All-solid-state lithium batteries (ASSLBs) offer improved energy density and safety over traditional liquid-electrolyte systems. However, their practical use is limited by the rigidity of inorganic lithium superionic conductors, which require impractically high stack pressures (>50 MPa) to maintain close solid-solid contacts during cycling. We introduce the idea of incorporating nonmetal-chlorine chemical bonds into the conductive network to make rigid conductors more flexible. Because nonmetal-chlorine chemical bonds (e.g., P-Cl, Si-Cl) exhibit low bond dissociation energies, they can undergo facile rotation and torsion, thereby facilitating Li+ migration and framework deformability. A liquid SiCl4 activation method is developed to introduce these chemical bonds, yielding a soft superionic conductor, Li3P0.58Si1.25Zr1.78Cl10.86O3.58. This material shows a high room-temperature Li+ conductivity of 4.55 mS cm-1 and a low Young's modulus of 2.09 GPa. This combination enables over 3000 cycles of ultrahigh-nickel cathode LiNi0.92Co0.05Mn0.03O2 at a high current density of 3 mA cm-2, and even allows for stable operation of ASSLBs with no capacity decay after 300 cycles under a low stack pressure of 5 MPa, much lower than the usual 50 MPa needed for most inorganic superionic conductors. Additionally, this chemical-bond-tuning method works with various nonmetal centers (P, Si, C, S), providing a flexible strategy for designing deformable superionic conductors suitable for low-pressure ASSLBs.

Lithium (Li) metal batteries hold substantial promise for suppressing the theoretical limitations of conventional lithium-ion batteries (LIBs), enabled by the ultrahigh energy density exceeding 500 Wh kg-1 and 1000 Wh L-1. However, safety concerns such as uncontrolled dendrite formation and rapid thermal runaway severely hinder its practical deployment. Replacing flammable liquid electrolytes with thermal-stable solid-state electrolytes (SSEs) to construct all-solid-state batteries (ASSBs) has attracted significant attention. Among various candidates, halide-based SSEs have emerged as a promising choice owing to their high ionic conductivity, wide electrochemical stability windows, and scalable synthesis routes. To accelerate materials discovery beyond empirical trial-and-error approaches, data-driven strategies, encompassing high-throughput computation, descriptor-based screening, and machine-learning-assisted prediction, are increasingly integrated into halide-based SSEs (HSSEs) research. Despite rapid progress, systematic discrepancies between theoretical predictions and experimental observations persist, limiting the predictive reliability. This review summarizes recent advances in data-driven studies of HSSEs, elucidating structure-property relationships, assessing the role of artificial intelligence in guiding materials design and synthesis. By emphasizing both acquired achievements and persistent theory-experiment gaps, this review underscores the pivotal role of theory-guided discovery and rational calibration strategies in promoting the development of next-generation HSSEs for high-performance ASSBs.

Liquid-phase Fourier transform infrared (FTIR) is applied for in situ and quantitative studies on the most commonly investigated ligand exchange reaction, i.e., replacement of alkanoates by alkylthiolate ligands on CdSe nanocrystals (NCs). The forward reaction on CdSe NCs with controlled facet structures─zinc-blende (100) facets proceeds in two distinctive channels, with time constants of ∼5 and ∼106 s, respectively. The fast channel occurs between thiols in solution and alkanoate ligands on the edges of the facets, with a near-infinity equilibrium constant. FTIR and solid-state NMR measurements suggest that the remaining alkanoate ligands on a (100) facet are promoted from a chelating to a bridging motif by the incoming thiolate ligands. The slow channel combines the on-edge exchange and on-facet position swapping between a pair of adjacent thiolate and alkanoate ligands. Monte Carlo simulation reveals two on-facet position swapping pathways with time constants as ∼240 and ∼450 s. The reverse ligand exchange also possesses a large chemical equilibrium constant, but it can only occur on few unique bonding sites that are unsuited for the thiolate binding motif. Results here imply that the ligand chemistry of colloidal NCs can be advanced to a quantitative level with molecular resolution.

