How evolutionary crystal structure prediction works--and why

Interface Nucleus Complementarity: An Iterative Process for the Discovery of Modular Intermetallics Guided by Chemical Pressure

We present an iterative process for the discovery of modular intermetallic structures based on a recently developed interface nucleus approach. The process begins with the proposal of a suitable geometric motif that may serve as an interface nucleus. We then screen crystallographic databases for structures containing this motif as potential intergrowth partners. The extent to which pairs of these structures are likely to combine into more complicated assembles is then assessed with a new chemical pressure-based metric, interface nucleus complementarity (INC). Promising combinations of structures are translated into systems for synthesis, with new compounds providing either support for the importance of the original interface nucleus or new geometrical motifs for the next round of analysis. We demonstrate this process using a fragment derived from the σ-phase structure as a starting point, leading to the synthesis of PrMg4.13Zn10.20 and a new motif to seed the next cycle.

Is pentavalent Pr(V) feasible in solid CsPrF6?

The oxidation state (OS) holds significant importance in the field of chemistry and serves as a crucial parameter for tracking electrons. Lanthanide (Ln) elements predominately exhibit a +III oxidation state, with a few elements such as Ce, Pr, Nd, Tb, and Dy able to achieve a +IV oxidation state. Over the past century, numerous attempts to synthesize Pr(V) have been made without success until recent reports on Pr(V) oxides and nitride-oxide in the gas phase expanded our understanding of Ln elements. However, the formation of Pr(V) in the condensed phase remains an open question. In this work, based on advanced quantum chemical investigations, we predict that formation of the solid-state CsPrVF6 from Pr(III) and Pr(IV) complexes is exothermic, indicating that CsPrVF6 is stable. The crystal structure comprises [PrF6]- octahedral clusters occupying the interstitial spaces of Cs cations. Electronic structure analysis reveals that the CsPrF6 crystal has a closed-shell structure and that Pr reaches its highest oxidation state of +V. The results indicate that the existence of Pr(V) in solid-state Ln fluorides is not impossible, which enriches our understanding of high-valence Ln compounds.

Exploring the Polymorphism of Dicalcium Silicates Using Transfer Learning Enhanced Machine Learning Atomic Potentials

Belitic cements are a greener alternative to Ordinary Portland Cement due to the lower CO2 associated with their production. However, their low reactivity with water is currently a drawback, resulting in longer setting times. In this study, we utilize a combination of evolutionary algorithms and machine learning atomic potentials (MLPs) to identify previously unreported belite polymorphs that may exhibit higher hydraulic reactivity than the known phases. To address the high computational demand of this methodology, we propose a novel transfer learning approach for generating MLPs. First, the models are pretrained on a large set of classical data (ReaxFF) and then retrained with density functional theory (DFT) data. We demonstrate that the transfer learning enhanced potentials exhibit higher accuracy, require less training data, and are more transferable than those trained exclusively on DFT data. The generated machine learning potential enables a fast, exhaustive, and reliable exploration of the dicalcium silicate polymorphs. This includes studying their stability through phonon analysis and calculating their structural and elastic properties. Overall, we identify ten new belite polymorphs within the energy range of the existing ones, including a layered phase with potentially high reactivity.

Proton Conducting Neuromorphic Materials and Devices

Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.

Structure-Prediction-Oriented Synthesis of Thiophosphates as Promising Infrared Nonlinear Optical Materials

Oriented synthesis of functional materials is a focus of attention in material science. As one of the most important function materials, infrared nonlinear optical materials with large second harmonic generation effects and broad optical band gap are in urgent need. In this work, directed by the theoretical structure prediction, the first series of non-centrosymmetric (NCS) alkali-alkaline earth metal [PS4]-based thiophosphates LiCaPS4 (Ama2), NaCaPS4 (P21), KCaPS4 (Pna21), RbCaPS4 (Pna21), CsCaPS4 (Pna21) were successfully synthesized. Comprehensive characterizations reveal that ACaPS4 could be regarded as promising IR NLO materials, exhibiting wide band gap (3.77-3.86 eV), moderate birefringence (0.027-0.064 at 1064 nm), high laser-induced damage threshold (LIDT, ~10×AGS), and suitable phase-matching second harmonic generation responses (0.4-0.6×AGS). Structure-properties analyses illustrate that the Ca-S bonds show non-ignorable covalent feature, and [PS4] together with [CaSn] units play dominant roles to determine the band gap and SHG response. This work indicates that Li-, Na- and K- analogs may be promising infrared nonlinear optical material candidates, and this is the first successful case of "prediction to synthesis" involving infrared (IR) nonlinear optical (NLO) crystals in the thiophosphate system and may provide a new avenue to the design and oriented synthesis of high-performance function materials in the future.

Novel ground state structures of N-doped LuH3

Ab-initiocrystal structure searches have played a pivotal role in recent discoveries of high-Tc hydride superconductors under high pressure. Using evolutionary crystal searches, we predict novel ground state structures of N-doped LuH3at ambient conditions. We find an insulating ground state structure for LuN0.125H2.875(∼1.0 wt.% N), contrary to earlier studies where assumed structures were all metallic. This insulating behavior of ground state was found to persist up to ∼45 GPa. However our crystal structure searches revealed a metallic state for an H-deficient variant of LuN0.125H2.875. We study bonding characteristics of important structures by calculating electronic density of states, electronic-localization functions and Bader charges. Our Bader charge analysis shows that insulators have both H+and H-ions whereas metals have only H-ions. We find that H+ions are bonded to N atomsviaa very short covalent bond. Thus we identify a clear relationship between formation of N-H bonds and insulating behavior of materials. Besides this, we perform crystal structure searches for three more compositions with higher N-content (>1.0 wt.%). Analysis of electronic properties shows that the ground states of these compositions are insulator.

A database of high-pressure crystal structures from hydrogen to lanthanum

This paper introduces the HEX (High-pressure Elemental Xstals) database, a complete database of the ground-state crystal structures of the first 57 elements of the periodic table, from H to La, at 0, 100, 200 and 300 GPa. HEX aims to provide a unified reference for high-pressure research, by compiling all available experimental information on elements at high pressure, and complementing it with the results of accurate evolutionary crystal structure prediction runs based on Density Functional Theory. Besides offering a much-needed reference, our work also serves as a benchmark of the accuracy of current ab-initio methods for crystal structure prediction. We find that, in 98% of the cases in which experimental information is available, ab-initio crystal structure prediction yields structures which either coincide or are degenerate in enthalpy to within 300 K with experimental ones. The main manuscript contains synthetic tables and figures, while the Crystallographic Information File (cif) for all structures can be downloaded from the related figshare online repository.

Beyond metals: theoretical discovery of semiconducting MAX phases and their potential application in thermoelectrics

MAX phase is a family of ceramic compounds, typically known for their metallic properties. However, we show here that some of them may be narrow bandgap semiconductors. Using a series of first-principles calculations, we have investigated the electronic structures of 861 dynamically stable MAX phases. Notably, Sc2SC, Y2SC, Y2SeC, Sc3AuC2, and Y3AuC2 have been identified as semiconductors with band gaps ranging from 0.2 to 0.5 eV. Furthermore, we have assessed the thermodynamic stability of these systems by generating ternary phase diagrams utilizing evolutionary algorithm techniques. Their dynamic stabilities are confirmed by phonon calculations. Additionally, we have explored the potential thermoelectric efficiencies of these materials by combining Boltzmann transport theory with first-principles calculations. The relaxation times are estimated using scattering theory. The zT coefficients for the aforementioned systems fall within the range of 0.5 to 2.5 at temperatures spanning from 300 to 700 K, indicating their suitability for high-temperature thermoelectric applications.

