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At least 721 records · Page 40

RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design

Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural constraints. This work presents RLMolLM, a reinforcement learning framework combining Proximal Policy Optimization (PPO) with genetic algorithms to address these limitations. Our approach optimizes multiple user-specified properties including quantitative estimates of drug-likeness (QED), synthetic accessibility (SA), and ADMET (absorption, distribution, metabolism, excretion, and toxicity) endpoints without requiring complete model retraining, while maintaining capability for scaffold-constrained generation where specific substructures must be preserved. We outperform state-of-the-art methods for molecular optimization, achieving best QED scores across GDB13, Moses, and Zinc datasets with up to 31% improvement over previous methods while maintaining excellent validity, uniqueness, and novelty metrics. For simultaneous multi-property optimization, our framework achieves substantial improvements in ADMET properties including 4.5-fold reduction in hERG toxicity and enhanced Caco-2 permeability compared to Moses dataset. Under structural constraints, the framework significantly improves molecular validity while preserving scaffolds and effectively optimizing properties. In conclusion, this versatile solution advances pharmaceutical and materials molecular design through effective integration of reinforcement learning and genetic algorithms with multi-property optimization and scaffold preservation.

Genetic algorithms↗

Optimized molecular aggregation via incorporating fluorinated unit in the polymer donor for 17.3% efficiency organic solar cells

Regulating molecular aggregation state via chemical modification of photovoltaic materials to optimize the blend morphology is an effective and challenging strategy to improve the photovoltaic performance of organic solar cells (OSCs). Here, in this work, we demonstrate a random terpolymerization strategy by incorporating 1,3-bis(5-bromo-4-fluorothiophen-2-yl)-5,7-bis(2-ethylhexyl)-4H,8H-benzo[1,2-c:4,5-c']bisthiophene-4,8-dione (BFT, 30 mol%) unit with fluorinated π-bridges into the molecular backbone of PM6 and develop a terpolymer PF1. Benefiting from the strong electronegativity of fluorine atom and noncovalent interaction of F---S, the energy levels, molecular ordering, and aggregation properties of the polymer donors are precisely regulated. Notably, in the active layer film based on PF1: Y6, the π-π stacking distance can reduce to 3.51 Å, which is significantly smaller than that of PM6:Y6 (3.65 Å) and boosts the effective exciton dissociation and charge transport, thereby effectively optimize the photovoltaic properties of the related devices. As a result, the PF1:Y6-based OSCs achieved a power conversion efficiency (PCE) of up to 17.3%, which is much higher than that of the controlled OSCs based on PM6:Y6 (PCE = 16.2%). These results demonstrate high-efficiency OSCs enabled by regulating molecular aggregation via terpolymerization strategy.

14 SOLAR ENERGY↗

Metal Complex Molecular Solids Showing Band-like Transport Driven by In Situ Ligand Exchange

Transition-metal complexes exhibit excellent charge transport properties in solid films, rendering them promising for application in modern electronics. Although the charge transport mechanism of metal complex solids with multiple redox states is considered to be governed by self-exchange hole hopping, the effect of additives, such as Lewis bases, has not been identified. Herein, we describe the effect of 4- tert -butylpyridine (TBP) on the charge transport mechanism and film properties of [Cu(dmbpy) 2 ] 2 + / + (dmbpy = 6,6'-dimethyl-2,2'-bipyridine)-based molecular solids. The formation of [Cu(TBP) 4 ] 2 + , excess TBP, and free dmbpy from the ligand-exchange reaction between [Cu(dmbpy) 2 ] 2 + and TBP increases the film conductivity and changes the transport mechanism from hopping to band-like transport through a combination of chemical composition, film morphology, and crystallographic changes. In conclusion, these findings advance our understanding of the fundamental properties of molecular metal complex solids and enable optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The mechanical response of micron-sized molecular crystals

Abstract Microstructures and corresponding properties of compacted powders ultimately depend on the mechanical response of individual particles. In principle, computational simulations can predict the results of powder compaction processes, but the selection of appropriate models for both particle–particle interactions and particle deformations across all relevant length scales remain nontrivial tasks, especially in material systems lacking detailed mechanical property information. The work presented here addresses these issues by conducting uniaxial compressions in situ inside of a scanning electron microscope to characterize the mechanical response of individual micron-sized particles of a molecular crystal, hexanitrohexaazaisowurtzitane (CL-20). This experimental approach enabled the collection of quantitative force and displacement data alongside simultaneous imaging to capture morphology changes. The results reveal information about elastic deformation, yield, plastic deformation, creep, and fracture phenomena. Accordingly, this work demonstrates a generalizable approach for assessing the mechanical response of individual micron-sized molecular crystal particles and utilizing those responses in particle-level models. Graphic abstract

