Browse Articles

Chirality transfer in lyotropic twist–bend nematics

Using molecular simulations and classical density functional theory, we study the liquid-crystalline phase behavior of a series of bent rod-like mesogens with a controlled degree of chirality introduced through a twist at the center of the particle. In the achiral limit, isotropic, uniaxial nematic, twist–bend nematic, and smectic phases form as the packing fraction increases. On introducing chirality, the symmetry between the right- and left-handed twist–bend phases is broken. The phase with the same-handedness as the particles quickly becomes overwhelmingly favored as the magnitude of the particle twist is increased, because the particles are then better able to follow the helical director field lines in the twist–bend phase and pack more efficiently. By contrast, the cholesteric phase is predicted to have the opposite handedness to that of the particle due to the relatively weakly twisted nature of the particles. That the cholesteric and twist–bend phases have opposite handedness illustrates the differences in the mechanisms of chirality transfer in the two phases. We also found that doping a system of achiral mesogens with a small fraction of chiral particles led to the selection of the twist–bend phase with the same chirality as the particle.

Photo-excited extracellular electron transfer of electroactive microorganism triggers RAFT polymerization

Abstract Living cell-triggered reversible addition-fragmentation chain-transfer (RAFT) polymerization is of great value for construction of living materials with diverse applications. However, microorganisms-activated polymerization without end-group heterogeneity is not yet established. Here, we develop an electroactive microorganism-triggered polymerization system using Shewanella oneidensis- secreted flavins (as electron shuttles) to directly reduce chain transfer agents (CTAs) to continuously generate radicals, thus initiating RAFT polymerization. This S. oneidensis -triggered polymerization integrates microbial extracellular electron transfer pathway and photoinduced electron transfer to reduce CTAs for continuous radical generation. We then genetically engineer S. oneidensis to enhance flavins biosynthesis and transport, accomplishing increased conversion ratio ( > 90%) of poly(N, N-dimethylacrylamide) with low polydispersity ( Ð  < 1.20). In addition, the S. oneidensis -triggered RAFT polymerization is effective for various monomers and CTAs, being able to synthesize diverse block copolymers. Synergistic integration of synthetic biology and RAFT polymerization provides a sustainable and controllable polymerization platform.

An AC voltage sensorless predictive current control method for grid-tied inverter with enhanced robustness against current DC offset

Understanding failures in electronic structure methods arising from the geometric phase effect

The geometric phase effect arises from the dependence on the nuclear coordinates in the electronic Hamiltonian, leading to sign changes of the electronic wave functions upon traversal of certain paths in nuclear configuration space. The geometric phase effect can have important consequences for the electronic structure problem, but this fact has largely gone unnoticed. We show how the geometric phase effect can significantly impact the accuracy of approximate electronic structure methods. In particular, we prove that for paths that enclose a conical intersection, any component of the wave function (such as an approximation to it) must vanish exactly, unless the associated conical intersections of the component and the wave function coincide. This has implications for methods that employ intermediate normalization, where the contribution along a reference wave function is fixed. We demonstrate numerically that the failure to account for the phase effect leads to asymptotic discontinuities in the wave function parameters. This results in breakdowns in coupled cluster methods or perturbation theories converging to excited states rather than the ground state. The global nature of the geometric phase effect means that these failures can span extended regions of nuclear configuration space, including regions far away from any conical intersection.

Unveiling a pervasive DNA adenine methylation regulatory network in the early-diverging fungus Rhizopus microsporus

A nitrogen deprivation gradient triggers transcriptional reprogramming for lipid biosynthesis in Auxenochlorella pyrenoidosa

Erratum: “Two packing pathways of Janus-like homopolymer-grafted nanoparticles at fluid–fluid interfaces” [J. Chem. Phys. 163, 134903 (2025)]

Operando microimaging of crystal structure and orientation in all components of all-solid-state-batteries

Integrated analysis of genotype by yield trait and genotype by environment interactions for selecting superior maize genotypes

New spectra of (HCl)3 and (HCl)4: Is the tetramer planar?

Spectra of HCl trimer and tetramer are studied in the H–Cl fundamental stretch region using a rapid-scan optical parametric oscillator source to probe a pulsed supersonic slit jet expansion. Compared to previous work on these weakly bound clusters, the effective rotational temperature in the jet (≈2.3 K) is much lower, resulting in reduced spectral congestion. For the trimer, this enables detection and assignment of all six isotopologue components of the degenerate perpendicular band around 2809 cm−1, and these new data result in significant changes in the resonant vibrational coupling parameters used to model isotopic effects. Very weak trimer “hot” bands are also observed. For the tetramer, a weak parallel band around 2790 cm−1 is observed and analyzed. Its presence suggests that the tetramer structure is (slightly) nonplanar, as predicted by modern ab initio calculations, and the validity of this conclusion is discussed. The much stronger perpendicular band of the tetramer around 2776 cm−1 has a considerable amount of partly resolved rotational structure, but it is lifetime-broadened (≈0.01 cm−1) and too congested to permit detailed analysis. Applying an expanded resonant vibrational coupling model, with input from the parallel band results, the overall shape of the perpendicular band is simulated with reasonable accuracy for two rotational temperatures, 2.3 and 13 K.