Chemical Bonding and Crystal Structure Schemes in Atomic/Molecular Layer Deposited Fe-Terephthalate Thin Films

Advanced deposition routes are vital for the growth of functional metal-organic thin films. The gas-phase atomic/molecular layer deposition (ALD/MLD) technique provides solvent-free and uniform nanoscale thin films with unprecedented thickness control and allows straightforward device integration. Most excitingly, the ALD/MLD technique can enable the in situ growth of novel crystalline metal-organic materials. An exquisite example is iron-terephthalate (Fe-BDC), which is one of the most appealing metal-organic framework (MOF) type materials and thus widely studied in bulk form owing to its attractive potential in photocatalysis, biomedicine, and beyond. Resolving the chemistry and structural features of new thin film materials requires an extended selection of characterization and modeling techniques. Here we demonstrate how the unique features of the ALD/MLD grown in situ crystalline Fe-BDC thin films, different from the bulk Fe-BDC MOFs, can be resolved through techniques such as synchrotron grazing-incidence X-ray diffraction (GIXRD), Mössbauer spectroscopy, and resonant inelastic X-ray scattering (RIXS) and crystal structure predictions. The investigations of the Fe-BDC thin films, containing both trivalent and divalent iron, converge toward a novel crystalline Fe(III)-BDC monoclinic phase with space group C2/c and an amorphous Fe(II)-BDC phase. Finally, we demonstrate the excellent thermal stability of our Fe-BDC thin films.

Pressure Induces Six-fold Coordination for the Lighter Pnictides Phosphorus and Arsenic Triiodide

In this study, we employ an evolutionary algorithm in conjunction with first-principles density functional theory (DFT) calculations to comprehensively investigate the structural transitions, electronic properties, and chemical bonding behaviors of XI3 compounds, where X denotes phosphorus (P) and arsenic (As), across a range of elevated pressures. Our computational analyses reveal a distinctive phenomenon occurring under compression, wherein the initially trigonal structures of PI3 (P 63) and AsI3 (R-3) undergo an intriguing transformation, leading to the emergence of six-coordinated monoclinic phases (C2/m) at 6 GPa and 2 GPa for PI3 and AsI3, respectively. These high-pressure phases exhibit their stability up to 10 GPa for PI3 and 12 GPa for AsI3. Notably, the resulting structures at elevated pressures bear striking resemblance to the widely recognized six-coordinated octahedral BiI3 crystal configuration observed at ambient conditions. Our investigation further underscores the pivotal role of pressure-induced reactivity of the lone-pair electrons in PI3 and AsI3, facilitating their enhanced stereochemical reactivity and thereby enabling higher six-fold coordination. Complementary analyses employing electron localization function (ELF) and density of states (DOS) effectively delineate the progression towards augmented coordination in PI3 and AsI3 with increasing pressure. While the phenomenon of heightened coordination is conventionally associated with heavier pnictide iodides such as SbI3 and BiI3 under ambient conditions due to heightened ionic character and relativistic effects in bismuth (Bi) and antimony (Sb), our findings accentuate that analogous structural transformations can also be induced in lighter elements like phosphorus (P) and arsenic (As) under the influence of pressure.

Experiment-Driven Atomistic Materials Modeling: A Case Study Combining X-Ray Photoelectron Spectroscopy and Machine Learning Potentials to Infer the Structure of Oxygen-Rich Amorphous Carbon

An important yet challenging aspect of atomistic materials modeling is reconciling experimental and computational results. Conventional approaches involve generating numerous configurations through molecular dynamics or Monte Carlo structure optimization and selecting the one with the closest match to experiment. However, this inefficient process is not guaranteed to succeed. We introduce a general method to combine atomistic machine learning (ML) with experimental observables that produces atomistic structures compatible with experiment by design. We use this approach in combination with grand-canonical Monte Carlo within a modified Hamiltonian formalism, to generate configurations that agree with experimental data and are chemically sound (low in energy). We apply our approach to understand the atomistic structure of oxygenated amorphous carbon (a-COx), an intriguing carbon-based material, to answer the question of how much oxygen can be added to carbon before it fully decomposes into CO and CO2. Utilizing an ML-based X-ray photoelectron spectroscopy (XPS) model trained from GW and density functional theory (DFT) data, in conjunction with an ML interatomic potential, we identify a-COx structures compliant with experimental XPS predictions that are also energetically favorable with respect to DFT. Employing a network analysis, we accurately deconvolve the XPS spectrum into motif contributions, both revealing the inaccuracies inherent to experimental XPS interpretation and granting us atomistic insight into the structure of a-COx. This method generalizes to multiple experimental observables and allows for the elucidation of the atomistic structure of materials directly from experimental data, thereby enabling experiment-driven materials modeling with a degree of realism previously out of reach.

Pb2[C2O6]-P3̄m1: new insights into the high-pressure behavior of carbonates

In the present study, based on density functional theory and crystal structure prediction approaches, we found a new high-pressure structure of lead carbonate, named Pb2[C2O6]-P3̄m1. This structure differs significantly from previously known modifications of lead carbonate. The Pb2[C2O6]-P3̄m1 structure is characterized by the presence of ethane-like [C2O6] groups, which can also be classified as orthooxalate groups. This structure is most energetically favorable at pressures above 92 GPa at low temperatures, while Pmmn (post-aragonite structure) is most favorable below this pressure. As temperature increases to 2000 K, the pressure required for the Pmmn → P3̄m1 phase transition increases to 100 GPa. The high-pressure modification Pb2[C2O6]-P3̄m1 retains its stability at least up to 200 GPa. In addition, the Raman spectrum of the newly discovered modification was calculated, which may be useful for subsequent identification of this phase in high-pressure experiments. At 100 GPa, the most intense band located at 1148 cm-1 corresponds to the symmetric stretching mode of the C-C bond in the [C2O6] orthooxalate groups. The second and third most intense modes appear at 1021 and 726 cm-1, correspondingly.

Predicted High-Energy Density MN8 Containing Anionic 18-Crown-6 Ring-Based Polynitrogen Monolayers Acting as Cryptand

In this study, we investigate the potential of the 18-crown-6-like two-dimensional (2D)-N8 structure to accommodate electrons from metals without compromising its covalent nitrogen network. Employing the crystal structure prediction enhanced by evolutionary algorithm and density functional theory methodology, we successfully predicted the existence of 16 layered M@2D-N8 complexes from a total of 39 MN8 systems investigated at 100 GPa (M = s-block Na-Cs, Be-Ba and d-block Ag, Au, Cd, Hg, Hf, W, and Y). Among those, there are 13 quenchable M@2D-N8 compounds that are dynamically stable at 1 atm. Orbital interactions and bonding analysis show that 2D-N8 presents a flat localized π* band that can accommodate one or two electrons without breaking the 2D covalent nitrogen network. Depending on the metal-to-polynitrogen charge transfer (formally, 1-4 electrons), these N-rich phases are semiconducting or metallic under ambient conditions. Ab initio molecular dynamics simulations show that K(I)@2D-N8 and Ca(II)@2D-N8 are thermally stable up to 600 K, while the Hf(IV)@2D-N8 compound is thermally not viable at 400 K because of the weakening of the N═N bonds due to a strong four-electron reduction. These metal 18-crown-6 ring-based polynitrogen compounds, as expected due to their high nitrogen content (eight nitrogen atoms per metal), could potentially serve as new high-energy density materials.