36 MATERIALS SCIENCE↗

Molecular Picture of the Transient Nature of Lipid Rafts

In biological membranes, lipid rafts are now thought to be transient and nanoscopic. However, the mechanism responsible for these nanoscopic assemblies remains poorly understood, even in the case of model membranes. Therefore, it has proven extremely challenging to probe the physicochemical properties of lipid rafts at the molecular level. Here, we use all-atom molecular dynamics (MD) simulations and inelastic X-ray scattering (IXS), an intrinsically nanoscale technique, to directly probe the energy transfer and collective short-wavelength dynamics (phonons) of biologically relevant model membranes. We show that the nanoscale propagation of stress in lipid rafts takes place in the form of collective motions made up of longitudinal (compression waves) and transverse (shear waves) molecular vibrations. Importantly, we provide a molecular picture for the so-called van der Waals mediated "force from lipid" [Anishkin, A. et al. Proc. Natl. Acad. Sci. U.S.A. 2014, 111, 7898], a key parameter for the ionic channel mechano-transduction and the mechanism for the lipid transfer of molecular level stress [Aponte-Santamaría, C. et al. J. Am. Chem. Soc. 2017, 139, 13588]. Specifically, we describe how lipid rafts are formed and maintained through the propagation of molecular stress, lipid raft rattling dynamics, and a relaxation process. Eventually, the rafts dissipate through the self-diffusion of lipids making up the rafts. We also show that the molecular stress and viscoelastic properties of transient lipid rafts can be modulated through the use of hydrophobic biomolecules such as melatonin and tryptophan. Overall, the herein proposed mechanism describing the molecular interactions for the formation and dissolution of lipid rafts may offer insights as to how lipid rafts enable biological function.

36 MATERIALS SCIENCE↗

Molecular Dynamics Simulation of a Multi-Walled Carbon Nanotube Based Gear

We used molecular dynamics to investigate the properties of a multi-walled carbon nanotube based gear. Previous work computationally suggested that molecular gears fashioned from (14,0) single-walled carbon nanotubes operate well at 50-100 gigahertz. The gears were formed from nanotubes with teeth added via a benzyne reaction known to occur with C60. A modified, parallelized version of Brenner's potential was used to model interatomic forces within each molecule. A Leonard-Jones 6-12 potential was used for forces between molecules. The gear in this study was based on the smallest multi-walled nanotube supported by some experimental evidence. Each gear was a (52,0) nanotube surrounding a (37,10) nanotube with approximate 20.4 and 16,8 A radii respectively. These sizes were chosen to be consistent with inter-tube spacing observed by and were slightly larger than graphite inter-layer spacings. The benzyne teeth were attached via 2+4 cycloaddition to exterior of the (52,0) tube. 2+4 bonds were used rather than the 2+2 bonds observed by Hoke since 2+4 bonds are preferred by naphthalene and quantum calculations by Jaffe suggest that 2+4 bonds are preferred on carbon nanotubes of sufficient diameter. One gear was 'powered' by forcing the atoms near the end of the outside buckytube to rotate to simulate a motor. A second gear was allowed to rotate by keeping the atoms near the end of its outside buckytube on a cylinder. The ends of both gears were constrained to stay in an approximately constant position relative to each other, simulating a casing, to insure that the gear teeth meshed. The stiff meshing aromatic gear teeth transferred angular momentum from the powered gear to the driven gear. The simulation was performed in a vacuum and with a software thermostat. Preliminary results suggest that the powered gear had trouble turning the driven gear without slip. The larger radius and greater mass of these gears relative to the (14,0) gears previously studied requires a smaller rotation rate and multiple rows of teeth to avoid excessive force on the gear teeth resulting, in slip and failure of the driven gear to turn. We hope that studies such as these will eventually lead to synthesis of components that can be assembled into atomically precise fullerene machines. These machines, in turn, may someday be used in machine-phase fullerene materials with remarkable properties.

Han, Jie↗

Rotational Dynamics of an Amphidynamic Zirconium Metal–Organic Framework Determined by Dielectric Spectroscopy

A zirconium metal–organic framework with a difluorophenylene rotator bearing a permanent electric dipole of ~3.2 D was synthesized, and its rotational motion was analyzed by temperature- and frequency-dependent broadband dielectric spectroscopy. While solid-state NMR confirms fast rotation qualitatively, the dissipation factors measured between 113 and 153 K suggested an activation energy E a = 2.6 kcal/mol, but deviations from a single Debye relaxation suggested a dynamic process that cannot be accounted for by a well-defined potential with a single activation barrier. The dynamic heterogeneity of the dipolar rotor was confirmed by analysis in terms of a Cole–Cole relaxation, which suggested a mean barrier of ~1.9 kcal/mol, with a heterogeneity that decreases as temperature increases. Based on the single-crystal structure, we propose that the kinetic heterogeneity results from a temperature-dependent potential where rotation motion is mediated by the escape of the rotator from an energy well created by a double Ph–H···F–Ph hydrogen bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Properties of air and combustion products of fuels with air

Thermodynamic and transport properties include ratio of specific heats, molecular weight, viscosity, heat capacity, thermal conductivity, and Prandtl number. Properties are calculated from 300 to 2500 degrees K and for pressures of three and ten atmospheres.

