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High-quantum yields in [6]helicenes: Achieved by boosting radiative decay and suppressing intersystem crossing via BN/BO substitution
High-efficiency chiral luminescent materials exploration remains a central challenge in organic optoelectronics. Herein, we report a comprehensive investigation of the spectroscopic properties and fluorescence quantum yields (QY) of three [6]helicenes derivatives, CC[6], BN[6], and BO[6], with a focus on the effect of B–N and B–O bonds substitution. The results demonstrate that BN/BO substitution induces a systematic redshift in emission and CPL spectra, enhances radiative decay rates (kr) by over 20-fold, and significantly suppresses internal conversion (kIC). Although intersystem crossing (kISC) remains the dominant non-radiative pathway, the net effect significantly enhances fluorescence QY, following the trend BO[6] (0.45) > BN[6] (0.34) > CC[6] (0.11). Mechanistic analysis reveals that the superior performance of BO[6] originates from an optimal balance between high kr and relatively weaker ISC. This study not only establishes BN/BO substitution as an effective strategy but also identifies the theoretically designed BO[6] as an optimal candidate, thus providing clear design principles for developing high-performance helicene-based fluorescent materials.
Modeling protonated helium clusters across the size-resolved to the droplet regimes: Structure and low-energy collision dynamics
A many-body polarizable potential is developed to model HenH+ clusters in their electronic ground state across a broad size range, trained to reproduce quantum chemical CCSD(T) calculations with a basis set of quadruple zeta quality. Putative global minima of small clusters containing up to n = 50 helium atoms exhibit a rigid HeH+He trimer core, around which additional atoms arrange into icosahedral-like motifs. The binding energy inferred from path-integral molecular dynamics simulations displays successive changes in its slope at n > 2, n > 6, and n > 13, and vibrational delocalization, as measured from the inherent structure entropy, is found to be significant already at small sizes. In large clusters, the trimer core is preserved and a much softer second solvation shell of ∼20 atoms is identified. The collision dynamics of a proton impinging on a 1000-atom helium droplet was simulated using ring-polymer molecular dynamics for various conditions and moderate energies in the eV range. Soft capture is found to take place for collision energies of ∼1 eV and below, while 10 eV collisions have the proton piercing through the droplet before being possibly captured back after losing sufficient energy. The resulting sticking cross sections generally follow the predictions of a simple Langevin capture model, extended to account for the finite radius of the helium target, except in the piercing regime. In the low collision energy limit, the sinking of an initial hydrogen atom after sudden ionization is found to be very slow once the trimer core is formed within 2 ps.
Verification of kinetic model for liquid molecule transport within adsorption layers on solid surfaces via molecular dynamics simulation
In the manufacturing process of semiconductor devices, wet processes such as cleaning and chemical treatment on surfaces with nanoscale fine structures play a critical role. The mass transport within nanoscale structures exhibits properties different from those of bulk liquids, owing to the influence of layered adsorption structures of liquid molecules formed near solid–liquid interfaces. In this study, we interpreted transport phenomena near solid–liquid interfaces as successive hopping motions between adsorption layers (adsorption and desorption events) and expressed their frequency using rate constants. Furthermore, we developed a theoretical model to quantitatively predict these rate constants based on the Arrhenius equation and transition state theory (TST). To validate the constructed theoretical model, molecular dynamics (MD) simulations were performed for two representative systems: a simple model consisting of Pt as the solid wall and Ar as the liquid molecule, and a more realistic system with SiO2 and H2O. The results showed that the initial desorption from the adsorption layer can be well described by the theoretical model, whereas subsequent desorption proceeds more slowly than predicted. The observed discrepancy between the theoretical model and the simulations was attributed to the breakdown of the quasi-equilibrium assumption in TST for the molecules remaining in the adsorption layer. To interpret this mismatch, we proposed a conceptual model that focuses on molecular recrossing events at the adsorption-layer boundary. It is expected to provide useful guidance for future modeling of transport phenomena near solid surfaces.