The surface hydrogen species of zinc oxide (ZnO) nanocrystals, including hydroxyl groups and water, play critical roles in determining their chemical reactivity, colloidal stability, and optoelectronic properties. However, direct structural identification of these surface species remains challenging due to their complex nature and surface disorder of the nanocrystals. Here, we present a comprehensive analysis of surface functionalities on sol-gel synthesized ZnO nanocrystals using advanced multinuclear and multidimensional solid-state nuclear magnetic resonance (NMR) spectroscopy, combined with density functional theory (DFT) theoretical calculations. By employing 1H, 7Li, 13C, 17O, and 31P NMR, alongside the use of deuterated precursors, 17O isotope labeling, probe molecules, defect analysis, and electron paramagnetic resonance (EPR) spectroscopy, we resolve and assign eight distinct hydrogen species, including acetate and lithium acetate ligands, chemisorbed and physisorbed water, terminal hydroxyls (OHT), tribridged hydroxyls (μ3-OH), and defect-associated hydroxyls. Furthermore, 1H-1H homonuclear correlation SSNMR experiments elucidate the crystal facet selectivity and spatial interactions of these surface hydrogen species. Our study establishes an in-depth understanding of the rich surface hydrogen landscape on ZnO nanocrystals and offers a framework for the rational design and functional tuning of ZnO-based nanomaterials.

Understanding how complex systems transition between order and chaos is a central challenge of nonequilibrium physics. While weak perturbations of classical integrable systems give rise to a mixed phase space of coexisting regular and chaotic trajectories, analogous behavior in interacting quantum many-body systems has remained elusive. Here we develop and experimentally implement a hybrid quantum-classical feedback protocol that autonomously discovers and stabilizes long-lived regular trajectories in a superconducting quantum processor. Each iteration combines short-time quantum evolution with classical optimization that projects the dynamics back onto a low-entanglement variational manifold, effectively distilling coherence from chaotic evolution. The stabilized trajectories reveal a quantum many-body mixed phase space emerging from nonlinear variational dynamics, without a direct analogue in classical or few-body quantum systems. Our results establish a versatile framework for algorithmic discovery and control of coherent dynamics previously inaccessible to experiment.

Two-dimensional π-conjugated covalent organic frameworks (COFs) have recently been shown to exhibit exceptionally high charge-carrier mobilities, challenging conventional views of charge transport in organic materials. In this study, we investigate the microscopic origin of charge transport in single-layer phthalocyanine-based poly(benzimidazobenzophenanthroline) ladder-type COFs using large-scale nonadiabatic molecular dynamics simulations based on ab initio-parameterized Holstein-Peierls Hamiltonians. Density functional theory calculations reveal narrow yet dispersive valence bands with small reduced effective masses and weak electron-phonon coupling, reflecting the rigid, fully fused backbone of the framework. To go beyond static band-structure descriptions, here we employ mixed quantum-classical surface-hopping simulations that explicitly account for both local and nonlocal electron-phonon interactions in large two-dimensional lattices. Despite the limited electronic bandwidths, the simulations predict band-like hole transport with a power-law temperature dependence and room-temperature mobilities exceeding 103 cm2 V-1 s-1. This unusually high mobility is attributed to the exceptionally low dynamical energetic disorder and suppressed coupling fluctuations enabled by the structural rigidity and long-range order of the COF lattice. In contrast, the introduction of moderate static disorder leads to rapid localization and a crossover to hopping-dominated transport. These results provide a microscopic understanding of ultrahigh charge mobilities in ladder-type two-dimensional COFs and establish key design principles for achieving efficient charge transport in organic framework materials.

Theoretical simulation of nonadiabatic scattering dynamics involves delicate treatment of both electronic coherence and decoherence all the time. In this study, we investigate the multiconfigurational Ehrenfest (MCE) dynamics with adaptive basis set expansion to capture the growing entanglement between the electronic states and the nuclear degrees of freedom with time, which shares the same features with the well-known overcoherence problem in the traditional Ehrenfest mean field method. Inspired by the decoherence studies in the framework of mixed quantum-classical dynamics, we here propose a decoherence-induced adaptive MCE (DA-MCE) method, which can deal with the coherent propagation and quantum decoherence in nonadiabatic scattering dynamics simultaneously. As demonstrated in the three famous Tully models, DA-MCE can efficiently capture the time evolution of the reduced density matrix, the Stueckelberg interference, and the rapid decoherence. In particular, both the adaptive expansion of the basis set and the form of the variational Ansatz are found to be highly important for the description of complex dynamics. Compared to the multiconfigurational surface hopping method proposed recently, our DA-MCE can also be regarded as a multiconfigurational version of the branching corrected mean field method, which indicates the potential combination of general mixed quantum-classical trajectories with the proposed multiconfigurational approach.