A meta-interactive neural network for solving time-varying quadratic programming problems

Abstract Many practical applications can be formulated as time-varying quadratic programming (TVQP) problems. Improving solution speed and accuracy can theoretically enhance efficiency. However, existing solvers such as the zeroing neural network (ZNN) and varying-parameter recurrent neural network (VPRNN) exhibit inherent limitations. Here, we propose a meta-interactive neural network (MINN). Unlike the independent neural structures in ZNN and VPRNN, the proposed MINN constructs a coupled topology for neurons, enabling information exchange within the network, and utilizing group dynamics to accelerate the convergence process. Notably, MINN relaxes the activation function constraints imposed by ZNN, allowing the use of non-monotonically increasing odd functions, thereby broadening the class of admissible activations. Lyapunov-based analysis confirms the enhanced convergence properties of MINN. Furthermore, numerical simulations demonstrate that MINN consistently outperforms ZNN and VPRNN in terms of convergence speed and robustness. Surprisingly, MINN also generalizes well to other time-varying problems, such as the Sylvester equation. Additionally, a detailed analysis of the coupling parameters reveals its critical role in system performance. Finally, applying MINN to robotic motion planning improves control accuracy from 10 −6 m to 10 −7 m.

AI-driven real-time responsive design of urban open spaces based on multi-modal sensing data fusion

A general molecular-scale dynamic memristor model based on non-steady-state charge transport kinetics and its information processing capability in reservoir computing

Non-steady-state molecular-scale dynamics, where fast electron transport couples with slow chemical state evolution, underpins the complex behaviors of molecular memristors, yet a general model linking these dynamics to neuromorphic computing remains elusive. We introduce a dynamic memristor model that integrates Landauer and Marcus electron transport theories with the kinetics of slow processes, such as proton/ion migration or conformational changes. This framework reproduces experimental conductance hysteresis and emulates synaptic functions such as short-term plasticity and spike-timing-dependent plasticity. By incorporating the model into a reservoir computing architecture, we show that computational performance optimizes when input frequency and bias mapping range align with the molecular system’s intrinsic kinetics. This chemistry-centric, bottom-up approach provides a theoretical foundation for molecular-scale neuromorphic computing, demonstrating how non-steady-state molecular-scale dynamics can drive information processing in the post-Moore era.

Origin of Earth’s hydrogen and carbon constrained by their core-mantle partitioning and bulk Earth abundance

A national growth mixture modeling analysis of county-level COVID-19 incidence rate trajectories and health inequities during three successive pandemic waves in 2020

Simulation of organic liquid and glass: Results for <i>ortho</i> -terphenyl (OTP) and curve fitting

Accurate organic forcefield calculations of the temperature-dependent volumetric behavior of ortho-terphenyl (OTP) have been undertaken and analysis of simulation results using different curve fitting methods conducted. The simulated liquid density of OTP is in excellent agreement with experimental measurements in the liquid region of the V(T) vs T curve. In the glass region, the simulated results are shown to be highly reproducible across independent simulations. In addition, results for the glass region show significant non-linearity as a function of temperature. A comparison of different means of analyzing a V(T) vs T curve is reported, with the incorporation of linear and quadratic terms preferred for both the glassy and liquid regions.

Strong yet superelastic ceramic aerogel enabled by synergistic soft-hard inter-nanowire nodes

The impact of physical activity on innovative behavior: a moderated mediation model

Effects of geometric parameters and wettability on pattern collapse in nanoscale systems

Pattern collapse during the drying process following wet cleaning in semiconductor manufacturing has emerged as a critical challenge, significantly impacting chip yield and device reliability. To better understand the nanoscale collapse mechanisms, we performed molecular dynamics simulations on isolated, parallel double cantilever nanopillars with varying high aspect ratios (ARs)—representative nanostructures in semiconductor processes. The results reveal that at the nanoscale, pattern collapse is driven by a complex interplay of Laplace pressure, surface tension, and interatomic interactions. For nanopillars with relatively low ARs, deflection remains minimal. However, near the critical AR, the restoring force sharply diminishes, causing a pronounced deflection surge and eventual pattern collapse. Wettability strongly affects drying dynamics, leading to two distinct modes. Under weak wettability, drying proceeds top–down. In contrast, strong wettability induces inside–out drying. Due to the significant influence of interatomic interactions at the nanoscale, the critical AR obtained from molecular dynamics simulations for different contact angles is slightly smaller than the theoretical predictions. Overall, this study reveals the drying mechanisms and the final collapse configurations at the microscopic scale, while providing a useful supplement to theoretical models in predicting the critical aspect ratio, thereby offering guidance for the design of micro/nano devices and their drying processes.

Reduced order modeling with shallow recurrent decoder networks