First-principles study of multifunctional Mn2B3 materials with high hardness and ferromagnetism

Transition metal boride TM2B3 is widely studied in the field of physics and materials science. However, Mn2B3 has not been found in Mn-B systems so far. Mn2B3 undergoes phase transitions from Cmcm (0-28 GPa) to C2/m (28-80 GPa) and finally to C2/c (80-200 GPa) under pressure. Among these stable phases, Cmcm- and C2/m-Mn2B3s comprise six-membered boron rings and C2/c-Mn2B3 has wavy boron chains. They all have good mechanical properties and can become potential multifunctional materials. The strong B-B covalent bonding is mainly responsible for the structural stability and hardness. Comparison of the hardness of the five TM2B3s with different bonding strengths of TM-B and B-B bonds reveals a nonlinear change in the hardness. According to the Stoner model, these structures possess ferromagnetism, and the corresponding magnetic moments are almost the same as those of GGA and GGA + U (U = 3.9 eV, J = 1 eV).

Toward Predicting the Assembly of Modular Intermetallics from Chemical Pressure Analysis: The Interface Nucleus Approach

Complex intermetallic phases are often constructed from domains derived from simpler structures arranged into hierarchical assemblies. These modular arrangements offer intriguing prospects, such as the integration of the properties of distinct compounds into a single material or for the emergence of new properties from the interactions among different domains. In this article, we develop a strategy for the design of such complex structures, which we term the interface nucleus approach. Within this framework, the assembly of complex structures is facilitated by interface nuclei: geometrical motifs shared by two parent structures that serve as a region of overlap to nucleate or seed the formation of a combined structure. Our central hypothesis is that the formation of an interface between structures at these motifs creates opportunities for the relief of atomic packing stresses, as revealed by Density Functional Theory-Chemical Pressure (DFT-CP) analysis: when corresponding interatomic contacts in two structures exhibit complementarity─negative CP with positive CP or intense CP with mild CP─the intergrowth allows for a more balanced packing arrangement. To illustrate the application of the interface nucleus concept, we analyze three modular intermetallic structures, the σ-phase (FeCr), PuNi3, and Ca6Cu6Al5 types. In each case, the assembly of the structure can be connected to complementary CP features in an interface nucleus shared by its parent structures, while the distribution of the interface nuclei in the parents serves to template the geometry of the overall framework. In this way, the interface nucleus approach points toward avenues for the design of modular intermetallics from the CP schemes of potential partner structures.

Pressure Induced Alteration and Stabilization of Intermolecular Stacking in Square-planar Osmium tetracarbonyl

Osmium carbonyls are well known to form stable 18-electron complexes like Os(CO)5 , Os2 (CO)9 and Os3 (CO)12 having both bridging and terminal carbonyls. For osmium tetra-carbonyl, Os(CO)4 solid-state packing significantly alters the ground-state structure. The gas-phase stable see-saw geometry converts to a square-planar structure in solid state. Highly efficient intermolecular stacking between Os(CO)4 units assists this transformation. Each Os(CO)4 molecule is stacked in a staggered orientation with respect to each other. Pressure induces a [Xe]4f14 5d6 6s2 (S=2)→[Xe]4f14 5d8 (S=0) electronic transition in osmium stabilize a square planar osmium tetra-carbonyl. Under the influence of isotropic pressure, the molecules not only come closer to each other but their relative orientations also get significantly altered. Calculations show that at P=1 GPa and above, the eclipsed orientation for the intermolecular stacking gets preferred over the staggered form. The staggered→eclipsed intermolecular stacking orientation under pressure is shown to be controlled by London dispersion interactions.

Top-down design of high-performance V-based MBene anode for Li/Na-ion batteries

Two-dimensional (2D) MBenes have enormous potential in energy applications. Vanadium metal, with its versatile and tunable electronic states, can further enhance the electrochemical performance of MBenes. However, most MBenes are composed of a few atomic layers as the metal boron (MB) block, e.g., M2B2, which might lead to instability and poor mechanical response. Herein, we designed and predicted 2D V4B6 associated with different terminations (T = Cl, O, S) using a top-down method and global search for parental V4AB6. Among the A element candidates, the P-glued MAB phase exhibited high stability and easy synthesizability. Moreover, 2D V4B6 was feasibly formed and easily exfoliated owing to its weak V-P bonding. Most of the surface functionalization could improve both the mechanical and electrochemical properties of the V4B6 monolayer. In particular, 2D V4B6S2 exhibited a high potential as an anode material for lithium-ion batteries (LIBs) with high theoretical capacity (297 mA h g-1), low diffusion barrier (0.166 eV), and low open circuit voltage (0.136 V), outperforming a majority of MXenes and transition metal sulfide layers. This work offers a new strategy for designing desirable 2D layers from parental materials, and tuning their properties via composition and surface functionalization, which could shed light on the development of other 2D metal-ion anodes.

Superconductivity of cubic MB6 (M = Na, K, Rb, Cs)

Previous studies have shown that NaB6, KB6, and RbB6 adopting Pm3̄m are superconductors with a relatively high Tc under ambient conditions. In this paper, we conducted systematic structural and related properties research on CsB6 through a genetic evolution algorithm and total energy calculations based on density functional theory between 0 and 20 GPa. Our results reveal a cubic Pm3̄m CsB6, which is dynamically stable under the pressures we studied. We systematically calculated the formation enthalpies, electronic properties, and superconducting properties of Pm3̄m MB6 (M = Na, K, Rb, Cs). They all exhibit metallic features, and boron has high contributions to band structures, density of states, and electron-phonon coupling (EPC). The calculated results about the Helmholtz free energy difference of Pm3̄m CsB6 at 0, 10, and 20 GPa indicate that it is stable upon chemical decomposition (decomposition to simple substances Cs and B) from 0 to 400 K. The phonon density of states indicates that boron atoms occupy the high frequency area. The EPC results show that Pm3̄m CsB6 is a superconductor with Tc = 11.7 K at 0 GPa, close to NaB6 (13.1 K), KB6 (11.7 K), and RbB6 (11.3 K) at 0 GPa in our work, which indicates that boron atoms play an essential role in superconductivity: vibrations of B6 regular octagons lead to the high Tc of Pm3̄m MB6. Our work about Pm3̄m hexaborides provides a supplementary study on the borides of the group IA elements (without Fr and Li) and has an important guiding significance for the experimental synthesis of CsB6.

