Nonadiabaticity in the iron bcc to hcp phase transformation

Strategic sampling with stochastic surface walking for machine learning force fields in iron's bcc-hcp phase transitions

This study developed a machine learning-based force field for simulating the bcc-hcp phase transitions of iron. By employing traditional molecular dynamics sampling methods and stochastic surface walking sampling methods, combined with Bayesian inference, we construct an efficient machine learning potential for iron. By using SOAP descriptors to map structural data, we find that the machine learning force field exhibits good coverage in the phase transition space. Accuracy evaluation shows that the machine learning force field has small errors compared to DFT calculations in terms of energy, force, and stress evaluations, indicating excellent reproducibility. Additionally, the machine learning force field accurately predicts the stable crystal structure parameters, elastic constants, and bulk modulus of bcc and hcp phases of iron, and demonstrates good performance in predicting higher-order derivatives and phase transition processes, as evidenced by comparisons with DFT calculations and existing experimental data. Therefore, our study provides an effective tool for investigating the phase transitions of iron using machine learning methods, offering new insights and approaches for materials science and solid-state physics research.

Cathodoluminescence and optical absorption spectroscopy of plasmonic modes in chromium micro-rods

Manipulating light at the sub-wavelength level is a crucial feature of surface plasmon resonance (SPR) properties for a wide range of nanostructures. Noble metals like Au and Ag are most commonly used as SPR materials. Significant attention is being devoted to identify and develop non-noble metal plasmonic materials whose optical properties can be reconfigured for plasmonic response by structural phase changes. Chromium (Cr) which supports plasmon resonance, is a transition metal with shiny finished, highly non-corrosive, and bio-compatible alloys, making it an alternative plasmonic material. We have synthesized Cr micro-rods from a bi-layer of Cr/Au thin films, which evolves from face centered cubic to hexagonal close packed (HCP) phase by thermal activation in a forming gas ambient. We employed optical absorption spectroscopy and cathodoluminescence (CL) imaging spectroscopy to observe the plasmonic modes from the Cr micro-rod. The origin of three emission bands that spread over the UV-Vis-IR energy range is established theoretically by considering the critical points of the second-order derivative of the macroscopic dielectric function obtained from density functional theory (DFT) matches with interband/intraband transition of electrons observed in density of states versus energy graph. The experimentally observed CL emission peaks closely match thes-dandd-dband transition obtained from DFT calculations. Our findings on plasmonic modes in Cr(HCP) phase can expand the range of plasmonic material beyond noble metal with tunable plasmonic emissions for plasmonic-based optical technology.

Closest Packing Polymorphism Interfaced Metastable Transition Metal for Efficient Hydrogen Evolution

Metastable materials are promising because of their catalytic properties, high-energy structure, and unique electronic environment. However, the unstable nature inherited from the metastability hinders further performance improvement and practical applications of these materials. Herein, this limitation is successfully addressed by constructing an in situ polymorphism interface (inf) between the metastable hexagonal-close-packed (hcp) phase and its stable counterpart (face-centered cubic, fcc) in cobalt-nickel (CoNi) alloy. Calculations reveal that the interfacial synergism derived from the hcp and fcc phases lowers the formation energy and enhances stability. Consequently, the optimized CoNi-inf exhibits an exceptionally low potential of 72 mV at 10 mA cm^-2 and a Tafel slope of 57 mV dec^-1 for the hydrogen evolution reaction (HER) in 1.0 m KOH. Furthermore, it is superior to most state-of-the-art non-noble-metal-based HER catalysts. No noticeable activity decay or structural changes are observed even over 14 h of catalysis. The computational simulation further rationalizes that the interface of CoNi-inf with a suitable d-band center provides uniform sites for hydrogen adsorption, leading to a distinguished HER catalytic activity. This work, therefore, presents a new route for designing metastable catalysts for potential energy conversion.

Atomistic Simulation of Adiabatic Reactive Processes Based on Multi-State Potential Energy Surfaces

The adiabatic reactive molecular dynamics (ARMD) method provides a framework to study chemical reactions using molecular dynamics simulations with minimal computational overhead. Here, ARMD is generalized to an arbitrary reactive process between two states in which reactants and products can be treated by an atomistic force field. The implementation is described, and the method is applied to two systems: the kinetics of NO rebinding to myoglobin (Mb) as a validation system and the conformational transition in neuroglobin (Ngb) which explores the full functionality of ARMD. For MbNO, the nonexponential kinetics observed both in experiment and earlier ARMD studies is reproduced. Furthermore, the sensitivity of the results with respect to the asymptotic separation between the two potential energy surfaces (NO bound and unbound) is studied.

Density functional theory for transition metals and transition metal chemistry

We introduce density functional theory and review recent progress in its application to transition metal chemistry. Topics covered include local, meta, hybrid, hybrid meta, and range-separated functionals, band theory, software, validation tests, and applications to spin states, magnetic exchange coupling, spectra, structure, reactivity, and catalysis, including molecules, clusters, nanoparticles, surfaces, and solids.