

Cryptic pockets expand the scope of drug discovery by enabling targeting of proteins currently considered undruggable because they lack pockets in their ground state structures. However, identifying cryptic pockets is labor-intensive and slow. The ability to accurately and rapidly predict if and where cryptic pockets are likely to form from a structure would greatly accelerate the search for druggable pockets. Here, we present PocketMiner, a graph neural network trained to predict where pockets are likely to open in molecular dynamics simulations. Applying PocketMiner to single structures from a newly curated dataset of 39 experimentally confirmed cryptic pockets demonstrates that it accurately identifies cryptic pockets (ROC-AUC: 0.87) >1,000-fold faster than existing methods. We apply PocketMiner across the human proteome and show that predicted pockets open in simulations, suggesting that over half of proteins thought to lack pockets based on available structures likely contain cryptic pockets, vastly expanding the potentially druggable proteome.

Algebraic Graph-Based Machine Learning Model for Li-Cluster Prediction.

In cluster research, determining the ground-state structure of medium-sized clusters is hindered by a large number of local minimum on potential energy surfaces. The global optimization heuristic algorithm is time-consuming due to the use of DFT to determine the relative size of the cluster energy. Although machine learning (ML) is proved to be a promising way to reduce the DFT computational costs, a suitable method to represent clusters as input vectors is one of the bottlenecks in the application of ML to cluster research. In this work, we proposed a multiscale weighted spectral subgraph (MWSS) as an effective low-dimension representation of clusters and build an MWSS-based ML model to discover the structure-energy relationships in lithium clusters. We combine this model with the particle swarm optimization algorithm and DFT calculations to search for globally stable structures of clusters. We have successfully predicted the ground-state structure of Li20.

Investigating the structural and electronic properties of anionic calcium-doped magnesium clusters

In recent years, the structure and properties of alkaline earth metal-doped Mg clusters have attracted much attention. Here, we investigated the structural properties, stability analysis, chemical bonding properties and charge transfer properties of Ca2Mgnˉ (n=1-15) nanoclusters by using the efficient CALYPSO structure search software and the DFT full domain search method based on B3PW91 level calculation. It is found that most of their ground state structures can inherit pure Mgn+2ˉ (n=1-15) clusters with high symmetry. We further compare the experimental and theoretical PES spectral data using pure Mgn+2ˉ (n=1-15) and find a high agreement, which also indicating the validity of my calculated all-domain most stable structure. We found the outstanding stability of the pentagonal Ca2Mg7ˉ by stability analysis. Charge transfer occurred in all Ca2Mgnˉ clusters, and this transfer was from Ca to Mg. The chemical bonding properties and molecular orbital revealed that the contribution of Mg-s and Mg-p to the molecular orbitals led to the formation of strong Mg-Mg bonds in the Ca2Mg7ˉ cluster, the s-p hybridization between Ca and Mg atoms and between Mg and Mg atoms also led to more powerful Mg-Mg bonds and Ca-Mg bonds, which is strong evidence for the stability of the Ca2Mg7ˉ clusters.

Identifying the ground state structures of point defects in solids

Point defects are a universal feature of crystals. Their identification is addressed by combining experimental measurements with theoretical models. The standard modelling approach is, however, prone to missing the ground state atomic configurations associated with energy-lowering reconstructions from the idealised crystallographic environment. Missed ground states compromise the accuracy of calculated properties. To address this issue, we report an approach to navigate the defect configurational landscape using targeted bond distortions and rattling. Application of our workflow to eight materials (CdTe, GaAs, Sb2S3, Sb2Se3, CeO2, In2O3, ZnO, anatase-TiO2) reveals symmetry breaking in each host crystal that is not found via conventional local minimisation techniques. The point defect distortions are classified by the associated physico-chemical factors. We demonstrate the impact of these defect distortions on derived properties, including formation energies, concentrations and charge transition levels. Our work presents a step forward for quantitative modelling of imperfect solids.