Lewandowski, K.↗

Employing a Narrow-Band-Gap Mediator in Ternary Solar Cells for Enhanced Photovoltaic Performance

Ternary organic solar cells (OSCs) provide a convenient and effective means to further improve the power conversion efficiency (PCE) of binary ones via composition control. However, the role of the third component remains to be explored in specific binary systems. Herein, we report ternary blend solar cells by adding the narrow-band-gap donor PCE10 as the mediator into the PBDB-T:IDTT-T binary blend system. The extended absorption, efficient fluorescence resonance energy transfer, enhanced charge dissociation, and induced tighter molecular packing of the ternary blend films enhance the photovoltaic properties of devices and deliver a champion PCE of 10.73% with an impressively high open-circuit voltage (VOC) of 1.03 V. Good miscibility and similar molecular packing behavior of the components guarantee the desired morphology in the ternary blend films, leading to solar cell devices with over 10% PCEs at a range of compositions. Our results suggest that ternary systems with properly aligned energy levels and overlapping absorption among the components hold great promises to further enhance the performance of corresponding binary ones.

14 SOLAR ENERGY↗

Intrinsic glassy-metallic transport in an amorphous coordination polymer

Conducting organic materials, such as doped organic polymers, molecular conductors and emerging coordination polymers4, underpin technologies ranging from displays to flexible electronics. Realizing high electrical conductivity in traditionally insulating organic materials necessitates tuning their electronic structure through chemical doping6. Furthermore, even organic materials that are intrinsically conductive, such as single-component molecular conductors, require crystallinity for metallic behavior. However, conducting polymers are often amorphous to aid durability and processability. Using molecular design to produce high conductivity in undoped amorphous materials would enable tunable and robust conductivity in many applications, but there are no intrinsically conducting organic materials that maintain high conductivity when disordered. Here we report an amorphous coordination polymer, Ni tetrathiafulvalene tetrathiolate, which displays markedly high electronic conductivity (up to 1,200 S cm –1 ) and intrinsic glassy-metallic behavior. Theory shows that these properties are enabled by molecular overlap that is robust to structural perturbations. This unusual set of features results in high conductivity that is stable to humid air for weeks, pH 0–14 and temperatures up to 140 °C. Furthermore, these findings demonstrate that molecular design can enable metallic conductivity even in heavily disordered materials, raising fundamental questions about how metallic transport can exist without periodic structure and indicating exciting new applications for these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic properties of CO emission from galaxies. II - Weighted correlations

The dependence of molecular gas emission on various global galaxy properties is tested by examining a series of correlations. CO luminosities of entire galaxies are correlated with their H I content, blue luminosity, disk area, far-infrared luminosity, Hubble type, Elmegreen arm type, DDO luminosity class, total B-V color, disk B-V color, and H-alpha emission. A weighted correlation test is derived and applied to correct for the strong Malmquist bias in the available CO observations of galaxies. The relative strengths of the correlations indicate that molecular emission has a strong dependence on galaxy scale, a weak dependence on galaxy form, and is closely linked to tracers of star forming regions.

Verter, Frances↗

Ultra-High-Molecular-Weight Silphenylene/Siloxane Elastomers

Elastomers enhance thermal and mechancial properties. Capable of performing in extreme thermal/oxidative environments and having molecular weights above 10 to the sixth power prepared and analyzed in laboratory experiments. Made of methylvinylsilphenylene-siloxane terpolymers, new materials amenable to conventional silicone-processing technology. Similarly formulated commercial methyl-vinyl silicones, vulcanized elastomers exhibit enhance thermal/oxidative stability and equivalent or superior mechanical properties.