Approximation of forces and torques from anisotropic pairwise interactions using multivariate polynomials
The dynamics of anisotropic particles are dictated by forces and torques that can be challenging to mathematically represent in computer simulations. Several data-driven approaches have been developed to approximate these interactions, but they often rely on having large amounts of training data that may be practically difficult to generate. Here, we extend a framework we recently developed for approximating anisotropic pair potentials to the approximation of pairwise forces and torques. The framework uses multivariate polynomials and physics-motivated coordinate transformations to produce accurate approximations using limited amounts of data. We first derive expressions relating the force and torque to partial derivatives of the approximated potential energy with respect to the transformed coordinates used to represent the particle configuration. We then explore several options for approximating the same pairwise interactions from measurements of the forces and torques, and we critically assess their accuracy using model two- and three-dimensional shape-anisotropic nanoparticles as test cases. We find that interpolation of the pairwise potential energy produces the best result when it is known, but force and torque matching (regression) is a viable strategy when only the force and torque are available.
Quantitative description of protein configuration and viscoelasticity using first-principles hydrodynamics applied to quartz crystal microbalance experiments
The quartz crystal microbalance (QCM) is one of the few label-free techniques capable of sampling the response of proteins and their aggregates. However, QCM signals come encrypted by a complicated interaction between the biomolecular viscoelastic response and their hydrodynamic perturbations. This has hampered the quantitative interpretation of QCM signals of biomolecules. In addition, the large size disparity between proteins and the QCM flow penetration length of 100 nm creates a deadlock for standard simulation packages. Using first-principles modeling and adaptive schemes, we show that the ultrasensitive QCM sensor can be upgraded to a high-precision quantitative tool for protein analysis. We present a “Virtual-QCM” (VQCM) framework to introduce viscoelastic structures in a hydrodynamic solver for semi-infinite wall-bounded oscillatory flow. The fluid solver [R. P. Peláez, P. Palacios-Alonso, and R. Delgado-Buscalioni, J. Fluid Mech. 1010, A57 (2025)] is spectral in time and space and implements open boundaries focusing on the relevant fluid layer around proteins with ∼104 speed-up. Biomolecules are modeled as viscoelastic networks connected to the atomistic level via coarse-graining theory. Integrating VQCM with experiments allows us to predict the physicochemical properties of FtsZ and ZipA; bacterial proteins with intrinsically disordered regions (IDRs) tethered to lipid membrane substrates. Quantitative match with experiments at all coverages permits us to measure substrate binding affinities, IDR extension ℓ, stiffness k, and intrinsic friction ξ. We find the polypeptide chains to be extremely sensitive to the buffer ionic strength, with protein friction affected by Mg+2. Measured intrinsic relaxation times ξ/k ∼ [3–30] ns are consistent with FRET analyses. Access to microscopic information using standard QCM sensors will help decipher the IDR structure–function and other protein aggregates.
Molecular simulation study of penetrant diffusion in vitrimer networks
The diffusivity of penetrants in polymer networks can be tailored by network topology, which is relevant to applications such as chemical separation membranes or the design of barrier coatings. Recent studies on permanent polymer networks have revealed how cross-linking affects both segmental relaxation and the entropic mesh confinement, and consequently, both physical phenomena affect penetrant diffusive dynamics. We build on this finding and investigate how penetrant diffusion occurs in vitrimers, materials with the same network topology as permanent networks but capable of topological rearrangement via bond exchange reactions. The structural relaxation of vitrimer networks is influenced by the kinetics of these bond exchange reactions. We employ molecular dynamics simulations to investigate how dynamic network rearrangement affects penetrant diffusion for various penetrant sizes, temperatures, vitrimer cross-link densities, and bond exchange rates. Our studies show that the diffusivity of small penetrants is largely unaffected by varying bond exchange rates; however, as the penetrant size increases, faster bond exchange rearrangements lead to enhanced diffusivity. Notably, this enhancement cannot be fully accounted for by changes in penetrant alpha hopping times, suggesting that bond exchange kinetics primarily affect the mesh confinement of penetrant diffusion in vitrimers.