Structural phase stability and thermodynamical properties of transition metal complex hydrides Na2MgTMH7 (TM=Sc−Cu) for hydrogen storage applications

In order to predict ground state structure as well as thermodynamical properties of transition metal-based complex hydrides (TMCHs) and identify potential hydrogen storage materials for energy storage applications, we have performed first-principles density functional spin polarized total energy calculations for Na2MgTMH7 where TM ​= ​Sc, Ti, V, Cr, Mn, Fe, Co, Ni, and Cu. To investigate the thermodynamical properties of transition metal-based complex hydrides (TMCHs) and to find potential hydrogen storage materials for energy storage applications. Our spin-polarized calculations show that all these materials are having a finite magnetic moment at the transition metal site with ferromagnetic or anti−ferromagnetic ordering as ground state configuration except the cases where TM ​= ​Sc, Co, Ni, and Cu. Our calculated enthalpy of formation and hydrogen site energy of TMCHs suggest that these systems are stable and the hydrogen is expected to release at a relatively low temperature compared to that of pure binary hydrides. We have performed the chemical bonding analyses between the constituents of TMCHs through density of states, charge density, electron localization function, Born effective charge, Bader effective charge, Mulliken charge, and COHP and these analyses suggest that there is an ionic bonding between hydrogen with Na, Mg, and transition metal with noticeable covalent bonding between hydrogen and Mg/TM.

Do-It-Yourself 5-Color 3D Printing of Molecular Orbitals and Electron Density Surfaces

This report outlines an approach for preparing 5-color 3D printed plastic models of molecular orbitals and electron density surfaces using a hobby-grade 3D printer. Instructions are provided for preparing 3D orbital and electron density surface (EDS) models using solid or mesh representations in ground state and transition state structures. We show that the information content of 3D orbital and surface models can be enhanced with text annotation, bisection, strut and dashed bond placement, and composite orbital-EDS model constructions. Example prints illustrate orbital concepts in organic and inorganic chemistry, such as the ethyl cation (σ–p hyperconjugation), methane (hybridization and C–H bonding), ethane (σ–σ* hyperconjugation in the staggered and eclipsed conformations), 2-hydroxytetrahydropyran (the anomeric effect/n−σ* hyperconjugation), the water dimer (hydrogen bonding/n−σ* overlap), ethylene, 1,3-butadiene, and benzene (π molecular orbitals), Re2Cl82–, and U2(COT)2 (metal–metal quadruple bonds). Transition state models illustrate orbital interactions in the SN2 reaction of cyanide with methyl, ethyl, and isopropyl chloride and in a hydroboration reaction of BH3 with propene. Composite EDS models of methyl and isopropyl chloride (for exploring their relative reactivities as SN2 electrophiles) and methylcyclohexane (visualizing 1,3-diaxial interactions) are described. Student perceptions of a multicolor 3D orbital print used in an introductory organic chemistry laboratory course are reported.

Predicting the locations of cryptic pockets from single protein structures using the PocketMiner graph neural network.

Cryptic pockets expand the scope of drug discovery by enabling targeting of proteins currently considered undruggable because they lack pockets in their ground state structures. However, identifying cryptic pockets is labor-intensive and slow. The ability to accurately and rapidly predict if and where cryptic pockets are likely to form from a protein structure would greatly accelerate the search for druggable pockets. Here, we present PocketMiner, a graph neural network trained to predict where pockets are likely to open in molecular dynamics simulations. Applying PocketMiner to single structures from a newly-curated dataset of 39 experimentally confirmed cryptic pockets demonstrates that it accurately identifies cryptic pockets (ROC-AUC: 0.87) >1,000-fold faster than existing methods. We apply PocketMiner across the human proteome and show that predicted pockets open in simulations, suggesting that over half of proteins thought to lack pockets based on available structures are likely to contain cryptic pockets, vastly expanding the druggable proteome.