Hundley, N. H.↗

Cartesian equivariant representations for learning and understanding molecular orbitals

Qualitative and quantitative orbital properties such as bonding/antibonding character, localization, and orbital energies are critical to how chemists understand reactivity, catalysis, and excited-state behavior. Despite this, representations of orbitals in deep learning models have been very underdeveloped relative to representations of molecular geometries and Hamiltonians. Here, we apply state-of-the-art equivariant deep learning architectures to the task of assigning global labels to orbitals, namely energies characterizations, given the molecular coefficients from Hartree–Fock or density functional theory. The architecture we have developed, the Cartesian Equivariant Orbital Network (CEONET), shows how molecular orbital coefficients are readily featurized as equivariant node features common to all graph-based machine-learned potentials. We find that CEONET performs well at predicting difficult quantitative labels such as the orbital energy and orbital entropy. Furthermore, we find that the CEONET representation provides an intuitive latent space for differentiating orbital character for the qualitative assignment of e.g. bonding or antibonding character. In addition to providing a useful representation for further integrating deep learning with electronic structure theory, we expect CEONET to be useful for automatizing and interpreting the results of advanced electronic structure methods such as complete active space self-consistent field theory. In particular, the ability of CEONET to infer multireference character via the orbital entropy paves the way toward the machine-learned selection of active spaces.

chemical reactions↗

Mapping the functional landscape of the receptor binding domain of T7 bacteriophage by deep mutational scanning

The interaction between a bacteriophage and its host is mediated by the phage's receptor binding protein (RBP). Despite its fundamental role in governing phage activity and host range, molecular rules of RBP function remain a mystery. Here, we systematically dissect the functional role of every residue in the tip domain of T7 phage RBP (1660 variants) by developing a high-throughput, locus-specific, phage engineering method. This rich dataset allowed us to cross compare functional profiles across hosts to precisely identify regions of functional importance, many of which were previously unknown. Substitution patterns showed host-specific differences in position and physicochemical properties of mutations, revealing molecular adaptation to individual hosts. We discovered gain-of-function variants against resistant hosts and host-constricting variants that eliminated certain hosts. To demonstrate therapeutic utility, we engineered highly active T7 variants against a urinary tract pathogen. Our approach presents a generalized framework for characterizing sequence–function relationships in many phage–bacterial systems.

59 BASIC BIOLOGICAL SCIENCES↗

RASPA3

RASPA3, a molecular simulation code for computing adsorption and diffusion in nanoporous materials and thermodynamic and transport properties of fluids. It implements force field based classical Monte Carlo/molecular dynamics in various ensembles. RASPA3 is rewritten from the ground up in C++23 with speed and code readability in mind. Transition-matrix Monte Carlo is added to compute the density of states and free energies. The Monte Carlo code for rigid molecules is based on quaternions, and the atomic positions needed in the energy evaluation are recreated from the center of mass position and quaternion orientation. The expanded ensemble methodology for fractional molecules, with a scaling parameter λ between 0 and 1, now also keeps track of analytic expressions of dU/dλ, allowing independent verification of the chemical potential using thermodynamic integration. The source code is freely available under the MIT license on GitHub.

Dubbeldam, David↗

Highly Conjugated Porphyrin Arrays Enable Optical Resolution of Ferromagnetic and Antiferromagnetic Aligned States of the Triplet Exciton and an Incorporated Stable Radical

Well-defined photogenerated molecular spin systems have potential utility in spintronics and quantum information science (QIS). Because molecular magnetic, optical, and electronic properties can be controlled by design, diverse spin systems can be prepared at modest temperatures. Photogenerated molecular spin systems often involve states prepared from the interaction of excitons and charges. Resolving the nature of electron spin alignment in photogenerated spin states described by the coupling of a triplet exciton and a stable radical commonly relies on EPR spectroscopy. Here, we describe ethyne-bridged (porphinato)metal ( PM n ) oligomers that incorporate a macrocycle-bound Cu(II) radical center. Upon photoexcitation of such PM n arrays, a singdoublet ( 2 S 1 ) state is formed; ultrafast internal conversion (IC) then produces a tripdoublet ( 2 T 1 ) state, which undergoes intersystem crossing (ISC) to produce a tripquartet ( 4 T 1 ) state, before relaxation to the ground state ( 2 S 0 ). These highly conjugated Cu(II) radical-containing PMn arrays enable direct observation of copper porphyrin 2 T 1 → 4 T 1 ISC dynamics from the biexponential decay of the near-infrared (NIR) 2,4 T 1 → 2,4 T n transient absorption manifold. Multireference n-electron valence perturbation theory (NEVPT2) computations illuminate how PM n electronic structure controls the relaxation dynamics of these long-lived (>10 ns) electronically excited multiplet states. These studies show that highly conjugated and polarizable porphyrin arrays incorporating stable spin centers provide rare π-delocalized systems where the ferromagnetic and antiferromagnetic alignment between a triplet exciton and a stable radical are both spectrally resolved and addressable using transient optical spectroscopy at wavelengths exceeding 1 μm, providing new opportunities to QIS.

14 SOLAR ENERGY↗

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