Ultrahigh Oxygen Ion Mobility in Ferroelectric Hafnia

Ferroelectrics and ionic conductors are important functional materials, each supporting a plethora of applications in information and energy technology. The underlying physics governing their functional properties is ionic motion, and yet studies of ferroelectrics and ionic conductors are often considered separate fields. Based on first-principles calculations and deep-learning-assisted large-scale molecular dynamics simulations, we report ferroelectric-switching-promoted oxygen ion transport in HfO_{2}, a wide-band-gap insulator with both ferroelectricity and ionic conductivity. Applying a unidirectional bias can activate multiple switching pathways in ferroelectric HfO_{2}, leading to polar-antipolar phase cycling that appears to contradict classical electrodynamics. This apparent conflict is resolved by the geometric-quantum-phase nature of electric polarization that carries no definite direction. Our molecular dynamics simulations demonstrate bias-driven successive ferroelectric transitions facilitate ultrahigh oxygen ion mobility at moderate temperatures, highlighting the potential of combining ferroelectricity and ionic conductivity for the development of advanced materials and technologies.

Prediction of novel ground-state structures and analysis of phonon transport in two-dimensional GexSy compounds

We conducted this study to explore the ground-state structures of two-dimensional (2D) variable-composition GexSy compounds, driven by the polymorphic characteristics of bulk germanium sulfides and the promising thermoelectric performance of 2D GeS (Pmn21). To accomplish this, we utilized the highly successful evolutionary-algorithm-based code USPEX in conjunction with VASP for total energy calculations, leading to the discovery of three previously unexplored structures of Ge2S (P2/c), GeS (P3̄m1), and GeS2 (P21/c). These 2D materials exhibit significantly lower formation energies compared to their reported counterparts. We thoroughly scrutinized the structural stability and subsequently analyzed their electronic structures. Our analysis reveals a nearly direct band gap of 0.12/0.84 eV with the PBE/HSE06 functional for 2D Ge2S and an indirect band gap for 2D GeS and GeS2. Their semiconducting nature highlights the crucial importance of lattice thermal conductivity (κl), which we determined by solving the Boltzmann transport equation for phonons. Importantly, we predict a room temperature κl value of 6.82 W m-1 K-1 for GeS, lower than its 2D orthorhombic counterpart. In the case of GeS2, we observed an anisotropic κl value of 16.95/10.68 W m-1 K-1 along the zigzag/armchair directions at 300 K, with an in-plane anisotropy ratio of 1.59, surpassing that of 2D IV-VI compounds. We delve into detailed discussions regarding the role of lattice anharmonicity, group velocities, phonon lifetimes, and three-phonon weighted phase space in the overall thermal conductivity analysis.

Crystal structures and P-T phase diagrams of SrC 2 O 5 and BaC 2 O 5

In this study, we present the results of a search for new stable structures of SrC2 O5 and BaC2 O5 in the pressure range of 0-100 GPa based on the density functional theory and crystal structure prediction approaches. We have shown that the recently synthesized pyrocarbonate structure SrC2 O5 - P 2 1 / c is thermodynamically stable for both SrC2 O5 and BaC2 O5 . Thus, SrC2 O5 - P 2 1 / c is stable relative to decomposition reaction above 10 GPa, while the lower-pressure stability limit for BaC2 O5 - P 2 1 / c is 5 GPa, which is the lowest value for the formation of pyrocarbonates. For SrC2 O5 , the following polymorphic transitions were found with increasing pressure: P 2 1 / c → F d d 2 at 40 GPa and 1000 K, F d d 2 → C 2 at 90 GPa and 1000 K. SrC2 O5 - F d d 2 and SrC2 O5 - C 2 are characterized by the framework and layered structures of [CO4 ]4 - tetrahedra, respectively. For BaC2 O5 , with increasing pressure, decomposition of BaC2 O5 - P 2 1 / c into BaCO3 and CO2 is observed at 34 GPa without any polymorphic transitions.

Multi-step nucleation pathway of C-S-H during cement hydration from atomistic simulations

The Calcium Silicate Hydrate (C-S-H) nucleation is a crucial step during cement hydration and determines to a great extent the rheology, microstructure, and properties of the cement paste. Recent evidence indicates that the C-S-H nucleation involves at least two steps, yet the underlying atomic scale mechanism, the nature of the primary particles and their stability, or how they merge/aggregate to form larger structures is unknown. In this work, we use atomistic simulation methods, specifically DFT, evolutionary algorithms (EA), and Molecular Dynamics (MD), to investigate the structure and formation of C-S-H primary particles (PPs) from the ions in solution, and then discuss a possible formation pathway for the C-S-H nucleation. Our simulations indicate that even for small sizes the most stable clusters encode C-S-H structural motifs, and we identified a C4S4H2 cluster candidate to be the C-S-H basic building block. We suggest a formation path in which small clusters formed by silicate dimers merge into large elongated aggregates. Upon dehydration, the C-S-H basic building blocks can be formed within the aggregates, and eventually crystallize.

Pressure-induced novel ZrN4 semiconductor materials with high dielectric constants: a first-principles study

In addition to Zr3N4 and ZrN2 compounds, zirconium nitrides with a rich family of phases always exhibit metal phases. By employing an evolutionary algorithm approach and first-principles calculations, we predicted seven novel semiconductor phases for the ZrN4 system at 0-150 GPa. Through calculating phonon dispersions, we identified four dynamically stable semiconductor structures under ambient pressure, namely, α-P1̄, β-P1̄, γ-P1̄, and β-P1 (with bandgaps of 1.03 eV, 1.10 eV, 2.33 eV, and 1.49 eV calculated using the HSE06 hybrid density functional, respectively). The calculated work functions and dielectric functions show that the four dynamically stable semiconductor structures are all high dielectric constant (high-k) materials, among which the β-P1̄ phase has the largest static dielectric constant (3.9 times that of SiO2). Furthermore, we explored band structures using the HSE06 functional and density of states (DOS) and the response of bandgaps to pressure using the PBE functional for the four new semiconductor configurations. The results show that the bandgap responses of the four structures exhibit significant differences when hydrostatic pressure is applied from 0 to 150 GPa.

Low-Temperature Predicted Structures of Ag2S (Silver Sulfide)

Silver sulfide phases, such as body-centered cubic argentite and monoclinic acanthite, are widely known. Traditionally, acanthite is regarded as the only low-temperature phase of silver sulfide. However, the possible existence of other low-temperature phases of silver sulfide cannot be ruled out. Until now, there have been only a few suggestions about low-temperature Ag2S phases that differ from monoclinic acanthite. The lack of a uniform approach has hampered the prediction of such phases. In this work, the use of such an effective tool as an evolutionary algorithm for the first time made it possible to perform a broad search for the model Ag2S phases of silver sulfide, which are low-temperature with respect to cubic argentite. The possibility of forming Ag2S phases with cubic, tetragonal, orthorhombic, trigonal, monoclinic, and triclinic symmetry is considered. The calculation of the cohesion energy and the formation enthalpy show, for the first time, that the formation of low-symmetry Ag2S phases is energetically most favorable. The elastic stiffness constants cij of all predicted Ag2S phases are computed, and their mechanical stability is determined. The densities of the electronic states of the predicted Ag2S phases are calculated. The prediction of low-temperature Ag2S structures indicates the possibility of synthesizing new silver sulfide phases with improved properties.