We propose a simple but robust variant of the fuzzy global optimization method, FGO-3body, to unbiasedly deal with large clusters with complex three-body interactions. For fullerene clusters (C60)N with the first-principles PPR potential energy surfaces, the three-body interactions have posed a major challenge, thus restricting the global optimization studies to cluster sizes of N ≤ 105 so far. In sharp contrast, our new FGO-3body method successfully increases this size to N ≤ 320. The corresponding global minimum structures and energies, magic sizes, and growth patterns have been obtained. In comparison with the results available in the literature for (C60)11 ≤ N ≤ 105, we additionally identify 14 and 3 new clusters with even lower energies using the PPR pair potential (with two-body interactions only) and the PPR potential (with both two-body and three-body interactions), respectively. In particular, after including the three-body interactions, small clusters with icosahedral structures become relatively less favored, and large clusters turn from decahedral to close-packed structures for N = 85, 87, 94, 98, 100, 153, 224, 231, 253, 269, and 285. Thereby, we have shown that FGO-3body is a powerful global structure optimization method for complex clusters.

The framework of mixed quantum-classical dynamics is promising for realizing efficient and reliable simulations of general nonadiabatic dynamics processes. In particular, the surface hopping method based on independent trajectories has attracted extensive interest over the past decades. In practical applications, however, its accuracy is often limited by the overcoherence problem. To address this limitation, we here utilize a machine learning approach to reveal the optimal decoherence time formula for high-dimensional systems and consider the kinetic energy projected along various force directions as the feature inputs. Remarkably, the obtained formula consistently distinguishes itself within the training set across four distinct descriptor spaces. The systematic benchmark confirms the high reliability of the formula based on the kinetic energy projected along the force direction of the nonactive potential energy surface. In fact, the vast majority of average population errors achieved by surface hopping with the new formula are below 0.01 and 0.02 in the investigated one- and two-dimensional systems, respectively. These results thus highlight the high performance of the new decoherence time formula in nonadiabatic scattering dynamics and demonstrate the feasibility of projecting the total kinetic energy onto a proper force direction to uncover the intricate decoherence effect in high-dimensional applications.

ABSTRACT A hexacationic cage incorporating three urea units can encapsulate two mutually repulsive anions in close proximity through a combination of hydrogen bonding and electrostatic interactions. This leads to exceptionally high binding affinities, with a K 1 × K 2 value of approximately 10 20 M ‒2 in MeCN‐ d 3 , for pairs of Cl ‒ or F ‒ anions. In its unbound state, the cage adopts a collapsed conformation stabilized by intramolecular interactions. These interactions are disrupted upon binding of the first anion guest, inducing an unfolded conformation that facilitates the binding of the second guest. Consequently, despite repulsion, the second Cl ‒ anion binds more strongly than the first by three orders of magnitude. This work presents a straightforward strategy for mimicking biological allosteric regulation and offers insights into the underlying physicochemical principles. The strong halide binding enables several applications. The cage can extract F ‒ from CaF 2 , suggesting a route to utilize fluorine from fluorspar for fluorochemical synthesis that bypasses the generation of hazardous HF. Furthermore, the cage can extract Cl ‒ or Br ‒ anions from organic halides, thereby stabilizing the corresponding carbocations and accelerating reactions involving these intermediates. In addition, the high affinity of the cage for halide anions released from fire suppressants provides for corrosion resistance.

It is still controversial whether the phonon bottleneck effect, traditionally considered to be negligible in strongly confined quantum dots (QDs) due to the efficient electron-hole energy exchange in Auger processes, could become more significant in n-doped QDs with fully occupied valence bands. In this study, we employ a generalized Holstein-Peierls Hamiltonian to describe the electron-vibration couplings in QDs and study the hot electron relaxation dynamics by large-scale nonadiabatic dynamics simulations based on the proposed effective Hamiltonian method. The high-energy electron undergoes rapid relaxation, driven by the high electronic density of states (DOS) and strong effective electron-vibration coupling in the energy space. In contrast, the time propagation of medium- and low-energy electrons shows an evident phonon bottleneck effect, characterized by the large energy separations that necessitate multiphonon processes, resulting in the relaxation time on the nanosecond scale. The electron relaxation rate is found to exhibit a power-law dependence on the electronic DOS, with an exponent of approximately 1.62. We also identify the key role of the quantum decoherence effect, which suppresses unphysical overcoherent electron propagation and enables exponential population decay to the conduction band minimum. The electron relaxation time calculated by the real-time simulations further validates the theoretical prediction by the obtained power-law formula. These theoretical findings elucidate the intricate interplay of electronic transitions, electron-vibration couplings, and quantum decoherence in QDs, providing insights for further optimization of QD-based optoelectronic devices.

