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Non-adiabatic molecular dynamics (NAMD) simulations have become an indispensable tool for investigating excited-state dynamics in solids. In this work, we propose a general framework, N 2 AMD (Neural-Network Non-Adiabatic Molecular Dynamics), which employs an E(3)-equivariant deep neural Hamiltonian to boost the accuracy and efficiency of NAMD simulations. Distinct from conventional machine learning methods that predict key quantities in NAMD, N 2 AMD computes these quantities directly with a deep neural Hamiltonian, ensuring excellent accuracy, efficiency, and consistency. N 2 AMD not only achieves impressive efficiency in performing NAMD simulations at the hybrid functional level within the framework of the classical path approximation (CPA), but also demonstrates great potential in predicting non-adiabatic coupling vectors and suggests a method to go beyond CPA. Furthermore, N 2 AMD demonstrates excellent generalizability and enables seamless integration with advanced NAMD techniques and infrastructures. Taking several extensively investigated semiconductors as the prototypical system, we successfully simulate carrier recombination in both pristine and defective systems at large scales where conventional NAMD often significantly underestimates or even qualitatively incorrectly predicts lifetimes. This framework offers a reliable and efficient approach for conducting accurate NAMD simulations across various condensed materials. Accurate nonadiabatic molecular dynamics (NAMD) is crucial for studying excited-state dynamics in solids but is computationally expensive. Here, authors use machine learning to enhance the efficiency and accuracy of NAMD simulations in solids.

Van der Waals (vdW) magnets provide a rich landscape for innovative spintronic applications at atomic thickness. Among them, chromium sulfide bromide (CrSBr) stands out as a semiconducting antiferromagnet with the potential for magnetoelectric manipulation. However, the detection and electrical control of 2D magnetism in CrSBr are constrained by its centrosymmetric structure and in-plane antiferromagnetism. To address this challenge, we construct heterostructure devices composed of trilayer CrSBr and monolayer graphene, where interfacial charge transfer breaks the inversion symmetry of both magnetic order and crystallographic structure. The inversion symmetry breaking by charge transfer thus allows a full discrimination of the otherwise degenerate magnetic states using optical second harmonic generation, including the charge transfer induced intermediate magnetic states that consist of antiferromagnetic and ferromagnetic vdW interfaces. Furthermore, gate voltage enables the tuning of charge transfer, effectively modulating the interlayer magnetic coupling and magnetic transitions. Our findings deepen the understanding of optospintronic interaction and magnetoelectric manipulation in vdW magnets, paving the way for electrically tunable 2D spintronic devices. CrSBr is an air-stable van der Waals semiconducting layered antiferromagnet, holding the promise for a variety of spintronic applications. However, like all antiferromagnets, readout and control of the magnetic structures are challenging. Here, using a graphene gate on trilayer CrSBr, Hong, Sun, and coauthors succeed in full discrimination of otherwise degenerate magnetic states and electrical control of magnetic transitions.

A unified picture of the electronic relaxation dynamics of ionized liquid water has remained elusive despite decades of study. Here, we employ sub-two-cycle visible to short-wave infrared pump-probe spectroscopy and ab initio nonadiabatic molecular dynamics simulations to reveal that the excess electron injected into the conduction band (CB) of ionized liquid water undergoes sequential relaxation to the hydrated electron s ground state via an intermediate state, identified as the elusive p excited state. The measured CB and p -electron lifetimes are 0.26 ± 0.02 ps and 62 ± 10 fs, respectively. Ab initio quantum dynamics yield similar lifetimes and furthermore reveal vibrational modes that participate in the different stages of electronic relaxation, with initial relaxation within the dense CB manifold coupled to hindered translational motions whereas subsequent p -to- s relaxation facilitated by librational and even intramolecular bending modes of water. Finally, energetic considerations suggest that a hitherto unobserved trap state resides ~0.3-eV below the CB edge of liquid water. Our results provide a detailed atomistic picture of the electronic relaxation dynamics of ionized liquid water with unprecedented time resolution. A unified picture of the electronic relaxation dynamics of ionized liquid water remains elusive despite decades of study. Here, the authors use few-cycle optical pump-probe spectroscopy and ab initio quantum dynamics to unambiguously identify a new transient intermediate in the relaxation pathway.

Metal halide perovskites (MHPs) exhibit unusual properties and complex dynamics. By combining ab initio time-dependent density functional theory, nonadiabatic molecular dynamics and machine learning, we advance quantum dynamics simulation to nanosecond timescale and demonstrate that large fluctuations of MHP defect energy levels extend light absorption to longer wavelengths and enable trapped charges to escape into bands. This allows low energy photons to contribute to photocurrent through energy up-conversion. Deep defect levels can become shallow transiently and vice versa, altering the traditional defect classification into shallow and deep. While defect levels fluctuate more in MHPs than traditional semiconductors, some levels, e.g., Pb interstitials, remain far from band edges, acting as charge recombination centers. Still, many defects deemed detrimental based on static structures, are in fact benign and can contribute to energy up-conversion. The extended light harvesting and energy up-conversion provide strategies for design of novel solar, optoelectronic, and quantum information devices.

