Crystal Structure Prediction via Efficient Sampling of the Potential Energy Surface

Organic Molecules Induce the Formation of Hopper-Like NaCl Crystals under Rapid Evaporation As Microcatalytic Reactors To Facilitate Micro/Nanoplastic Degradation

As representative examples of inorganic ionic crystals, NaCl and KCl usually form cubes during the natural evaporation process. Herein, we report the hopper-like NaCl and KCl crystals formed on the iron surface under rapid vacuum evaporation aided by organic molecules. Theoretical and experimental results indicate that it is attributed to the organic molecules alternating adsorption between {100} and {110} surfaces instead of adsorbing a single surface, as well as the fast crystal growth rate. Following this law, we found hopper-like crystals formed under natural evaporation conditions in salt lake crystals as well as synthesized kilogram-class hopper-like crystals. Interestingly, the hopper-like crystals can act as microcatalytic reactors to efficiently facilitate micro/nanoplastic degradation with ∼91.72% styrene yield, highly decreasing the degradation temperature from ∼400 to ∼275 °C. These findings provide an understanding of the growth mechanism of various crystals and a friendly environmental, low-carbon, and economical microcatalytic reactor for efficient micro/nanoplastic degradation.

Characterization of ephedrine HCl and pseudoephedrine HCl using quadrupolar NMR crystallography guided crystal structure prediction

Quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) is a nascent protocol for predicting, solving, and refining crystal structures. QNMRX-CSP employs a combination of solid-state NMR data from quadrupolar nuclides (i.e., nuclear spin >1/2), static lattice energies and electric field gradient (EFG) tensors from dispersion-corrected density functional theory (DFT-D2*) calculations, and powder X-ray diffraction (PXRD) data; however, it has so far been applied only to organic HCl salts with small and rigid organic components, using 35Cl EFG tensor data for both structural refinement and validation. Herein, QNMRX-CSP is extended to ephedrine HCl (Eph) and pseudoephedrine HCl (Pse), which are diastereomeric compounds that feature distinct space groups and organic components that are larger and more flexible. A series of benchmarking calculations are used to generate structural models that are validated against experimental data, and to explore the impacts of the: (i) starting structural models (i.e., geometry-optimized fragments based on either a known crystal structure or an isolated gas-phase molecule) and (ii) selection of unit cell parameters and space groups. Finally, we use QNMRX-CSP to predict the structure of Pse in the dosage form Sudafed® using only 35Cl SSNMR data as experimental input. This proof-of-concept work suggests the possibility of employing QNMRX-CSP to solve the structures of organic HCl salts in dosage forms - something which is often beyond the capabilities of conventional, diffraction-based characterization methods.

Leveraging Machine Learning Potentials for In-Situ Searching of Active sites in Heterogeneous Catalysis

This Perspective explores the integration of machine learning potentials (MLPs) in the research of heterogeneous catalysis, focusing on their role in identifying in situ active sites and enhancing the understanding of catalytic processes. MLPs utilize extensive databases from high-throughput density functional theory (DFT) calculations to train models that predict atomic configurations, energies, and forces with near-DFT accuracy. These capabilities allow MLPs to handle significantly larger systems and extend simulation times beyond the limitations of traditional ab initio methods. Coupled with global optimization algorithms, MLPs enable systematic investigations across vast structural spaces, making substantial contributions to the modeling of catalyst surface structures under reactive conditions. The review aims to provide a broad introduction to recent advancements and practical guidance on employing MLPs and also showcases several exemplary cases of MLP-driven discoveries related to surface structure changes under reactive conditions and the nature of active sites in heterogeneous catalysis. The prevailing challenges faced by this approach are also discussed.

Superconducting Electride Li9S with a Transition Temperature above the McMillan Limit

An electride, characterized by unique interstitial anionic electrons (IAEs), offers promising avenues for modulating its superconductivity. The pressure-dependent coupling between IAEs and orbital electrons significantly affects the superconducting transition temperature (Tc). However, existing research has predominantly concentrated on pressures within 300 GPa. To advance the understanding, we propose investigating the Li-S system under ultrahigh pressure to unveil novel electride superconductors. Five stable Li-rich electrides with diverse IAE topologies, including one Li7S, three Li9S, and one Li12S phases, are identified through structural search calculations. Among the Li9S phases, in the C2/c phase (600 GPa), the IAEs are connected to the S atomic extra-nuclear electrons with the unconventional d orbital attribute due to the extreme pressure, while two low-pressure R-3 (25 GPa) and C2/m (400 GPa) phases have interconnected IAEs. Due to its unique IAE attributes, C2/c Li9S exhibits the highest Tc of 53.29 K at 600 GPa. Its superconductivity results from the coupling of the S d, Li p electrons, and IAEs with the low-frequency phonons associated with the attraction between IAEs and the Li-S framework. Our work enhances insights into IAEs within electrides and their role in facilitating superconductivity.

