Enhancing crystal structure prediction by decomposition and evolution schemes based on graph theory

Two-Dimensional M-Chalcogene Family with Tunable Superconducting, Topological, and Magnetic Properties

An interesting question is whether chalcogen atoms can emulate the role of carbon or boron elements stabilized between two transition metal layers, as observed in MXenes or MBenes. Here, we predict a new family of two-dimensional ternary compounds M4XY2 (where M = Pd, Y, Zr, etc.; X = S, Se, Te; and Y = Cl, Br, I), named M-chalcogene. Through first-principles calculations, we reveal diverse physical properties in these compounds, including superconducting, topological, and magnetic characteristics, where the bilayer transition metals play crucial roles. Moreover, the expected helical edge states and superconducting transition temperatures in Pd4SCl2 can be finely tuned by strains. Additionally, the Ti4SCl2 is predicted to be a topological insulator and shows promise as a gas sensor candidate for certain exotic gases. Our findings expand two-dimensional material families and provide promising platforms for diverse physical phenomena with efficient tunability by external stimuli for various applications.

Superconducting ternary hydrides in Ca-U-H under high pressure

The research on hydrogen-rich ternary compounds attract tremendous attention for it paves new route to room-temperature superconductivity at lower pressures. Here, we study the crystal structures, electronic structures, and superconducting properties of the ternary Ca-U-H system, combining crystal structure predictions withab-initiocalculations under high pressure. We found four dynamically stable structures with hydrogen clathrate cages: CaUH12-Cmmm, CaUH12-Fd-3m, Ca2UH18-P-3m1, and CaU3H32-Pm-3m. Among them, the Ca2UH18-P-3m1 and CaU3H32-Pm-3mare likely to be synthesized below 1 megabar. Thefelectrons in U atoms make dominant contribution to the electronic density of states around the Fermi energy. The electron-phonon interaction calculations reveal that phonon softening in the mid-frequency region can enhance the electron-phonon coupling significantly. TheTcvalue of Ca2UH18-P-3m1 is estimated to be 57.5-65.8 K at 100 GPa. Our studies demonstrate that introducing actinides into alkaline-earth metal hydrides provides possibility in designing novel superconducting ternary hydrides.

A whale optimization algorithm based on atom-like structure differential evolution for solving engineering design problems

The whale optimization algorithm has received much attention since its introduction due to its outstanding performance. However, like other algorithms, the whale optimization algorithm still suffers from some classical problems. To address the issues of slow convergence, low optimization precision, and susceptibility to local convergence in the whale optimization algorithm (WOA). Defining the optimization behavior of whale individuals as quantum mechanical behavior, a whale optimization algorithm based on atom-like structure differential evolution (WOAAD) is proposed. Enhancing the spiral update mechanism by introducing a sine strategy guided by the electron orbital center. Improving the random-walk foraging mechanism by applying mutation operations to both the electron orbital center and random individuals. Performing crossover operations between the newly generated individuals from the improved mechanisms and random dimensions, followed by a selection process to retain superior individuals. This accelerates algorithm convergence, enhances optimization precision, and prevents the algorithm from falling into local convergence. Finally, implementing a scouting bee strategy, where whale individuals progressively increase the number of optimization failures within a limited parameter L. When a threshold is reached, random initialization is carried out to enhance population diversity. Conducting simulation experiments to compare the improved algorithm with the whale optimization algorithm, other optimization algorithms, and other enhanced whale optimization algorithms. The experimental results indicate that the improved algorithm significantly accelerates convergence, enhances optimization precision, and prevents the algorithm from falling into local convergence. Applying the improved algorithm to five engineering design problems, the experimental results demonstrate that the improved algorithm exhibits good applicability.

Purely single-bonded spiral nitrogen chains stabilized by trivalent lanthanum ions

Inspired by the single-bonded nitrogen chains stabilized by tetravalent cerium, pentavalent tantalum, and hexavalent tungsten atoms, we explored the possibility of single-bonded nitrogen polymorphs stabilized by trivalent lanthanum ions. To achieve this, we utilized the crystal structure search method on the phase diagram of binary La-N compounds. We identified three novel thermodynamically stable phases, the C2/c LaN3, P-1 LaN4, and P-1 LaN8. Among them, the C2/c phase with infinite helical poly-N6 chains becomes thermodynamically stable above 50 GPa. Each nitrogen atom in the poly-N6 chain acquires one extra electron, and the spiral chain is purely single-bonded. The C2/c phase has an indirect band gap of ∼1.6 eV at 60 GPa. Notably, the band gap exhibits non-monotonic behavior, decreases first and then increases with increasing pressure. This abnormal behavior is attributed to the significant bonding of two La-N bonds at around 35 GPa. Phonon spectrum calculations and AIMD simulations have confirmed that the C2/c phase can be quenched to ambient conditions with slight distortion, and it exhibits excellent detonation properties. Additionally, we also discovered armchair-like nitrogen chains in LaN4 and the armchair and zigzag-like mixed nitrogen chains in LaN8. These results provide valuable insights into the electronic and bonding properties of nitrides under high pressure and may have important implications for the design and development of novel functional materials.

Graph Partitions in Chemistry

We study partitions (equitable, externally equitable, or other) of graphs that describe physico-chemical systems at the atomic or molecular level; provide examples that show how these partitions are intimately related with symmetries of the systems; and discuss how such a link can further lead to insightful relations with the systems' physical and chemical properties. We define a particular kind of graph partition, which we call Chemical Equitable Partition (CEP), accounting for chemical composition as well as connectivity and associate it with a quantitative measure of information reduction that accompanies its derivation. These concepts are applied to model molecular and crystalline solid systems, illustrating their potential as a means to classify atoms according to their chemical or crystallographic role. We also cluster materials in meaningful manners that take their microstructure into account and even correlate them with the materials' physical properties.