Prediction and Rationalization of Abundant C-N-H Molecules in Different Environments

The extreme chemical diversity of CmNnHk molecules is at the same time very important (central in organic chemistry) and difficult to rationalize in the sense that some molecules are abundant and easy to synthesize, while others are rare and difficult to make. Using the recently developed criteria of molecular "magicity", combined with evolutionary structure prediction and quantum-chemical calculations, we study these molecules in a wide range of compositions (0 ≤ m ≤ 13, 0 ≤ n ≤ 4, and 0 ≤ k ≤ 14). "Magic" molecules are defined as those that are lower in energy than any isochemical mixture of molecules with the nearest compositions. The predicted "magic" molecules are in good agreement with compounds found in versatile environments (interstellar and circumstellar media, Titan's lower atmosphere, and crude oil fractions) and in experimental chemistry. This work shows the predictive power of our approach, capable of predicting and explaining stable molecules in complex systems.

Hypervalent hydridosilicate in the Na-Si-H system

Hydrogenation reactions at gigapascal pressures can yield hydrogen-rich materials with properties relating to superconductivity, ion conductivity, and hydrogen storage. Here, we investigated the ternary Na-Si-H system by computational structure prediction and in situ synchrotron diffraction studies of reaction mixtures NaH-Si-H2 at 5-10 GPa. Structure prediction indicated the existence of various hypervalent hydridosilicate phases with compositions NamSiH(4+m) (m = 1-3) at comparatively low pressures, 0-20 GPa. These ternary Na-Si-H phases share, as a common structural feature, octahedral SiH6 2- complexes which are condensed into chains for m = 1 and occur as isolated species for m = 2, 3. In situ studies demonstrated the formation of the double salt Na3[SiH6]H (Na3SiH7, m = 3) containing both octahedral SiH6 2- moieties and hydridic H-. Upon formation at elevated temperatures (>500°C), Na3SiH7 attains a tetragonal structure (P4/mbm, Z = 2) which, during cooling, transforms to an orthorhombic polymorph (Pbam, Z = 4). Upon decompression, Pbam-Na3SiH7 was retained to approx. 4.5 GPa, below which a further transition into a yet unknown polymorph occurred. Na3SiH7 is a new representative of yet elusive hydridosilicate compounds. Its double salt nature and polymorphism are strongly reminiscent of fluorosilicates and germanates.

Complex Oxides for Brain-Inspired Computing: A Review

The fields of brain-inspired computing, robotics, and, more broadly, artificial intelligence (AI) seek to implement knowledge gleaned from the natural world into human-designed electronics and machines. In this review, the opportunities presented by complex oxides, a class of electronic ceramic materials whose properties can be elegantly tuned by doping, electron interactions, and a variety of external stimuli near room temperature, are discussed. The review begins with a discussion of natural intelligence at the elementary level in the nervous system, followed by collective intelligence and learning at the animal colony level mediated by social interactions. An important aspect highlighted is the vast spatial and temporal scales involved in learning and memory. The focus then turns to collective phenomena, such as metal-to-insulator transitions (MITs), ferroelectricity, and related examples, to highlight recent demonstrations of artificial neurons, synapses, and circuits and their learning. First-principles theoretical treatments of the electronic structure, and in situ synchrotron spectroscopy of operating devices are then discussed. The implementation of the experimental characteristics into neural networks and algorithm design is then revewed. Finally, outstanding materials challenges that require a microscopic understanding of the physical mechanisms, which will be essential for advancing the frontiers of neuromorphic computing, are highlighted.

Structural stability, dihydrogen bonding, and pressure-induced polymorphic transformations in hydrazine borane

Hydrazine borane (N2H4BH3) has attracted considerable interest as a promising solid-state hydrogen storage material owing to its high hydrogen content and easy preparation. In this work, pressure-induced phase transitions of N2H4BH3 were investigated using a combination of vibrational spectroscopy, X-ray diffraction, and density functional theory (DFT) up to 30 GPa. Our results showed that N2H4BH3 exhibits remarkable structural stability in a very broad pressure region up to 15 GPa, and then two phase transitions were identified: the first one is from the ambient-pressure Pbcn phase to a Pbca phase near 15 GPa; the second is from the Pbca phase to a Pccn phase near 25 GPa. As revealed by DFT calculations, the unusual stability of N2H4BH3 and the late phase transformations were attributed to the pressure-mediated evolutions of dihydrogen bonding frameworks, the compressibility and the enthalpies of the high-pressure polymorphs. Our findings provide new insight into the structures and bonding properties of N2H4BH3 that are important for hydrogen storage applications.

Machine learning search for stable binary Sn alloys with Na, Ca, Cu, Pd, and Ag

We present our findings of a large-scale screening for new synthesizable materials in five M-Sn binaries, M = Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by the known richness of M-Sn properties with potential applications in energy storage, electronics packaging, and superconductivity. For the systematic exploration of the large configuration space, we relied on our recently developed MAISE-NET framework that constructs accurate neural network interatomic potentials and utilizes them to accelerate ab initio global structure searches. The scan of over two million candidate phases at a fraction of the typical ab initio calculation cost has uncovered 29 possible intermetallics thermodynamically stable at different temperatures and pressures (1 bar and 20 GPa). Notable predictions of ambient-pressure materials include a simple hP6-NaSn2 phase, fcc-based Pd-rich alloys, tI36-PdSn2 with a new prototype, and several high-temperature Sn-rich ground states in the Na-Sn, Cu-Sn, and Ag-Sn systems. Our modeling work also involved ab initio (re)examination of previously observed M-Sn compounds that helped explain the entropy-driven stabilization of known Cu-Sn phases. The study demonstrates the benefits of guiding structure searches with machine learning potentials and significantly expands the number of predicted thermodynamically stable crystalline intermetallics achieved with this strategy so far.

One dimensional ferroelectric nanothreads with axial and radial polarization

Long-range ferroelectric crystalline order usually fades away as the spatial dimension decreases, and hence there are few two-dimensional (2D) ferroelectrics and far fewer one-dimensional (1D) ferroelectrics. Due to the depolarization field, low-dimensional ferroelectrics rarely possess the polarization along the direction of reduced dimensionality. Here, using first-principles density functional theory, we explore the structural evolution of nanoribbons of varying widths constructed by cutting a 2D sheet of ferroelectric α-III2VI3 (III = Al, Ga, In; VI = S, Se, Te). We discover a one-dimensional ferroelectric nanothread (1DFENT) of ultrasmall diameter with both axial and radial polarization, potentially enabling ultra-dense data storage with a 1D domain of just three unit cells being the functional unit. The polarization in 1DFENT of Ga2Se3 exhibits an unusual piezoelectric response: a stretching stress along the axial direction will increase both the axial and radial polarization, referred to as the auxetic piezoelectric effect. Utilizing the intrinsically flat electronic bands, we demonstrate the coexistence of ferroelectricity and ferromagnetism in 1DFENT and a counterintuitive charge-doping-induced metal-to-insulator transition. The 1DFENT with both axial and radial polarization offers a counterexample to the Mermin-Wagner theorem in 1D and suggests a new platform for the design of ultrahigh-density memory and the exploration of exotic states of matter.