Ground-State Structure of Quaternary Alloys (SiC)1−x (AlN)x and (SiC)1−x (GaN)x

Despite III-nitride and silicon carbide being the materials of choice for a wide range of applications, theoretical studies on their quaternary alloys are limited. Here, we report a systematic computational study on the electronic structural properties of (SiC)x (AlN)1-x and (SiC)x (AlN)1-x quaternary alloys, based on state-of-the-art first-principles evolutionary algorithms. Trigonal (SiCAlN, space group P3m1) and orthorhombic (SiCGaN, space group Pmn21) crystal phases were as predicted for x = 0.5. SiCAlN showed relatively weak thermodynamic instability, while that of SiCGaN was slightly elevated, rendering them both dynamically and mechanically stable at ambient pressure. Our calculations revealed that the Pm31 crystal has high elastic constants, (C11~458 GPa and C33~447 GPa), a large bulk modulus (B0~210 GPa), and large Young's modulus (E~364 GPa), and our results suggest that SiCAlN is potentially a hard material, with a Vickers hardness of 21 GPa. Accurate electronic structures of SiCAlN and SiCGaN were calculated using the Tran-Blaha modified Becke-Johnson semi-local exchange potential. Specifically, we found evidence that SiCGaN has a very wide direct bandgap of 3.80 eV, while that of SiCAlN was indirect at 4.6 eV. Finally, for the quaternary alloys, a relatively large optical bandgap bowing of ~3 eV was found for SiCGaN, and a strong optical bandgap bowing of 0.9 eV was found for SiCAlN.

Novel Ultrahard Extended Hexagonal C10, C14 and C18 Allotropes with Mixed sp2/sp3 Hybridizations: Crystal Chemistry and Ab Initio Investigations

Based on 4H, 6H and 8H diamond polytypes, novel extended lattice allotropes C10, C14 and C18 characterized by mixed sp3/sp2 carbon hybridizations were devised based on crystal chemistry rationale and first-principles calculations of the ground state structures and energy derived properties: mechanical, dynamic (phonons), and electronic band structure. The novel allotropes were found increasingly cohesive along the series, with cohesive energy values approaching those of diamond polytypes. Regarding mechanical properties, C10, C14, and C18 were found ultrahard with Vickers hardness slightly below that of diamond. All of them are dynamically stable, with positive phonon frequencies reaching maxima higher than in diamond due to the stretching modes of C=C=C linear units. The electronic band structures expectedly reveal the insulating character of all three diamond polytypes and the conductive character of the hybrid allotropes. From the analysis of the bands crossing the Fermi level, a nesting Fermi surface was identified, allowing us to predict potential superconductive properties.

Structure optimization with stochastic density functional theory.

Linear-scaling techniques for Kohn-Sham density functional theory are essential to describe the ground state properties of extended systems. Still, these techniques often rely on the localization of the density matrix or accurate embedding approaches, limiting their applicability. In contrast, stochastic density functional theory (sDFT) achieves linear- and sub-linear scaling by statistically sampling the ground state density without relying on embedding or imposing localization. In return, ground state observables, such as the forces on the nuclei, fluctuate in sDFT, making optimizing the nuclear structure a highly non-trivial problem. In this work, we combine the most recent noise-reduction schemes for sDFT with stochastic optimization algorithms to perform structure optimization within sDFT. We compare the performance of the stochastic gradient descent approach and its variations (stochastic gradient descent with momentum) with stochastic optimization techniques that rely on the Hessian, such as the stochastic Broyden-Fletcher-Goldfarb-Shanno algorithm. We further provide a detailed assessment of the computational efficiency and its dependence on the optimization parameters of each method for determining the ground state structure of bulk silicon with varying supercell dimensions.