Chiral discrimination on gate-based quantum computers
We present a novel approach to chiral discrimination using gate-based quantum processors, addressing a key challenge in adapting conventional control techniques using modern quantum computing. Schemes such as stimulated rapid adiabatic passage and shortcuts to adiabaticity have shown strong potential for enantiomer discrimination; however, their reliance on analog and continuous-time control makes them incompatible with digital gate-based quantum computing architectures. Here, we adapt these protocols for quantum computers by discretizing their Gaussian-shaped pulses through Trotterization. We simulate the chiral molecule 1,2-propanediol and experimentally validate this gate-based implementation on IBM quantum hardware. Our results demonstrate that this approach is a viable foundation for advancing chiral discrimination protocols, preparing the way for quantum-level manipulation of molecular chirality on accessible quantum architectures.
Effect of on-site correlation on the structure, stability, and magnetic properties of (FeCl2)3 trimer
In a recent experiment, Kresin and co-workers, in addition to validating an earlier theoretical prediction by Pradhan and Jena that the Fe atoms in the (FeCl2)2 dimer are coupled antiferromagnetically, found that the magnetic moment of the (FeCl2)3 trimer is same as that of its monomer, namely, 4 μB. This is in contrast to the FeCl2 monolayer where the coupling between the Fe atoms is ferromagnetic. Calculations using density functional theory showed that the ground state of the trimer is ferromagnetic with a total magnetic moment of 12 μB and its structure mimics that of the H-phase of the monolayer. Molecular dynamics simulations showed that the ferromagnetic isomer is unable to overcome an energy barrier at liquid helium temperature. However, when on-site correlation was included, which was earlier found to be unimportant for the magnetic configuration of the (FeCl2)2 dimer, the ground state geometry of the trimer assumed linear chain geometry, sharply different from what would be expected from the H- or T-phases of its monolayer. Interestingly, the preferred magnetic moment of the chain-like trimer is found to be 4 μB, in agreement with experiment. These results demonstrate the importance of including on-site correlation in each calculation involving transition metals. The intricate relationship between structure and magnetic properties of clusters can be used to tailor metastable materials that nature does not prefer.
Non-ideal two-dimensional electronic spectroscopy: Theory for a transparent nonlinear system
The necessary requirement for an ideal two-dimensional electronic spectroscopy experiment is utilization of ultrashort optical pulses with rectangular spectra for pulse envelopes, while the system transitions fall within the optical pulse window. In this case, the obtained spectra shows clear resonances of the sample response function and various quantum transitions are mapped onto the two-dimensional spectra without distortions. Such conditions, however, are not realistic: first, the pulses never have such spectral profile; second, there may be many transitions that are away from the optical window. In this paper, we present general practical expressions for simulating two-dimensional electronic spectroscopy measurements with specific pulse spectral profiles, and we demonstrate that the off-resonant transitions may have large contributions to the spectra especially at short delay times, when pulse overlaps are significant.
Theoretical quantum design of pump-laser pulses for generating helical photon-dressed states
Controlling the unidirectional rotation of π-electrons is a key challenge in the development of organic electronic and optoelectronic devices. In our recent study [Mineo et al., J. Chem. Phys. 161, 194311 (2024)], we explored the generation of unidirectional π-electron rotations in both low- and high-symmetry molecules by utilizing helical photon-dressed states. These states were formed using circularly or elliptically polarized laser fields within a minimal three-state electronic model under the frozen-nuclei approximation. However, that approach did not address the preparation of appropriate initial conditions or the tailored light–matter interactions required to create photon-dressed states. To overcome this limitation, it is crucial to consider a process that prepares the photon-dressed states from the electronic ground state through optical pumping with pulsed lasers. In this work, we analytically design such pulsed lasers to induce helical photon-dressed states in both low- and high-symmetry aromatic rings, starting from the ground state. We further incorporate the nuclear vibrational effects within the adiabatic approximation and apply those designed laser fields to low-symmetry aromatic rings. Finally, we numerically demonstrate the generation of angular momenta associated with the photon-dressed states using the analytically designed laser fields. Vibrational effects are found to selectively influence the stability of specific photon-dressed states.
