Browse Articles

Upper-state-assisted uphill energy transfer in a far-red light-harvesting antenna from an Antarctic alga

Photosynthetic organisms thrive across remarkably diverse light environments, from dim, spectrally filtered habitats to high-irradiance niches. Their antenna complexes have evolved structural and excitonic features that tailor energy capture and delivery to local conditions, making comparative studies of noncanonical antennas essential for understanding the diversity of evolved designs. Here, we investigate the far-red light-harvesting complex from an Antarctic alga, Prasiola crispa (Pc-frLHC), whose ring-shaped undecameric (11-subunit) antenna absorbs strongly near ∼710 nm yet still drives photosystem II. Using femtosecond transient absorption with selective excitation of chlorophyll (Chl) b (645 nm), Chl a (675 nm), and far-red Chls (740 nm), we resolve a rapid, directional energy transfer cascade that funnels population into the lowest excitonic level of the far-red Chl trimer. Transient absorption anisotropy directly resolves a characteristic hopping time between the far-red Chl trimers of ∼11.5 ps, while exciton–exciton annihilation kinetics under increased fluence at far-red excitation provide independent corroboration. Spectral dynamics and anisotropy further reveal the existence of a higher-lying excitonic state near ∼670 nm within the far-red Chls. Thermal access to this ∼670 nm state enables repeated cycling that facilitates the uphill transfer toward Chl a despite a sizable energy gap of ∼580 cm−1. These findings clarify how Pc-frLHC exploits the excitonic coupling and the ring-mediated transport to harvest redshifted light for photosystem II excitation, offering general principles for engineering photofunctional systems adapted to spectrally limited environments.

Introduction to modeling radical pair quantum spin dynamics with tensor networks

Radical pairs are short-lived, spin-correlated intermediates that underpin processes in chemistry, biology, and emerging quantum technologies. Their behavior is governed by coupled electron-nuclear spin dynamics and is sensitive to weak magnetic fields, but full quantum treatments have been obstructed by the extreme computational cost of modeling many interacting spins. Here, this barrier is removed, demonstrating that open-system radical-pair dynamics can be resolved at nuclear-spin scales previously intractable, explicitly reaching regimes with tens of coupled nuclei and validated up to 60 spins. In biologically relevant flavin-tryptophan radical pairs, electron-transfer pathways and magnetic-field anisotropy are found to reshape spin evolution and, in turn, spin-selective reaction yields. The resulting directional responses expose a strong mechanistic link between the nuclear environment, magnetic geometry, and chemical outcome—a relationship central to hypotheses of avian magnetoreception and other magnetic-field effects in biology. This establishes a widely applicable simulation framework that removes a long-standing barrier in spin chemistry, quantum biology, and spin-based device science.

Ground and low-lying excited state potential energy surfaces of diiodomethane in four dimensions

We report a set of adiabatic potential energy surfaces (PESs) for diiodomethane, including the ground electronic state and all excited states accessible via single-photon absorption near 260 nm. Although constrained to four dimensions, these PESs capture the essential photochemical processes following photoexcitation—namely, bond breaking and rearrangement among the methyl radical and the two iodine atoms. Constructed using an accurate and efficient spline interpolation algorithm, the PESs reproduce local features with high fidelity and exhibit overall smooth first-order derivatives, making them suitable for molecular dynamics simulations. We identify key stationary points on the ground-state PES and on three excited-state PESs, and map reaction pathways leading to CH2I + I dissociation via the intermediate formation of a CH2I–I isomer. These PESs provide a valuable resource for molecular dynamics studies, enabling detailed exploration of photochemistry in diiodomethane.

Confinement-induced ultrafast conductivity in 2D perovskites resolved by correlative terahertz–NIR spectroscopy