Prediction of Stable Surfaces of Metal Oxides through the Unsaturated Coordination Index

This study proposes the unsaturated coordination index, σ, as a potential descriptor of the stability of metal-oxide surfaces cleaved from bulk. The value of σ, the number of missing bonds per unit area, can be obtained very quickly using only crystallographic data, namely, the bulk geometry. The surface energies of various binary oxides, with and without atom relaxation, were calculated. Their correlations with σ had good coefficients of determination (R2) values, particularly in high-symmetry crystals. The proposed descriptor is very useful for an initial evaluation of stable metal-oxide surfaces without conducting any surface model calculations.

Evolutionary Algorithm-Based Crystal Structure Prediction of CuxZnyOz Ternary Oxides

Binary zinc(II) oxide (ZnO) and copper(II) oxide (CuO) are used in a number of applications, including optoelectronic and semiconductor applications. However, no crystal structures have been reported for ternary Cu-Zn-O oxides. In that context, we investigated the structural characteristics and thermodynamics of CuxZnyOz ternary oxides to map their experimental feasibility. We combined evolutionary crystal structure prediction and quantum chemical methods to investigate potential CuxZnyOz ternary oxides. The USPEX algorithm and density functional theory were used to screen over 4000 crystal structures with different stoichiometries. When comparing compositions with non-magnetic CuI ions, magnetic CuII ions, and mixed CuI-CuII compositions, the magnetic Cu2Zn2O4 system is thermodynamically the most favorable. At ambient pressures, the thermodynamically most favorable ternary crystal structure is still 2.8 kJ/mol per atom higher in Gibbs free energy compared to experimentally known binary phases. The results suggest that thermodynamics of the hypothetical CuxZnyOz ternary oxides should also be evaluated at high pressures. The predicted ternary materials are indirect band gap semiconductors.

A stable and strongly ferromagnetic Fe17O10- cluster with an accordion-like structure

Isolated clusters are ideal systems for tailoring molecule-based magnets and investigating the evolution of magnetic order from microscopic to macroscopic regime. We have prepared pure Fe_n^- (n = 7-31) clusters and observed their gas-collisional reactions with oxygen in a flow tube reactor. Interestingly, only the larger Fe_n^- (n ≥ 15) clusters support the observation of O₂-intake, while the smaller clusters Fe_n^- (n = 7-14) are nearly nonreactive. What is more interesting is that Fe₁₇O₁₀^- shows up with prominent abundance in the mass spectra indicative of its distinct inertness. In combination with DFT calculations, we unveil the stability of Fe₁₇O₁₀^- within an interesting acordion-like structure and elucidate the spin accommodation in such a strongly ferromagnetic iron cluster oxide.

MAGUS: machine learning and graph theory assisted universal structure searcher

Crystal structure predictions based on first-principles calculations have gained great success in materials science and solid state physics. However, the remaining challenges still limit their applications in systems with a large number of atoms, especially the complexity of conformational space and the cost of local optimizations for big systems. Here, we introduce a crystal structure prediction method, MAGUS, based on the evolutionary algorithm, which addresses the above challenges with machine learning and graph theory. Techniques used in the program are summarized in detail and benchmark tests are provided. With intensive tests, we demonstrate that on-the-fly machine-learning potentials can be used to significantly reduce the number of expensive first-principles calculations, and the crystal decomposition based on graph theory can efficiently decrease the required configurations in order to find the target structures. We also summarized the representative applications of this method on several research topics, including unexpected compounds in the interior of planets and their exotic states at high pressure and high temperature (superionic, plastic, partially diffusive state, etc.); new functional materials (superhard, high-energy-density, superconducting, photoelectric materials), etc. These successful applications demonstrated that MAGUS code can help to accelerate the discovery of interesting materials and phenomena, as well as the significant value of crystal structure predictions in general.

Formation and Polymorphism of Semiconducting K2SiH6 and Strategy for Metallization

K2SiH6, crystallizing in the cubic K2PtCl6 structure type (Fm3̅m), features unusual hypervalent SiH62- complexes. Here, the formation of K2SiH6 at high pressures is revisited by in situ synchrotron diffraction experiments, considering KSiH3 as a precursor. At the investigated pressures, 8 and 13 GPa, K2SiH6 adopts the trigonal (NH4)2SiF6 structure type (P3̅m1) upon formation. The trigonal polymorph is stable up to 725 °C at 13 GPa. At room temperature, the transition into an ambient pressure recoverable cubic form occurs below 6.7 GPa. Theory suggests the existence of an additional, hexagonal, variant in the pressure interval 3-5 GPa. According to density functional theory band structure calculations, K2SiH6 is a semiconductor with a band gap around 2 eV. Nonbonding H-dominated states are situated below and Si-H anti-bonding states are located above the Fermi level. Enthalpically feasible and dynamically stable metallic variants of K2SiH6 may be obtained when substituting Si partially by Al or P, thus inducing p- and n-type metallicity, respectively. Yet, electron-phonon coupling appears weak, and calculated superconducting transition temperatures are <1 K.

A database of low-energy atomically precise nanoclusters

The chemical and structural properties of atomically precise nanoclusters are of great interest in numerous applications, but the structures of the clusters can be computationally expensive to predict. In this work, we present the largest database of cluster structures and properties determined using ab-initio methods to date. We report the methodologies used to discover low-energy clusters as well as the energies, relaxed structures, and physical properties (such as relative stability, HOMO-LUMO gap among others) for 63,015 clusters across 55 elements. We have identified clusters for 593 out of 1595 cluster systems (element-size pairs) explored by literature that have energies lower than those reported in literature by at least 1 meV/atom. We have also identified clusters for 1320 systems for which we were unable to find previous low-energy structures in the literature. Patterns in the data reveal insights into the chemical and structural relationships among the elements at the nanoscale. We describe how the database can be accessed for future studies and the development of nanocluster-based technologies.

Computational Approaches for Organic Semiconductors: From Chemical and Physical Understanding to Predicting New Materials

While a complete understanding of organic semiconductor (OSC) design principles remains elusive, computational methods─ranging from techniques based in classical and quantum mechanics to more recent data-enabled models─can complement experimental observations and provide deep physicochemical insights into OSC structure-processing-property relationships, offering new capabilities for in silico OSC discovery and design. In this Review, we trace the evolution of these computational methods and their application to OSCs, beginning with early quantum-chemical methods to investigate resonance in benzene and building to recent machine-learning (ML) techniques and their application to ever more sophisticated OSC scientific and engineering challenges. Along the way, we highlight the limitations of the methods and how sophisticated physical and mathematical frameworks have been created to overcome those limitations. We illustrate applications of these methods to a range of specific challenges in OSCs derived from π-conjugated polymers and molecules, including predicting charge-carrier transport, modeling chain conformations and bulk morphology, estimating thermomechanical properties, and describing phonons and thermal transport, to name a few. Through these examples, we demonstrate how advances in computational methods accelerate the deployment of OSCsin wide-ranging technologies, such as organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), organic thermoelectrics, organic batteries, and organic (bio)sensors. We conclude by providing an outlook for the future development of computational techniques to discover and assess the properties of high-performing OSCs with greater accuracy.