Two-mode Floquet fewest switches surface hopping for nonadiabatic dynamics driven by two-frequency laser fields
Two-frequency (two-color) laser fields provide a powerful and flexible means for steering molecular dynamics. However, quantitatively reliable and scalable theoretical tools for simulating laser-driven nonadiabatic processes under such fields remain limited. Here, we develop a two-mode Floquet fewest switches surface hopping (two-mode F-FSSH) approach for two-frequency driving within a mixed quantum–classical framework. We validate the algorithm on three driven one-dimensional two-state models: a Rabi model and two avoided-crossing scattering models. The electronic and nuclear dynamics are benchmarked against numerically exact results from split-operator calculations, showing good agreement across a broad range of initial conditions and field parameters. These results establish two-mode F-FSSH as a practical framework for designing and simulating two-frequency control protocols and motivate extensions to more realistic systems.
Neutral barium in solid neon: Optical spectroscopy and first excited state lifetime
Matrix isolation spectroscopy enables probing atomic properties in controlled cryogenic environments. Here, we present a spectroscopic study on neutral barium atoms embedded in a neon cryogenic crystal at 6.8 K, extending previous investigations performed in other noble gas hosts. The visible and near-infrared emission spectra were recorded under two different laser excitation schemes. First, 10-ns laser pulses at 355 nm were used to directly excite high-lying energy levels of barium, enabling the observation of fluorescence cascades. Second, a tunable continuous-wave laser operating between 700 and 900 nm allowed us to determine the matrix-induced shifts of barium energy levels relative to their vacuum values, as well as the inhomogeneous linewidths of the observed transitions, and to perform lifetime measurements. Our results confirm multiple radiative pathways and matrix-induced relaxation channels affecting the 5d6s and 6s6p barium manifolds. Furthermore, we present the first lifetime measurement of the barium 5d6s 3D1 state in a neon crystal, yielding 0.39 ± 0.02 s, with a predicted increase of about 10% at 2 K. This study of fluorescence and spectroscopic properties of barium isolated in neon represents an important step toward future searches for the electron electric dipole moment using barium monofluoride in neon matrices, where neutral barium atoms may act as unavoidable impurities and potential sources of background and systematic limitations.
Super-Arrhenius dynamic slowdown revealed by slow variable modulation in the fragile supercooled liquid
The super-Arrhenius dynamic slowdown in fragile supercooled liquids remains one of the central unresolved questions in condensed matter physics. In this study, we analyze particle jump dynamics in a prototypical fragile glass-forming liquid, the Kob–Andersen Lennard-Jones (KALJ) model. Using the displacement of jumping particles as the reaction coordinate, we demonstrate the emergence of non-Poissonian dynamics as the temperature decreases. In the mildly supercooled regime, the outer region of the first coordination shell of a jumping particle exhibits a significant distribution shift during the jump motion. By comparing the survival probability with its slow-fluctuation limit using this distribution as a slow variable, we confirm that particles in this region modulate the jump dynamics, enhance the jump rate fluctuations, and thereby induce the dynamic slowdown as supercooling proceeds. As the temperature decreases, this behavior extends to the outer regions of the second coordination shell and beyond, intensifying the dynamic slowdown. This spatial growth of the slow variables responsible for dynamic disorder exhibits close correspondence with an increase in the static correlation length. These results provide a microscopic mechanism for the super-Arrhenius dynamic slowdown in the KALJ model.