Quantum wells made of quasi two-dimensional organic–inorganic hybrid perovskites (2D-PKs) offer a high degree of flexibility in tailoring optoelectronic properties through carrier confinement and functional interlayers. Compared to their 3D counterparts, 2D-PKs exhibit tunable photoluminescence, excitonic binding at room temperature, and enhanced structural stability. However, the dynamics of photoinduced charge carriers and their transport properties are highly intertwined due to the interplay of diverse excitation species, charge carrier cooling, transport, and radiative and non-radiative recombination. In this study, we employ optical-pump terahertz-probe spectroscopy (OPTP) to analyze the local conductivity dynamics of 2D-PK (n = 5) 2-(9H-carbazol-9-yl)ethan-1-ammonium [(MA)5(CzEA)2(PbI3)5] and 3D-MAPI methylammonium lead iodide (MeNH3PbI3) perovskites on picosecond timescales. Remarkably, we observe an intensity-dependent, 2D-specific buildup of an ultrafast, few-picosecond decay in local THz-conductivity. By combining OPTP with transient absorption and picosecond time-resolved photoluminescence (tr-PL), we correlate photoconductivity and carrier population. Thus, we can attribute the 2D-specific ultrafast THz response to delayed hot-carrier cooling and subsequent exciton formation, which effectively reduces the free-carrier conductivity. This intensity-dependent, ultrafast THz response appears as a signature of the recently identified hot-carrier bottleneck in bulk perovskites, and this effect manifests itself in a unique form in the 2D material. These results encourage further investigations on the impact of functional organic interlayers and provide insights into designing tunable carrier responses for ultrafast devices via adapted heterostructures and confinements.

Gas separation with binary-cooperative heterogeneous membranes

Capillary fluctuation method applied to moving solid–liquid interfaces: Temperature dependence of interfacial properties in pure aluminum

Understanding the solid–liquid interfacial thermodynamics of pure metals under undercooled conditions is essential for predicting microstructure evolution, yet quantitative data on the temperature dependence of interfacial free energy and its anisotropy remain limited. In this study, we extend the capillary fluctuation method (CFM) to moving solid–liquid interfaces obtained from molecular dynamics simulations of solidification in undercooled pure Al. By tracking the instantaneous interface position during steady-state migration and analyzing the fluctuation spectra of the interface height, the average interfacial free energy γ0 and the anisotropy strengths ϵ1 and ϵ2 were determined as functions of temperature. The fluctuation spectra retained a characteristic k−2 dependence even for moving interfaces, demonstrating that the CFM is applicable under non-equilibrium solidification conditions. The results show that γ0 tends to increase with decreasing temperature near the melting point, consistent with theoretical expectations and previous computational studies. The anisotropy parameters exhibit only weak temperature dependence: ϵ1 remains nearly constant over the investigated temperature range, whereas ϵ2 tends to decrease toward zero with increasing undercooling. These trends indicate that the anisotropy of the interfacial free energy at high undercoolings is primarily governed by ϵ1.

Computation and resource efficient genome-wide association analysis for large-scale imaging studies

Exploiting the path-integral radius of gyration in open quantum dynamics

A major challenge in open quantum dynamics is the inclusion of Matsubara-decay terms in the memory kernel, which arise from the quantum-Boltzmann delocalization of the bath modes. This delocalization can be quantified by the radius of gyration squared R2(ω) of the imaginary-time Feynman paths of the bath modes as a function of the frequency ω. In a hierarchical equations of motion (HEOM) calculation with a Debye–Drude spectral density, R2(ω) is the only quantity that is treated approximately (assuming convergence with respect to hierarchy depth). Here, we show that the well-known Ishizaki–Tanimura correction is equivalent to separating smooth from “Brownian” contributions to R2(ω) and that modifying the correction leads to a more efficient HEOM in the case of fast baths. We also develop a simple “A4” adaptation of the “AAA” (adaptive Antoulas–Anderson) algorithm in order to fit R2(ω) to a sum over poles, which results in an extremely efficient implementation of the standard HEOM method at low temperatures.

Targeting leucine-rich repeat kinase 2 overcomes resistance to oncolytic herpes simplex virus-based therapies in glioblastoma

Windmilling clusters of active quadrupoles

Active matter has thrived in recent years, driven both by the insight that it underlies fundamental processes in nature and by its vast potential for applications. This allows for innovation, both inspired by experimental observations and by the construction of novel systems with desired properties. In this paper, we develop a novel system in the search for a new kind of pattern formation: microstructural motifs with orthogonal alignment. Taking a simple active Brownian particle model applied to dumbbell-shaped particles, we add a quadrupolar interaction by positioning two antiparallel magnetic dipolar moments on each particle. We find that the phase behavior is determined by the competition between active motion and the orthogonal alignment favored by quadrupolar attraction. By varying these quantities, we are able to tune both the internal structure of the aggregates and find a surprising stability of triangular aggregates, to the point of clusters of size N = 3 being strongly overrepresented. Although none of the component particles are chiral, the resulting structures spin in a random, fixed direction due to the combination of the polarity of the active motion. This results in an ensemble of windmilling (randomly spinning in a circular motion) aggregates with windmill-like shapes (due to the three or four core component dumbbells). Ultimately, this simple model shows an interesting range of microstructural motifs, with great potential for experimental implementations.