Exciton diffusion is crucial for various optoelectronic applications of organic semiconductors, yet the underlying mechanisms remain to be fully elucidated. We here focus on the Frenkel exciton and make a systematic large-scale nonadiabatic dynamics study of exciton diffusion. It is found that long-range interactions could enhance exciton diffusion if the nearest-neighbor exciton coupling is relatively weak compared with the exciton-phonon coupling strength. When the nearest-neighbor coupling becomes strong enough, however, we uncover a paradoxical suppression of exciton diffusion (PSED) by long-range interactions. In general, both the temperature and interaction range could simultaneously change the energy distribution and delocalization strength of the exciton. The competition between these two effects results in the complex dynamics of PSED due to long-range interactions. These findings have deepened our understanding of exciton diffusion, which may facilitate the rational design of organic materials for improving the energy conversion efficiency of solar cells.

In our recent work (J. Phys. Chem. Lett. 2023, 14, 7680), we utilized the exact quantum dynamics results as references and proposed a general machine learning method to obtain the optimal decoherence time formula for surface hopping simulation. Here, we extend this strategy from one-dimensional systems to the much more intricate scenarios with multiple nuclear dimensions. Different from the one-dimensional situation, an effective nuclear kinetic energy is defined by extracting the component of nuclear momenta along the non-adiabatic coupling vector. Combined with the energy difference between adiabatic states, high-order descriptor space can be generated by binary operations. Then the optimal decoherence time formula can be obtained by machine learning procedures based on the full quantum dynamics reference data. Although we only use the final channel populations in 24 scattering samples as training data for machine learning, the obtained optimal decoherence time formula can well reproduce the time evolution of the reduced and spatial distribution of population. As benchmarked in a large number of 56840 one- and two-dimensional samples, the optimal decoherence time formula shows exceptionally high and uniform performance when compared with all other available formulas.

All-solid-state sodium batteries (ASSSBs) with a working voltage of approximately 3.5 V hold great potential for safe, sustainable, and high-energy-density electrochemical energy storage. However, 3.5 V oxide-type cathodes (e.g., NaNi1/3Fe1/3Mn1/3O2) may suffer from interfacial contact loss with solid electrolytes due to their intrinsic rigidity, resulting in irreversible capacity degradation during cycling. Herein, we report a highly deformable chloride cathode, NaFeCl4, displaying Young's modulus of only 1.33 GPa and excellent structural reversibility. Benefiting from the soft lattice, the NaFeCl4 cathode maintains a crack-free morphology despite significant changes in structural units between tetrahedra [Fe3+Cl4] and octahedra [Fe2+Cl6] upon repeated Na+ insertion/extraction, achieving a high capacity retention of 84.4% over 500 cycles. Moreover, with only 5.2% of the cost of the NaNi1/3Fe1/3Mn1/3O2 and 3.7% of the cost of Na3V2(PO4)3 cathode, NaFeCl4 can deliver a working voltage of ∼3.45 V vs Na+/Na and energy density of ∼405 Wh kg-1. This chloride cathode offers new insight into solving the mechanical issues in solid-state systems, guiding future developments of low-cost, stable, and high-voltage cathodes for ASSSBs.

The framework of exact factorization (XF) has inspired a series of trajectory-based nonadiabatic dynamics methods through introducing different approximations. Recently, the coupled-trajectory surface hopping (CTSH) method has been proposed to combine the key advantages of the coupled-trajectory mixed quantum-classical method based on XF and the fewest switches surface hopping. We here present a novel variant of CTSH, namely sign-consistent CTSH (SC-CTSH), which considers proper trajectory clustering to reconstruct the nuclear density distribution and the consistency between wave function and active states to introduce decoherence. Using the exact quantum solutions as references, the high performance of SC-CTSH is benchmarked in the widely studied scattering models and compared with other related XF-based methods. Due to the incorporation of new trajectory clustering and sign consistency algorithms, SC-CTSH obtains more accurate quantum momentum and decoherence during the nonadiabatic dynamics, which makes the combination of XF and surface hopping more consistent and reliable. This study further highlights the significance of internal consistency between wave function and active states, which is important in the further development of mixed quantum-classical dynamics methods.