Statistics of thermal avalanches in driven amorphous systems
Within the framework of the random first-order transition theory of glasses, we discuss the statistics of “thermal avalanches,” the large scale rearrangements in driven amorphous systems near their instability. Stringy excitations yield non-Poisson waiting-time statistics. Embedding these statistics in a generalized master equation captures the non-Markovian, aging dynamics of avalanche clusters. We apply this framework to analyze nonequilibrium signatures of thermal avalanches—auto-correlation functions and effective temperatures—under both quasi-static shear and stochastic shaking protocols. We use full counting statistics to derive the complete distribution of both the avalanche magnitudes and avalanche counts, uncovering the intermediate-time behavior.
Thermal and chemical control of emission and excited-state dynamics in non-(TMS)3P-derived InP quantum dots
Here, we present a systematic study of how reaction temperature and indium halide precursor chemistry govern the optical properties of colloidal indium phosphide quantum dots (InP QDs), enabling emission tuning across the visible spectrum (∼530–660 nm) for quantum dot light-emitting diode (QLED) applications. InP QDs were synthesized over a temperature range of 160–300 °C using InHal3 (Hal = Cl, Br, I) as the indium source and tris(diethylamino)phosphine [(DEA)3P] as a non-pyrophoric phosphorus precursor. Across all halides, increasing reaction temperature produces a near-linear red shift in photoluminescence between 180 and 280 °C, with this behavior breaking down at higher temperatures. The extent of wavelength tunability follows the order InCl3 > InBr3 > InI3, with InCl3-derived QDs additionally exhibiting improved monodispersity and reduced photoluminescence quantum yield degradation upon film formation. Optical and structural properties were characterized using photoluminescence and electroluminescence spectroscopy and transmission electron microscopy, alongside systematic evaluation of drop-cast thin films. QLEDs fabricated from QDs of comparable emission wavelength exhibit external quantum efficiencies of 0.05%–0.09%, with devices based on InCl3-derived QDs delivering the highest efficiencies. The absence of a monotonic trend in device performance with halide molecular weight suggests a non-linear relationship between precursor chemistry, excited-state dynamics, and electroluminescent efficiency. Although these efficiencies remain lower than those achieved using (TMS)3P-derived InP QDs, this study demonstrates the viability of environmentally benign aminophosphine-based synthetic routes and highlights the need for device architectures specifically optimized for non-(TMS)3P-derived InP QDs.
Vibrational spectral signature of water to probe the mystery of urea aggregation and validation of force fields
Urea is a widely used protein denaturant; however, the potential of urea to form self-assembled structures at higher concentrations and the influence of its self-interactions on water structure and dynamics remain elusive. This open question demands tracking of molecular-level rearrangements. In this work, we explore the influence of urea on water’s local structure and dynamics and relate it to urea self-association. We correlate the vibrational spectral response and orientational dynamics of water with concentration-dependent self-association of urea by examining the interface surface area, hydrogen bond strength, and population of relevant donor–acceptor pairs. We compare the response of four urea force fields (KBFF, OPLS-S, OPLS-AA-D, and GAFF-D3) with SPC/E water. The KBFF–SPC/E pair best reproduces the experimental IR spectra. Both variants of the Duffy model (OPLS-S and OPLS-AA-D) show blue shifts with reasonable broadening and strong concentration-dependent responses, while GAFF-D3 shows random peak shifts with prominent broadening. Regarding urea self-aggregation, KBFF is mildly repulsive, Duffy models are attractive, and GAFF-D3 is neutral with high variability. Only the KBFF–SPC/E pair captures the expected deceleration in water-orientational dynamics. We conclude that urea does not self-aggregate significantly in water, even at higher concentrations; urea aggregation, when present, arises from the accumulation of weak, short-lived contacts rather than from strong pairwise association. KBFF emerges as the most reliable classical non-polarizable model of urea for capturing both structural and dynamic properties of water.