Cryo-EM analysis of V/A-ATPase intermediates reveals the transition of the ground-state structure to steady-state structures by sequential ATP binding

Vacuolar/archaeal-type ATPase (V/A-ATPase) is a rotary ATPase that shares a common rotary catalytic mechanism with FoF1 ATP synthase. Structural images of V/A-ATPase obtained by single-particle cryo-electron microscopy during ATP hydrolysis identified several intermediates, revealing the rotary mechanism under steady-state conditions. However, further characterization is needed to understand the transition from the ground state to the steady state. Here, we identified the cryo-electron microscopy structures of V/A-ATPase corresponding to short-lived initial intermediates during the activation of the ground state structure by time-resolving snapshot analysis. These intermediate structures provide insights into how the ground-state structure changes to the active, steady state through the sequential binding of ATP to its three catalytic sites. All the intermediate structures of V/A-ATPase adopt the same asymmetric structure, whereas the three catalytic dimers adopt different conformations. This is significantly different from the initial activation process of FoF1, where the overall structure of the F1 domain changes during the transition from a pseudo-symmetric to a canonical asymmetric structure (PNAS NEXUS, pgac116, 2022). In conclusion, our findings provide dynamical information that will enhance the future prospects for studying the initial activation processes of the enzymes, which have unknown intermediate structures in their functional pathway.

The influence of double lanthanide metal atoms on the stability of germanium-based clusters

The influence of double lanthanide metal atoms on the stability of germanium-based clusters was conducted by means of density functional theory calculations. The consistency and accuracy of structure optimization are tested with three exchange correlation functionals (PBE, BPW91 and B3LYP). Unlike the pentagonal bipyramid derivatives of LnGe7- and pure germanium, the ground state structures of Ln2Ge6- (Ln = La, Ce and Lu) clusters are preference to tetragonal bipyramid with two capped atoms. The enhancement effect on clusters stability is Ce/ La > Lu > Yb. Total density of states diagram represents the extremely inconspicuous spin polarization of Ln2Ge6- clusters. In fact, the value of the magnetic moment is also very small, which is 1 μB.

The largest fullerene.

Fullerenes are lowest energy structures for gas phase all-carbon particles for a range of sizes, but graphite remains the lowest energy allotrope of bulk carbon. This implies that the lowest energy structure changes nature from fullerenes to graphite or graphene at some size and therefore, in turn, implies a limit on the size of free fullerenes as ground state structures. We calculate this largest stable single shell fullerene to be of size N = 1 × 104, using the AIREBO effective potential. Above this size fullerene onions are more stable, with an energy per atom that approaches graphite structures. Onions and graphite have very similar ground state energies, raising the intriguing possibility that fullerene onions could be the lowest free energy states of large carbon particles in some temperature range.

Synthesis of and theoretical research on some azine derivatives and investigation of their antimicrobial activities

This study includes experimental, theoretical, and antimicrobial investigations on 1-(diphenylmethylene)-2-(4-methoxybenzylidene)hydrazine (5), 1-(3,5-dimethoxybenzylidene)-2-(diphenylmethylene)hydrazine (6) and 1- (diphenylmethylene)-2-(2,3,4-trimethoxybenzylidene)hydrazine (7). The structures of the compounds synthesized by microwave method were determined by spectroscopic methods and elemental analysis. Conformational analysis, ground state structure, fourier transform infrared spectra (FT-IR), and nuclear magnetic resonance (NMR) spectra of the compounds were computed using density functional theory (DFT) calculations in the theoretical research. Based on the B3LYP/6-31G(d,p) level, the conformers from the torsional barrier scanning were optimized. The B3LYP/6-311++G .(d,p) was used to determine the harmonic vibrational frequencies, potential energy distribution (PED), infrared intensities, and NMR chemical shifts of the most stable conformers. The experimental findings were compared with theoretically expected spectral data. The antibacterial activity of the prepared compounds was tested in vitro against nine bacteria and one yeast species. The antimicrobial activity of the compounds was tested by minimum inhibitory concentration (MIC) and agar well diffusion method. Compound 7 showed good activity against the bacteria and yeast, while 5 and 6 showed no antimicrobial activity. Compound 7 showed zone of inhibition values in the range of 10-15 mm against Klebsiella pneumonia, Pseudomonas aeruginosa and Salmonella typhimurium The results indicated that compound 7 was effective against bacteria.