The electron‐phonon interaction is known as one of the major mechanisms determining electrical and thermal properties. In particular, it alters the carrier transport behaviors and sets fundamental limits to carrier mobility. Establishing how electrons interact with phonons and the resulting impact on the carrier transport property is significant for the development of high‐efficiency electronic devices. Here, carrier transport behavior mediated by the electron‐phonon coupling in BiFeO3 epitaxial thin films is directly observed. Acoustic phonons are generated by the inverse piezoelectric effect and coupled with photocarriers. Via the electron‐phonon coupling, doughnut shape carrier distribution has been observed due to the coupling between hot carriers and phonons. The hot carrier quasi‐ballistic transport length can reach 340 nm within 1 ps. The results suggest an effective approach to investigating the effects of electron‐phonon interactions with temporal and spatial resolutions, which is of great importance for designing and improving electronic devices. The hot carriers generated in BiFeO3 are capable of coupling with phonons and undergo quasi‐ballistic transport over a distance of 340 nm in the first picosecond. Even after undergoing cooling processes, the carrier diffusion coefficient mediated by electron‐phonon coupling remains significantly higher than that of bulk. These findings introduce novel perspectives for the development of efficient electronic devices based on BiFeO3.

Mechanistic studies on lead halide perovskites (LHPs) in recent years have suggested charge carrier screening as partially responsible for long carrier diffusion lengths and lifetimes that are key to superior optoelectronic properties. These findings have led to the ferroelectric large polaron proposal, which attributes efficient charge carrier screening to the extended ordering of dipoles from symmetry-breaking unit cells that undergo local structural distortion and break inversion symmetry. It remains an open question whether this proposal applies in general to semiconductors with LHP-like anharmonic and dynamically disordered phonons. Here, we study electron-phonon coupling in Bi₂O₂Se, a semiconductor which bears resemblance to LHPs in ionic bonding, spin-orbit coupling, band transport with long carrier diffusion lengths and lifetimes, and phonon disorder as revealed by temperature-dependent Raman spectroscopy. Using coherent phonon spectroscopy, we show the strong coupling of an anharmonic phonon mode at 1.50 THz to photo-excited charge carriers, while the Raman excitation of this mode is symmetry-forbidden in the ground-state. Density functional theory calculations show that this mode, originating from the A1g phonon of out-of-plane Bi/Se motion, gains oscillator strength from symmetry-lowering in polaron formation. Specifically, lattice distortion upon ultrafast charge localization results in extended ordering of symmetry-breaking unit cells and a planar polaron wavefunction, namely a two-dimensional polaron in a three-dimensional lattice. This study provides experimental and theoretical insights into charge interaction with anharmonic phonons in Bi₂O₂Se and suggests ferroelectric polaron formation may be a general principle for efficient charge carrier screening and for defect-tolerant semiconductors.

Light–matter interactions that induce charge and energy transfer across interfaces form the foundation for photocatalysis 1 , 2 , energy harvesting 3 and photodetection 4 , among other technologies. One of the most common mechanisms associated with these processes relies on carrier injection. However, the exact role of the energy transport associated with this hot-electron injection remains unclear. Plasmon-assisted photocatalytic efficiencies can improve when intermediate insulation layers are used to inhibit the charge transfer 5 , 6 or when off-resonance excitations are employed 7 , which suggests that additional energy transport and thermal effects could play an explicit role even if the charge transfer is inhibited 8 . This provides an additional interfacial mechanism for the catalytic and plasmonic enhancement at interfaces that moves beyond the traditionally assumed physical charge injection 9 – 12 . In this work, we report on a series of ultrafast plasmonic measurements that provide a direct measure of electronic distributions, both spatially and temporally, after the optical excitation of a metal/semiconductor heterostructure. We explicitly demonstrate that in cases of strong non-equilibrium, a novel energy transduction mechanism arises at the metal/semiconductor interface. We find that hot electrons in the metal contact transfer their energy to pre-existing free electrons in the semiconductor, without an equivalent spatiotemporal transfer of charge. Further, we demonstrate that this ballistic thermal injection mechanism can be utilized as a unique means to modulate plasmonic interactions. These experimental results are well-supported by both rigorous multilayer optical modelling and first-principle ab initio calculations. An energy transduction mechanism across metal/semiconductor interfaces, which relies on electron–electron energy transfer rather than the transport of charge, is demonstrated through ultrafast infrared spectroscopy. This ballistic thermal injection process allows for extended modulation of plasmonic absorption in epsilon-near-zero media.

The calculation of electron-phonon couplings (EPCs) is essential for understanding various fundamental physical properties, including electrical transport, optical and superconducting behaviors in materials. However, obtaining EPCs through fully first-principles methods is notably challenging, particularly for large systems or when employing advanced functionals. Here we introduce a machine learning framework to accelerate EPC calculations by utilizing atomic orbital-based Hamiltonian matrices and gradients predicted by an equivariant graph neural network. We demonstrate that our method not only yields EPC values in close agreement with first-principles results but also enhances calculation efficiency by several orders of magnitude. Application to GaAs using the Heyd-Scuseria-Ernzerhof functional reveals the necessity of advanced functionals for accurate carrier mobility predictions, while for the large Kagome crystal CsV Sb , our framework reproduces the experimentally observed double domes in pressure-induced superconducting phase diagrams. This machine learning framework offers a powerful and efficient tool for the investigation of diverse EPC-related phenomena in complex materials.

The lifetimes of non-equilibrium charge carriers in semiconductors calculated using non-adiabatic molecular dynamics often differ from experimental results by orders of magnitude. By revisiting the definition of carrier lifetime, we report a systematic procedure for calculating the effective carrier lifetime in semiconductor crystals under realistic conditions. The consideration of all recombination mechanisms and the use of appropriate carrier and defect densities are crucial to bridging the gap between modeling and measurements. Our calculated effective carrier lifetime of CH NH PbI agrees with experiments, and is limited by band-to-band radiative recombination and Shockley-Read-Hall defect-assisted non-radiative recombination, whereas the band-to-band non-radiative recombination is found to be negligible. The procedure is further validated by application to the compound semiconductors CdTe and GaAs, and thus can be applied in carrier lifetime simulations in other material systems.