Depolarization induced III-V triatomic layers with tristable polarization states

The integration of ferroelectrics that exhibit high dielectric, piezoelectric, and thermal compatibility with the mainstream semiconductor industry will enable novel device types for widespread applications, and yet there are few silicon-compatible ferroelectrics suitable for device downscaling. We demonstrate with first-principles calculations that the enhanced depolarization field at the nanoscale can be utilized to soften unswitchable wurtzite III-V semiconductors, resulting in ultrathin two-dimensional (2D) sheets possessing reversible polarization states. A 2D sheet of AlSb consisting of three atomic planes is identified to host both ferroelectricity and antiferroelectricity, and the tristate switching is accompanied by a metal-semiconductor transition. The thermodynamic stability and potential synthesizability of the triatomic layer are corroborated with phonon spectrum calculations, ab initio molecular dynamics simulations, and variable-composition evolutionary structure search. We propose a 2D AlSb-based homojunction field effect transistor that supports three distinct and nonvolatile resistance states. This new class of III-V semiconductor-derived 2D materials with dual ferroelectricity and antiferroelectricity opens up the opportunity for nonvolatile multibit-based integrated nanoelectronics.

First-principles structure prediction of two-dimensional HCN polymorphs obtained via formal molecular polymerization

In the present study, ab initio evolutionary algorithms and heuristic approach were used to predict new two-dimensional (2D) hydrogen cyanide crystalline phases based on HCN and HNC molecular building blocks. Our research revealed thirty-seven 2D HCN and HNC structures within six topological families which contain N₁, N₂ dimers, N₃ trimers, infinite poly-N motifs, or zigzag C-C chains. HSE06 functional calculations indicated that 2D 1Pmn2₁ HCN, 2Pma2 HCN, 3P2₁2₁2 HCN, and 6Pbcm HNC are direct semiconductors with band gaps E_g of 5.1, 4.2, 4.3, and 2.8 eV, respectively, and isovalent element substitutions (C by Ge/Si, and H by F) were performed to tune the electronic band gaps of the resulting 2D structures (E_g = 1.2-7.4 eV). Moreover, it has been found that the high in-plane Young's modulus (330.3-445.8 N m^-1) and strong tolerance of direct band transitions (E_g = 1.2-5.3 eV) against the external biaxial strains in these four 2D HCN structures endow them with potential applications in photofunctional and flexible electronic devices. Finally, ab initio molecular dynamics simulations showed that at 50 GPa and 400 K, HCN molecules in a bulk I4mm hydrogen cyanide molecular crystal can extend to 2D HCN covalent nets.

Optimal shapes of disk assembly in saturated random packings

Particle morphology is one of the most significant factors influencing the packing structures of granular materials. With certain targeted properties or optimization criteria, inverse packing problems have drawn extensive attention in terms of their adaptability to many material design tasks. An important question hard to answer is which particle shape, especially within given shape families, forms the densest (loosest) random packing? In this paper, we address this issue for the disk assembly model in two dimensions with an infinite variety of shapes, which are simulated in the random sequential adsorption process to suppress crystallization. Via a unique shape representation method, particle shapes are transformed into genotype sequences in the continuous shape space where we utilize the genetic algorithm as an efficient shape optimizer. Specifically, we consider three representative species of disk assembly, i.e., congruent tangent disks, incongruent tangent disks, and congruent overlapping disks, and carry out shape optimization on their packing densities in the saturated random state. We numerically search optimal shapes in the three species with a variable number of constituent disks which yield the maximal and minimal packing densities. We obtain an isosceles circulo-triangle and an unclosed ring for the maximal and minimal packing density in saturated random packings, respectively. The perfect sno-cone and isosceles circulo-triangle are also specifically investigated which give remarkably high packing densities of around 0.6, much denser than those of ellipses. This study is beneficial for guiding the design of particle shapes as well as the inverse design of granular materials.

Machine learned interatomic potential for dispersion strengthened plasma facing components

Tungsten (W) is a material of choice for the divertor material due to its high melting temperature, thermal conductivity, and sputtering threshold. However, W has a very high brittle-to-ductile transition temperature, and at fusion reactor temperatures (≥1000 K), it may undergo recrystallization and grain growth. Dispersion-strengthening W with zirconium carbide (ZrC) can improve ductility and limit grain growth, but much of the effects of the dispersoids on microstructural evolution and thermomechanical properties at high temperatures are still unknown. We present a machine learned Spectral Neighbor Analysis Potential for W-ZrC that can now be used to study these materials. In order to construct a potential suitable for large-scale atomistic simulations at fusion reactor temperatures, it is necessary to train on ab initio data generated for a diverse set of structures, chemical environments, and temperatures. Further accuracy and stability tests of the potential were achieved using objective functions for both material properties and high temperature stability. Validation of lattice parameters, surface energies, bulk moduli, and thermal expansion is confirmed on the optimized potential. Tensile tests of W/ZrC bicrystals show that although the W(110)-ZrC(111) C-terminated bicrystal has the highest ultimate tensile strength (UTS) at room temperature, observed strength decreases with increasing temperature. At 2500 K, the terminating C layer diffuses into the W, resulting in a weaker W-Zr interface. Meanwhile, the W(110)-ZrC(111) Zr-terminated bicrystal has the highest UTS at 2500 K.

Computational Design and Theoretical Properties of WC3N6, an H-Free Melaminate and Potential Multifunctional Material

By means of first-principles theory, existence, synthetic conditions, and structural as well as physicochemical properties have been predicted for the first hydrogen-free melaminate salt of the composition WC₃N₆. We find at least two energetically favorable polymorphs adopting space groups P1 and P3, both of which are layer-like porous materials. In addition to sizable Madelung fields stabilizing saltlike WC₃N₆, the complex C₃N₆^6- anions are connected via perfectly optimized W-N bonds, forming WN₅ in the P1 and WN₆ coordination polyhedra in the P3 polymorphs. The band gaps of the P1 and P3 phases are HSE-predicted as 2.25 and 1.21 eV, respectively, significantly smaller than those of g-C₃N₄ and WO₃. Moreover, both phases have suitable band-edge potentials that may provide sufficient driving force for photocatalytic water splitting; at least for the P1 phase, there is also a reasonable chance for reduced electron-hole recombination. In addition, the polymorphs's large optical absorption coefficients should greatly enhance the photocatalytic performance. WC₃N₆ defines a new class of compounds and has unique structural characteristics, mirrored from its electrical and optical properties, and it should provide another chemical path for preparing efficient photocatalysts and optoelectronic devices.

Stability of sulfur molecules and insights into sulfur allotropy

Using ab initio evolutionary algorithm USPEX, we predict structures of sulfur molecules S_n (n = 2 - 21). It is shown that for n ≥ 5 stable structures of sulfur molecules are closed helical rings, which is in agreement with the experimental data and previous calculations. We investigate the stability of molecules using the following criteria: second-order energy difference (Δ²E), fragmentation energy (E_frag) and HOMO-LUMO gaps. The S₈ molecule has the highest value of Δ²E and forms the most common allotropic form of sulfur (orthorhombic α-S), into which all other modifications convert over time at room temperature. Commonly found molecules S₁₂ and S₆ also have strongly positive Δ²E. Another well-known molecule, S₇, has negative Δ²E, but at temperatures above 900 K has positive second-order free energy difference Δ²G. Generally, Δ²E (or Δ²G at finite temperatures) is a quantitative measure of the stability allowing one to predict the ease of formation of molecules and corresponding molecular crystals. Temperature dependence of the above-mentioned measures of stability explains a wide range of facts about sulfur crystalline allotropes, molecules in the gas phase, etc.