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.

Magnesium oxide-water compounds at megabar pressure and implications on planetary interiors

Magnesium Oxide (MgO) and water (H₂O) are abundant in the interior of planets. Their properties, and in particular their interaction, significantly affect the planet interior structure and thermal evolution. Here, using crystal structure predictions and ab initio molecular dynamics simulations, we find that MgO and H₂O can react again at ultrahigh pressure, although Mg(OH)₂ decomposes at low pressure. The reemergent MgO-H₂O compounds are: Mg₂O₃H₂ above 400 GPa, MgO₃H₄ above 600 GPa, and MgO₄H₆ in the pressure range of 270-600 GPa. Importantly, MgO₄H₆ contains 57.3 wt % of water, which is a much higher water content than any reported hydrous mineral. Our results suggest that a substantial amount of water can be stored in MgO rock in the deep interiors of Earth to Neptune mass planets. Based on molecular dynamics simulations we show that these three compounds exhibit superionic behavior at the pressure-temperature conditions as in the interiors of Uranus and Neptune. Moreover, the water-rich compound MgO₄H₆ could be stable inside the early Earth and therefore may serve as a possible early Earth water reservoir. Our findings, in the poorly explored megabar pressure regime, provide constraints for interior and evolution models of wet planets in our solar system and beyond.

Pressure Stabilized Lithium-Aluminum Compounds with Both Superconducting and Superionic Behaviors

Superconducting and superionic behaviors have physically intriguing dynamic properties of electrons and ions, respectively, both of which are conceptually important and have great potential for practical applications. Whether these two phenomena can appear in the same system is an interesting and important question. Here, using crystal structure predictions and first-principle calculations combined with machine learning, we identify several stable Li-Al compounds with electride behavior under high pressure, and we find that the electronic density of states of some of the compounds has characteristics of the two-dimensional electron gas. Among them, we estimate that Li_{6}Al at 150 GPa has a superconducting transition temperature of around 29 K and enters a superionic state at a high temperature and wide pressure range. The diffusion in Li_{6}Al is found to be affected by an electride and attributed to the atomic collective motion. Our results indicate that alkali metal alloys can be effective platforms to study the abundant physical properties and their manipulation with pressure and temperature.

Superionic Silica-Water and Silica-Hydrogen Compounds in the Deep Interiors of Uranus and Neptune

Silica, water, and hydrogen are known to be the major components of celestial bodies, and have significant influence on the formation and evolution of giant planets, such as Uranus and Neptune. Thus, it is of fundamental importance to investigate their states and possible reactions under the planetary conditions. Here, using advanced crystal structure searches and first-principles calculations in the Si-O-H system, we find that a silica-water compound (SiO_{2})_{2}(H_{2}O) and a silica-hydrogen compound SiO_{2}H_{2} can exist under high pressures above 450 and 650 GPa, respectively. Further simulations reveal that, at high pressure and high temperature conditions corresponding to the interiors of Uranus and Neptune, these compounds exhibit superionic behavior, in which protons diffuse freely like liquid while the silicon and oxygen framework is fixed as solid. Therefore, these superionic silica-water and silica-hydrogen compounds could be regarded as important components of the deep mantle or core of giants, which also provides an alternative origin for their anomalous magnetic fields. These unexpected physical and chemical properties of the most common natural materials at high pressure offer key clues to understand some abstruse issues including demixing and erosion of the core in giant planets, and shed light on building reliable models for solar giants and exoplanets.

Metallic Aluminum Suboxides with Ultrahigh Electrical Conductivity at High Pressure

Aluminum, as the most abundant metallic elemental content in the Earth's crust, usually exists in the form of alumina (Al₂O₃). However, the oxidation state of aluminum and the crystal structures of aluminum oxides in the pressure range of planetary interiors are not well established. Here, we predicted two aluminum suboxides (Al₂O, AlO) and two superoxides (Al₄O₇, AlO₃) with uncommon stoichiometries at high pressures using first-principle calculations and crystal structure prediction methods. We find that the P4/nmm Al₂O becomes stable above ~765 GPa and may survive in the deep mantles or cores of giant planets such as Neptune. Interestingly, the Al₂O and AlO are metallic and have electride features, in which some electrons are localized in the interstitials between atoms. We find that Al₂O has an electrical conductivity one order of magnitude higher than that of iron under the same pressure-temperature conditions, which may influence the total conductivity of giant planets. Our findings enrich the high-pressure phase diagram of aluminum oxides and improve our understanding of the interior structure of giant planets.

Robust Quantum Search with Uncertain Number of Target States

The quantum search algorithm is one of the milestones of quantum algorithms. Compared with classical algorithms, it shows quadratic speed-up when searching marked states in an unsorted database. However, the success rates of quantum search algorithms are sensitive to the number of marked states. In this paper, we study the relation between the success rate and the number of iterations in a quantum search algorithm of given λ=M/N, where M is the number of marked state and N is the number of items in the dataset. We develop a robust quantum search algorithm based on Grover–Long algorithm with some uncertainty in the number of marked states. The proposed algorithm has the same query complexity ON as the Grover’s algorithm, and shows high tolerance of the uncertainty in the ratio M/N. In particular, for a database with an uncertainty in the ratio M±MN, our algorithm will find the target states with a success rate no less than 96%.