Clathrate metal superhydrides under high-pressure conditions: enroute to room-temperature superconductivity

Room-temperature superconductivity has been a long-held dream of mankind and a focus of considerable interest in the research field of superconductivity. Significant progress has recently been achieved in hydrogen-based superconductors found in superhydrides (hydrides with unexpectedly high hydrogen contents) that are stabilized under high-pressure conditions and are not capturable at ambient conditions. Of particular interest is the discovery of a class of best-ever-known superconductors in clathrate metal superhydrides that hold the record for high superconductivity (e.g. T c = 250-260 K for LaH10) among known superconductors and have great promise to be those that realize the long-sought room-temperature superconductivity. In these peculiar clathrate superhydrides, hydrogen forms unusual 'clathrate' cages containing encaged metal atoms, of which such a kind was first reported in a calcium hexa-superhydride (CaH6) showing a measured high T c of 215 K under a pressure of 170 GPa. In this review, we aim to offer an overview of the current status of research progress on the clathrate metal superhydride superconductors, discuss the superconducting mechanism and highlight the key features (e.g. structure motifs, bonding features, electronic structure, etc.) that govern the high-temperature superconductivity. Future research direction along this line to find room-temperature superconductors will be discussed.

Performance of Particle Swarm Optimization in Predicting the Orientation of π-Conjugated Molecules Inside Carbon Nanotubes Compared with Density Functional Theory Calculations

Particle swarm optimization (PSO) was employed to obtain the global minimum of host-guest structures consisting of a triiodobenzene molecule (BzI3) inside an armchair (m,m) nanotube (BzI3@(m,m)), whose host-guest interactions are approximated by Lennard-Jones (LJ) potentials. The host-guest structures obtained using the PSO-LJ method were then compared with those obtained through dispersion-corrected density functional theory (DFT) calculations to evaluate the performance of the PSO-LJ approach in predicting the guest orientation inside a tube. When the inner space of the host tube is limited for guest encapsulation, the PSO-LJ method can reproduce the DFT results of BzI3@(m,m) in terms of the guest orientation. Conversely, in nanotubes with a sufficiently large space to allow a guest to freely move, corresponding to weak tube confinement, the PSO-LJ method yields guest orientations that are different from those obtained through DFT calculations; however, both methods obtain energetically close guest orientations. Accordingly, PSO-LJ method-assisted DFT calculations can quickly provide energetically stable guest orientations in BzI3@(m,m) in weak tube confinement, which can be ignored in DFT calculations, where a single initial geometry is typically used.

Metallic Re3O2 with mixed-valence states

Rhenium (Re) shows the richest valence states from +2 to +7 in compounds, but its mixed-valence states are still missing thus far. In this work, we have explored the Re-O phase diagram with a wide range of stoichiometric compositions under high pressure through first-principles structural search calculations. Besides identifying two novel high-pressure phases of ReO2 and ReO3, we reveal two hitherto unknown Re-rich Re3O2 and O-rich ReO4 compounds. Re atoms in Re3O2 show mixed-valence states due to their inequivalent coordination environments, the first example in Re-based compounds. Electronic structure calculations demonstrate that the four discovered Re-O phases exhibit metallicity contributed by Re 5d electrons. Among them, ReO3 has a predicted critical temperature of up to 12 K at 50 GPa, derived from the interaction between Re 5d electrons and Re-derived low-frequency phonons. Our study points to new opportunities to disclose novel transition metal compounds with mixed-valence states.

A pressure-induced superhard SiCN4 compound uncovered by first-principles calculations

Silicon-carbon-nitride (Si-C-N) compounds are a family of potential superhard materials with many excellent chemical and physical properties; however, only SiCN, Si2CN4 and SiC2N4 were synthesized. Here, we theoretically report a new SiCN4 compound with P41212, Fdd2 and R3̄ structures by first-principles structural predictions based on the particle swarm optimization algorithm. Pressure-induced structural phase transitions from P41212 to Fdd2, and then to the R3̄ phase were determined at 2 GPa and 249 GPa. By comparing enthalpy differences with 1/3Si3N4 + C + 4/3N2, it was found that these structures tend to decompose at ambient pressure. However, with the increase of pressure, the enthalpy differences of Fdd2 and R3̄ structures turn to be negative and they can be stabilized at a pressure of more than 41 GPa. They are also dynamically stable as no imaginary frequencies were found in their stabilized pressure ranges. The calculated band gap is 4.37 eV for P41212, 3.72 eV for Fdd2 and 3.81 eV for the R3̄ phase by using the Heyd-Scuseria-Ernzerhof (HSE06) method and the estimated Vickers hardness values are higher than 40 GPa by adopting the elastic modulus based hardness formula, which confirmed their superhard characteristics. These results provide significant insights into Si-C-N systems and will inevitably promote the future experimental works.