Structural Polymorphism Kinetics Promoted by Charged Oxygen Vacancies in HfO_{2}

Defects such as oxygen vacancy are widely considered to be critical for the performance of ferroelectric HfO_{2}-based devices, and yet atomistic mechanisms underlying various exotic effects such as wake-up and fluid imprint remain elusive. Here, guided by a lattice-mode-matching criterion, we systematically study the phase transitions between different polymorphs of hafnia under the influences of neutral and positively charged oxygen vacancies using a first-principles-based variable-cell nudged elastic band technique. We find that the positively charged oxygen vacancy can promote the transition of various nonpolar phases to the polar phase kinetically, enabled by a transient high-energy tetragonal phase and extreme charge-carrier-inert ferroelectricity of the polar Pca2_{1} phase. The intricate coupling between structural polymorphism kinetics and the charge state of the oxygen vacancy has important implications for the origin of ferroelectricity in HfO_{2}-based thin films as well as wake-up, fluid imprint, and inertial switching.

(2×1) Reconstruction Mechanism of Rutile TiO2(011) Surface

Understanding the reconstruction kinetics of solid surfaces involving an ensemble of atomic movements is practically important but challenging due to the complexity of high-dimensional potential energy surfaces. Herein, we develop a step-deciding technique incorporated with the nudged elastic band method, which enables multidirection pathway sampling and ensures the capture of a minimum energy path (MEP). Using this approach, the (2×1) reconstruction mechanism of a rutile-TiO₂(011) surface, a classic and long-standing open problem in the fields of surface science and heterogeneous catalysis, is quantified, and the MEP is explicitly identified and explained. Following the least-bond-breaking rule, it gives a stepwise Ti-O bond cleavage mechanism with a collection of decoupled local structural relaxation modes at an overall barrier of 1.25 eV critically affected by initial Ti-O bond opening, which is much lower than the common synergy mechanism. Moreover, the adsorption-induced reconstruction is rationalized considering practical reaction conditions, where H atom adsorbate is shown to effectively stabilize the labile one-fold O_1c intermediate and promote the reconstruction kinetics. This work reveals the reconstruction mechanism regarding multiatom movements and provides a general method for the structural exploration of other complicated systems.

Zwitterionic or Not? Fast and Reliable Structure Determination by Combining Crystal Structure Prediction and Solid-State NMR

When it comes to crystal structure determination, computational approaches such as Crystal Structure Prediction (CSP) have gained more and more attention since they offer some insight on how atoms and molecules are packed in the solid state, starting from only very basic information without diffraction data. Furthermore, it is well known that the coupling of CSP with solid-state NMR (SSNMR) greatly enhances the performance and the accuracy of the predictive method, leading to the so-called CSP-NMR crystallography (CSP-NMRX). In this paper, we present the successful application of CSP-NMRX to determine the crystal structure of three structural isomers of pyridine dicarboxylic acid, namely quinolinic, dipicolinic and dinicotinic acids, which can be in a zwitterionic form, or not, in the solid state. In a first step, mono- and bidimensional SSNMR spectra, i.e., ¹H Magic-Angle Spinning (MAS), ¹³C and ¹⁵N Cross Polarisation Magic-Angle Spinning (CPMAS), ¹H Double Quantum (DQ) MAS, ¹H-¹³C HETeronuclear CORrelation (HETCOR), were used to determine the correct molecular structure (i.e., zwitterionic or not) and the local molecular arrangement; at the end, the RMSEs between experimental and computed ¹H and ¹³C chemical shifts allowed the selection of the correct predicted structure for each system. Interestingly, while quinolinic and dipicolinic acids are zwitterionic and non-zwitterionic, respectively, in the solid state, dinicotinic acid exhibits in its crystal structure a "zwitterionic-non-zwitterionic continuum state" in which the proton is shared between the carboxylic moiety and the pyridinic nitrogen. Very refined SSNMR experiments were carried out, i.e., ¹⁴N-¹H Phase-Modulated (PM) pulse and Rotational-Echo Saturation-Pulse Double-Resonance (RESPDOR), to provide an accurate N-H distance value confirming the hybrid nature of the molecule. The CSP-NMRX method showed a remarkable match between the selected structures and the experimental ones. The correct molecular input provided by SSNMR reduced the number of CSP calculations to be performed, leading to different predicted structures, while RMSEs provided an independent parameter with respect to the computed energy for the selection of the best candidate.

Protein structure prediction using the evolutionary algorithm USPEX

Protein structure prediction is one of major problems of modern biophysics: current attempts to predict the tertiary protein structure from amino acid sequence are successful mostly when the use of big data and machine learning allows one to reduce the "prediction problem" to the "problem of recognition". Compared with recent successes of deep learning, classical predictive methods lag behind in their accuracy for the prediction of stable conformations. Therefore, in this work we extended the evolutionary algorithm USPEX to predict protein structure based on global optimization starting with the amino acid sequence. Moreover, we compared frequently used force fields for the task of protein structure prediction. Protein structure relaxation and energy calculations were performed using Tinker (with several different force fields) and Rosetta (with REF2015 force field) codes. To create new protein structure models in the USPEX algorithm, we developed novel variation operators. The test of the new method on seven proteins having (for simplicity) no cis-proline (with ω ≈ 0°) residues, and a length of up to 100 residues, revealed that our algorithm predicts tertiary structures of proteins with high accuracy. The comparison of the final potential energies of the predicted protein structures obtained using the USPEX and the Rosetta Abinitio approach showed that in most cases the developed algorithm found structures with close or even lower energy (Amber/Charmm/Oplsaal) and scoring function (REF2015). While USPEX has clearly demonstrated its ability to find very deep energy minima, our study showed that the existing force fields are not sufficiently accurate for accurate blind prediction of protein structures without further experimental verification.

Phosphorus nanoclusters and insight into the formation of phosphorus allotropes

Elemental phosphorus has a striking variety of allotropes, which we analyze by looking at stable phosphorus clusters. We determine the ground-state structures of P_n clusters in a wide range of compositions (n = 2-50) using density functional calculations and global optimization techniques. We explain why the high-energy white phosphorus is so easily formed, compared to the much more stable allotropes - the tetrahedral P₄ cluster is so much more stable than nearby compositions that only by increasing the size to P₁₀ one can get a more stable non-P₄-based structure. Starting from 17 atoms, phosphorus clusters have a single-stranded structure, consisting of a set of well-resolved structural units connected by P₂ linking fragments. The investigation of relative stability has revealed even-odd alternations and structural magic numbers. The former are caused by the higher stability of clusters with even numbers of atoms due to closed electronic shells. The structural magic numbers are associated with the presence of particular stable structural units and lead to enhanced stability of P_18+12k (k = 0, 1, 2) clusters. We also compare the energies of the obtained ground-state structures with clusters of different phosphorus allotropes. Clusters of fibrous phosphorus are energetically the closest to the ground states, white phosphorus clusters are found to be less stable, and the least stable allotrope at the nanocluster scale is black phosphorene.