Formal <i>O</i> ( <i>N</i> 3) scaling <i>GW</i> calculations by block tensor decomposition for large molecule systems
Within the framework of many-body perturbation theory based on Green’s functions, the GW approximation has emerged as a pivotal method for computing quasiparticle energies and excitation spectra. However, its high computational cost and steep scaling present significant challenges for applications to large molecular systems. In this work, we extend the block tensor decomposition (BTD) algorithm, recently developed in our previous work [Zhang et al., J. Chem. Phys. 163, 174109 (2025)] for low-rank tensor compression, to enable a formally O(N3)-scaling GW algorithm. By integrating BTD with an imaginary-time GW formalism and introducing a real space screening strategy for the polarizability, we achieve an observed scaling of approximately O(N2) in test systems. Key parameters of the algorithm are optimized on the S66 dataset using the JADE algorithm, ensuring a balanced compromise between accuracy and efficiency. Our BTD-based random phase approximation also exhibits O(N2) scaling, and eigenvalue-self-consistent GW calculations become feasible for systems with over 3000 basis functions. This work establishes BTD as an efficient and scalable approach for large-scale GW calculations in molecular systems.
Dynamics of low-temperature water are driven by electrostatics
Non-Gaussian dynamics in low-temperature liquids are assigned to spatial fluctuations of relaxation times and linear transport coefficients (dynamic heterogeneity). In contrast, molecular dynamics simulations of SPC/E water assign non-Gaussian dynamics to electrostatic intermolecular interactions growing in prominence with lowering temperature. Translational non-Gaussian parameters and rotational/translational relaxation times follow master curves produced by either changing temperature or the liquid’s dipole moment. Static and dynamic compensation relations found for bulk water are assigned to the separation of time scales between density and electrostatic fluctuations.
Decoupling thermo-mechanical signals in ionic hydrogels via deep operator networks
In responsive hydrogels, concurrent thermal and mechanical stimuli induce inseparable electrical signals due to the superposition of the ionic thermoelectric and piezoionic effects, a fundamental challenge in soft ionotronics. To address this, we propose the T-DeepONet model, which integrates the superior temporal modeling capability of the transformer with the spatial encoding of the deep operator network (DeepONet) to learn the complex thermo-mechanical operator. The model is trained on a comprehensive synthetic dataset generated from experimentally validated finite element simulations, enabling T-DeepONet to map the coupled voltage fields to independent temperature and pressure distributions. By integrating transformer-based temporal modeling with DeepONet’s spatial encoding, T-DeepONet resolves the distinct spatiotemporal signatures of thermal diffusion and mechanical transients, achieving 98.2% R2 accuracy across synchronous and asynchronous loading scenarios with ∼100 ms inference latency. This work establishes a general framework for real-time, field-level disentanglement in multiphysics soft matter systems, opening avenues for high-fidelity tactile perception in soft robotics and bridging advances in nonequilibrium ion transport with operator learning.
Efficient computational modeling of Raman spectra of liquids and solutions
An efficient approach for an accurate quantum mechanical (QM) modeling of Raman spectra of condensed-phase systems is described. Energetically low-lying cluster structures of a molecule surrounded by an explicit shell of solvating molecules are efficiently generated at the semi-empirical tight-binding QM level and then re-optimized at the Density Functional Theory (DFT) level of theory. Such cluster models of a solvated molecule are shown to be sufficient to reproduce experimental vibrational frequencies and relative Raman intensities of several hydrogen-bonded liquids and aqueous solutions with the use of B3LYP-D3/def2-TZVP, ωB97X-3c, or B97-3c DFT methods in harmonic simulations, provided that the first solvation shell is included in the model. Analogous simulations at the computationally less demanding PBE-D3/def2-TZVP level provided less good, but still reasonably accurate, results. With the examples of acetone, acetonitrile, benzene, and their deuterated analogs, and the ionic liquid 1,3-dimethylimidazolium tetrafluoroborate, it is demonstrated that Raman spectra of liquids, where pronounced hydrogen bonds are absent, can be obtained in the gas-phase approximation. A comparison of absolute Raman intensities measured for gaseous and liquid acetone, acetonitrile, and benzene with our cluster simulations suggests that the inclusion of more than the first solvation shell is needed to reproduce the observed increase in Raman scattering cross sections in liquids relative to gases.