Being a numerically exact method for the simulation of dynamics in open quantum systems, the hierarchical equations of motion (HEOM) approach still suffers from the curse of dimensionality. In this study, we propose a novel multiconfigurational Ehrenfest (MCE)-HEOM method, which introduces the MCE ansatz to the second quantization formalism of HEOM. Here, the MCE equations of motion are derived from the time-dependent variational principle in a composed Hilbert-Liouville space, and each MCE coherent-state basis can be regarded as having an infinite hierarchical tier such that the truncation tier of auxiliary density operators in MCE-HEOM can also be considered to be infinite. As demonstrated in a series of representative spin-boson models, our MCE-HEOM significantly reduces the number of variational parameters and could efficiently handle the strong non-Markovian effect, which is difficult for conventional HEOM due to the requirement of a very deep truncation tier. MCE-HEOM is further applied to the 7-site Fenna-Matthews-Olson complex to study energy transfer in photosynthesis, and the results indicate that multi-site and multi-bath cases can also be accurately described with high efficiency. Compared to MCE, MCE-HEOM reduces the number of effective bath modes and circumvents the initial sampling for finite temperatures, eventually resulting in a significant reduction in computational cost.

The interplay between Frenkel (FE) excitons and charge-transfer (CT) states crucially impacts exciton transport in organic molecular aggregates. Using large-scale nonadiabatic surface hopping dynamics on Holstein-type Hamiltonians parametrized for realistic systems, we here show that exciton diffusion strongly depends on the FE-CT energy offset (ΔE) and the sign pattern of excitonic and electronic couplings. Hybridization at the bottom of the exciton band (H- and J+) promotes delocalized states with moderate CT character (30-50%), boosting diffusion coefficients by up to an order of magnitude. In contrast, hybridization at the top of the band (H+ and J-) leads to stronger localization and reduced transport. These trends persist even under strong vibronic coupling, where band-based descriptions fail, highlighting robust design principles for enhancing exciton mobility in organic materials.

The integration of both rigid and flexible components holds great potential to significantly enhance the overall performance of organic electronic devices. Non-covalent interactions are frequently harnessed to augment the planar conjugation of polymers, consequently elevating the rigidity of these polymers. However, the influence of the dihedral angle distortion between donor and acceptor units, which is induced by the flexibility inherent in donor-acceptor copolymers, on charge transport remains poorly understood. In this study, we systematically investigate intra-chain charge transport parameters and charge mobility for the 3,6-bis(thiophen-2-yl) diketopyrrolopyrrole (DPPT) conjugated with various donor moieties. Combining with density functional theory (DFT) and the Su-Schrieffer-Heeger (SSH) model, we find that when the non-covalent interactions between the donor and acceptor units are enhanced (as exemplified by DPPT-FT and DPPT-BO), the coupling between electrons and low-frequency vibrations is significantly suppressed. Simultaneously, the intra-chain electronic coupling increases owing to substantial orbital overlap. Surface hopping simulations are utilized to study the charge transport properties. For DPPT-T, DPPT-FT, and DPPT-BT, weaker molecular rigidity and disordered chain packing lead to thermally activated hopping transport (low electronic coupling and high reorganization energy). In contrast, the enhanced structural rigidity of DPPT-BO facilitates charge delocalization, leading to an initial improvement in carrier mobility under low-temperature conditions, and thermal fluctuation effects induce a band-like behavior at high temperature.

Generating large, nontrivial quantum chemistry test problems with known ground-state solutions remains a core challenge for benchmarking electronic structure methods. Inspired by planted-solution techniques from combinatorial optimization, we introduce four classes of Hamiltonians with embedded, retrievable ground states. These Hamiltonians mimic realistic electronic structure problems, support adjustable complexity, and are derived from reference systems. Crucially, their ground-state energies can be computed exactly, provided the construction parameters are known. To obscure this structure and control perceived complexity, we introduce techniques such as killer operators, balance operators, and random orbital rotations. We showcase this framework using examples based on homogeneous catalysts of industrial relevance and validate tunable difficulty through density matrix renormalization group convergence behavior. Beyond enabling scalable, ground-truth benchmark generation, our approach offers a controlled setting to explore the limitations of electronic structure methods and investigate how Hamiltonian structure influences ground state solution difficulty.