A DFT study towards dynamic structures of iron and iron carbide and their effects on the activity of the Fischer-Tropsch process

The Fe-based Fischer-Tropsch synthesis (FTS) catalyst shows a rich phase chemistry under pre-treatment and FTS conditions. The exact structural composition of the active site, whether iron or iron carbide (FeCx), is still controversial. Aiming to obtain an insight into the active sites and their role in affecting FTS activity, the swarm intelligence algorithm is implemented to search for the most stable Fe(100), Fe(110), Fe(210) surfaces with different carbon ratios. Then, ab initio atomistic thermodynamics and Wulffman construction were employed to evaluate the stability of these surfaces at different chemical potentials of carbon. Their FTS reactivity and selectivity were later assessed by semi-quantitative micro-kinetic equations. The results show that stability, reactivity, and selectivity of the iron are all affected by the carbonization process when the carbon ratio increases. Formation of the carbide, a rather natural process under experimental conditions, would moderately increase the turnover frequency (TOF), but both iron and iron carbide are active to the reaction.

Theoretical exploration of the bromine substitution effect and hydrostatic pressure responsive mechanism for room temperature phosphorescence

Stimulus-responsive organic room temperature phosphorescence (RTP) materials with long lifetimes, high efficiencies and tunable emission properties have broad applications. However, the amounts and species of efficient RTP materials are far from meeting the requirements and the inner stimulus-responsive mechanisms are unclear. Therefore, developing efficient stimulus-responsive RTP materials is highly desired and the relationship between the molecular structures and luminescent properties of RTP materials needs to be clarified. Based on this point, the influences of different substitution sites of Br on the luminescent properties of RTP molecules are studied by the combined quantum mechanics and molecular mechanics (QM/MM) coupled with thermal vibration correlation function (TVCF) theory. Moreover, the hydrostatic pressure effect on the efficiencies and lifetimes is explored and the inner mechanism is illustrated. The results show that, for the exciton conversion process, the o-substitution molecule possesses the largest spin-orbit coupling (SOC) value (〈S1|Ĥso|T1〉) in the intersystem crossing (ISC) process and this is conducive to the accumulation of triplet excitons. However, for the energy consumption process, the large SOC value (〈S0|Ĥso|T1〉) for the p-substitution molecule brings a fast non-radiative decay rate, and the small SOC value for the m-substitution molecule generates a decreased non-radiative decay rate which is helpful for realizing long lifetime emission. Keeping with this perspective, the conflict between high exciton utilization and long RTP emission needs to be balanced rather than enhancing the SOC effect by simply adding heavy atoms in RTP systems. Through regulating the molecular stacking modes by the hydrostatic pressure effect, the inner stimulus-responsive mechanism is revealed. The data of 〈S1|Ĥso|T1〉 in the ISC process remain almost unchanged, while 〈S0|Ĥso|T1〉 values and transition dipole moments are sensitive to the hydrostatic pressure. Under 1 GPa, the RTP molecule achieves a maximum efficiency (81.17%) and long lifetime (2.72 ms) with the smallest SOC and decreased non-radiative decay rate. To our knowledge, this is the first time that the hydrostatic pressure responsive mechanism for RTP molecules is revealed from a theoretical perspective, and the relationships between molecular structures and luminescent properties are detected. Our work could facilitate the development of high performance RTP molecules and expand their applications in multilevel information encryption.

Structures of LaH10, EuH9, and UH8 superhydrides rationalized by electron counting and Jahn-Teller distortions in a covalent cluster model

The superconducting hydrides LaH₁₀, EuH₉ and UH₈ are studied using chemically intuitive bonding analysis of periodic and molecular models. We find trends in the crystallographic and electronic structures of the materials by focusing on chemically meaningful building blocks in the predicted H sublattices. Atomic charge calculations, using two complementary techniques, allow us to assign oxidation states to the metals and divide the H sublattice into neutral and anionic components. Cubic [H₈]^q- clusters are an important structural motif, and molecular orbital analysis of this cluster in isolation shows the crystal structures to be consistent with our oxidation state assignments. Crystal orbital Hamilton population analysis confirms the applicability of the cluster model to the periodic electronic structure. A Jahn-Teller distortion predicted by MO analysis rationalises the distortion observed in a prior study of EuH₉. The impact of this distortion on superconductivity is determined, and implications for crystal structure prediction in other metal-hydrogen systems are discussed. Additionally, the performance of electronic structure analysis methods at high pressures are tested and recommendations for future studies are given. These results demonstrate the value of simple bonding models in rationalizing chemical structures under extreme conditions.

Data-driven prediction of complex crystal structures of dense lithium

Lithium (Li) is a prototypical simple metal at ambient conditions, but exhibits remarkable changes in structural and electronic properties under compression. There has been intense debate about the structure of dense Li, and recent experiments offered fresh evidence for yet undetermined crystalline phases near the enigmatic melting minimum region in the pressure-temperature phase diagram of Li. Here, we report on an extensive exploration of the energy landscape of Li using an advanced crystal structure search method combined with a machine-learning approach, which greatly expands the scale of structure search, leading to the prediction of four complex Li crystal structures containing up to 192 atoms in the unit cell that are energetically competitive with known Li structures. These findings provide a viable solution to the observed yet unidentified crystalline phases of Li, and showcase the predictive power of the global structure search method for discovering complex crystal structures in conjunction with accurate machine learning potentials.