Template-directed vertical photopolymerization for construction of triphenylamine-based poly(diacetylene) nanofibers

Abstract Template-directed synthesis of macromolecules prevails in natural systems. However, artificial template-directed covalent polymerization that proceeds without sacrificing the delicate non-covalent order needed for precursor alignment remains a formidable challenge. Here we report a supramolecular-templating strategy for photopolymerization of triphenylamine-based diyne assemblies. Cooperative hydrogen- and halogen-bonding align C 3 -symmetric monomers into ordered stacks that evolve from nanodots into micron-scale nanofibers. Ultraviolet irradiation then triggers axial cross-linking of the diyne moieties, producing continuous one-dimensional conjugated polymers. Selective acid treatment cleaves the I···N halogen bond to remove the template while preserving nanofibrillar integrity, yielding a stable covalent network with red-shifted emission. We demonstrate that this self-assemble-then-cure strategy integrates reversible supramolecular organization with irreversible covalent fixation, providing a general and scalable route to vertically oriented conjugated polymer architectures.

Configurational entropy of randomly double-folding ring polymers

Topologically constrained genome-like polymers often double-fold into tree-like configurations. Here, we calculate the exact number of tightly double-folded configurations available to a ring polymer in ideal conditions. For this purpose, we introduce a scheme that allows us to define a “code” specifying how a ring wraps a randomly branching tree and calculate the number of admissible wrapping codes via a variant of Bertrand’s ballot theorem. As a validation, we demonstrate that data from Monte Carlo simulations of an elastic lattice model of non-interacting tightly double-folded rings with controlled branching activity are in excellent agreement with exact expressions for branch-node and tree size statistics that can be derived from our expression for the ring entropy.

Polyanion-stabilized amorphous halide electrolytes with low lithium content for all-solid-state lithium batteries

Low-lying excited correlated electronic states of cycloparaphenylene and cyclacene: An efficient symmetrized density matrix renormalization group study with periodic boundary condition

One-dimensional and quasi-one-dimensional correlated fermionic models can be studied efficiently using the Density Matrix Renormalization Group (DMRG) method with open boundary conditions. Although the implementation of the conventional DMRG technique in investigating a fermionic model with a periodic boundary condition (PBC) is still challenging due to the demand of high computational facility, this work reports the efficient use of the symmetrized DMRG (SDMRG) technique in studying the low-lying correlated excited-states of radially π-conjugated cycloparaphenylene ([6]CPP) and [n]cyclacene molecules within the Pariser–Parr–Pople (PPP) model Hamiltonian with adequate computational cost. The low-lying correlated singlet excited energies of [6]CPP calculated within the PPP model are in very good agreement with experiment. Compared to [6]CPP, the numerical accuracy of DMRG calculations for highly correlated [n]cyclacene depends on the number of DMEV basis (m). Such a study shows an efficient pathway to implement the SDMRG technique in studying fermionic systems with PBC in the future.

Asymmetric synthesis of Heteroatom-bridged [3.2.1]Octane scaffolds via enantioselective β-H elimination reaction

Corresponding orbitals in periodic frozen-density embedding: The case of alkaline-earth subnitrides, <i>Ae</i> 2N, by the example of Ba2N

The metallic metal-rich phase Ba2N, a representative example for the Ae2N alkaline-earth subnitrides, is examined using theoretical methods to investigate its electronic structure and chemical bonding, with a special focus on the “excess” electron found within these structures, alluding to an electride character. To quantify the latter phenomenon, the “corresponding orbital” formalism, introduced by Neese to the molecular quantum chemists about two decades ago [F. Neese, J. Phys. Chem. Solids 65, 781 (2004)], is adapted to the recently developed periodic frozen-density approach [M. Pauls et al., J. Phys. Chem. A 127, 6541 (2023)]. While the existence of Ba2N goes back to both constructive Ba-6s–N-2sp orbital interference (covalency) and significant ionic bonding, we identify that the “excess” electron engaged in a singlet ground state of the presumably non-paramagnetic phase contributes to intra-layer Ba–Ba bonding while destabilizing the inter-layer Ba–Ba bonding by occupying antibonding σ-type orbitals.

Cryo-EM structures of UBA6 reveal mechanisms of E1–E2 specificity and dual FAT10/ubiquitin thioester transfer

Free energy landscapes, nucleation, and morphological stability of biphasic nanodroplets dispersed in a liquid phase: A Monte Carlo simulation study of a ternary system

This work employs semigrand canonical ensemble Monte Carlo simulations to investigate the morphology of biphasic nanodroplets suspended in a liquid phase. Using a ternary Lennard-Jones system, we explore the free energy landscapes, nucleation pathways, and thermodynamic stability of core–shell, Janus, and dumbbell configurations that arise from internal phase separation within a parent nanodroplet. Our simulations confirm that the final morphology is dictated by the balance of interfacial free energies between the two droplet components and the surrounding liquid. While a thermodynamic model based on binary interfacial energies provides general predictions, the adsorption of a third component at the liquid–liquid interface alters the interfacial free energy, leading to discrepancies between the model and simulation, particularly for core–shell and crescent-shell morphologies. We also observe a link between the nucleation mechanism and the resulting morphology. Nucleation occurs at higher compositions for systems that form Janus droplets compared to those that form core–shell structures. These findings highlight the limitations of macroscopic models at the nanoscale and offer a more nuanced understanding of phase transitions in nanodroplets, which is essential for the rational design of complex nanoparticles.

Strong optical anisotropy in one-dimensional phosphorus wavy tubes

Abstract Anisotropic materials with intrinsic one-dimensional architectures, where chains or tubes align along a crystallographic axis, exhibit direction-dependent optical responses and serve as ideal building blocks for polarization-sensitive optoelectronics. While progress exists in engineered compounds, discovering elemental crystals with naturally ordered one-dimensional building blocks exhibiting giant optical anisotropy remains challenging. Here, we report the synthesis of a direct-bandgap semiconducting one-dimensional phosphorus single crystal composed of unique wavy polygonal tubes. The monoclinic lattice structure is revealed by single-crystal X-ray diffraction and advanced transmission electron microscopy. The crystal exhibits giant birefringence in the visible and near-infrared regions, stemming from electron localization and anisotropic transitions of the phosphorus 3 p orbital along the tube axis. The low-symmetry structure endows remarkable linear and nonlinear optical anisotropies, including orientation-dependent photoluminescence, Raman scattering, and second-harmonic generation. This study establishes a paradigm for designing giant optical anisotropies, opening avenues for on-chip polarization devices and nonlinear photonic circuits.

A large-scale dataset and physics-informed neural network for viscosity prediction in many-component aqueous and organic solutions

Modern industrial liquids—including coolants, lubricants, solvent blends, cryoprotectant cocktails, etc.—frequently employ complex, many-component formulations, but contemporary viscosity models and datasets are overwhelmingly limited to simplified binary or ternary compositions, leaving the most application-relevant compositional spaces broadly unexplored. This gap is attributable both to the limitations of classical viscosity correlations, which typically require either untenably idealized interaction assumptions or an untenably larger number of interaction parameters, and to the lack of systematic many-component viscosity datasets. Here, we provide a first-of-its-kind dataset of 44 316 viscosity measurements spanning 100 aqueous and organic solutions of up to 17-component complexity across temperatures from −20 to 35 °C, and we use it to power a physics-informed neural network (PINN) model that provides unprecedented predictive power and physical insight into many-component solution viscosity. We first show that predictive implementations of two prominent classical models (Katti–Chaudhuri and augmented Adam–Gibbs) systematically fail to describe these solutions but retain valuable trend-level information. We then use these models as physical guides for our PINN, embedding classical model insight as a training aid while machine learning the residual non-ideal contributions that dominate in many-component composition space. The resulting model, which we also provide as a software application, maintains stable performance across solution complexity, outperforming both classical correlations and data-only artificial neural networks on fully withheld test data. Finally, we compare residuals of both the classical and PINN models as a function of component number and entropy of mixing, suggesting that entropic phenomena unaccounted for in classical models may dominate the viscosity of many-component solutions.