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A six-legged piano stool dysprosium single-molecule magnet
No full textDysprosium single-molecule magnets (SMMs) with two mutually trans- anionic ligands have shown large crystal field (CF) splitting, giving record effective energy barriers to magnetic reversal (Ueff) and hysteresis temperatures (TH). However, these complexes tend to be bent, imposing a transverse field that reduces the purity of the mJ projections of the CF states and promotes magnetic relaxation. A complex with only one anionic ligand could have more pure CF states, and thus high Ueff and TH. Here we report the first example of an SMM with this topology, [Dy(C5Me5)(FPh)6][{Al[OC(CF3)3]3}2(µ-F)]2 (1-Dy), which exhibits Ueff = 564(33) cm–1 and TH = 14 K at sweep rates of 22 Oe s–1; the C5Me5 ligand imposes a strong axial CF and the five equatorially-bound neutral fluorobenzenes present only weak transverse interactions. We show that complexes such as 1-Dy can be useful starting materials for heteroleptic Ln complexes as the fluorobenzenes are easily displaced
Incorporating Azaheterocycle Functionality in Aerobic, Copper-Catalyzed Aminooxygenation of Alkenes
No full textDespite the maturity of alkene 1,2-difunctionalization reactions involving C–N bond formation, a key limitation across aminofunctionalization methods is incompatibility with substrates bearing medicinally relevant N-heterocycles. Using a cooperative ligand-substrate catalyst activation strategy, we have developed an aerobic, copper-catalyzed alkene aminooxygenation method that exhibits broad tolerance for β,γ-unsaturated carbamates bearing aromatic azaheterocycle substitution. The synthetic potential of this methodology was demonstrated by engaging a densely-functionalized vonoprazan analogue and elaborating an aminooxygenated product to synthesize a heteroarylated analogue precursor of the FDA-approved antibiotic chloramphenicol
Ab Initio Molecular Dynamics Simulations of Atmospheric Molecular Clusters Boosted by Neural Networks
No full textThe computational cost of accurate quantum chemistry (QC) calculations of large molecular systems can often be unbearably high. Machine learning offers a lower computational cost compared to QC methods while maintaining their accuracy. In this study, we employ the polarizable atom interaction neural network (PaiNN) architecture to train and model the potential energy surface of molecular clusters relevant to atmospheric new particle formation, such as sulfuric acid–ammonia clusters. We compare the differences between the neural network and previous kernel ridge regression modeling for the Clusteromics I–V data sets. We showcase three models capable of predicting electronic binding energies and interatomic forces with mean absolute errors of <0.3 kcal/mol and <0.2 kcal/mol/ ̊A, respectively. Furthermore, we demonstrate that the error of the modeled properties remains below the chemical accuracy of 1 kcal/mol even for clusters vastly larger than those in the training database (up to (H2SO4)15(NH3)15 clusters, containing 30 molecules). Consequently, we emphasize the potential applications of these models for faster and more thorough configurational sampling and for boosting molecular dynamics studies of large atmospheric molecular clusters
AB-stacked bilayer β12–borophene as a promising anode material for alkali metal-ion batteries
No full textAs the lightest 2D- material, monolayer borophene exhibits a specific charge capacity of 1860 mAh g-1 for Li-ion batteries, which is four times higher than that of graphite and is one of the highest specific charge capacities ever reported for 2D anode materials. Additionally, it showed high mechanical strength and a low diffusion barrier. However, monolayer borophene suffers from stability issues in its free-standing form, which restricts its real-life applications. Inspired by the recent experimental investigations, which proved the higher stability of bilayer borophene polymorphs (BBPs) over their monolayer counterparts, in this work, we investigated the dynamical and thermodynamical stabilities of both AA and AB–stacked BBPs in their β12 phase using first-principles calculations. Between the two stacking patterns, we found that only the AB–stacked β12–BBP is both energetically and dynamically stable, and we further investigated its potential as a high-performance anode material for alkali metal ion batteries. Our investigations show that AB–stacked β12–BBP exhibits good electrical conductivity before and after metal atom (Li/Na/K) adsorption onto it. Further, AB–stacked β12–BBP adsorbs the metal atoms strongly with adsorption energies ranging between -0.89 to -1.44 eV, indicating that there is a lesser possibility of forming dendrites on this anode. Similarly, it has a low diffusion energy barrier (~ 0.13–0.49 eV) for metal atoms, meeting the fast charge/discharge rate requirements. Moreover, it exhibits a reasonably low average metal-insertion voltage (0.43 to 0.65 V) and a specific charge capacity of 330–413 mAh g-1 that is comparable to graphite. All the above findings suggest that the AB–stacked bilayer β12– borophene can be a potentially favorable anode material
Developing Chlorin/Arylaminoquinazoline Conjugates with Nanomolar Activity for Targeted Photodynamic Therapy: Design, Synthesis, SAR, and Biological Evaluation
No full textIn this report, we developed novel chlorin/arylaminoquinazoline conjugates for targeted photodynamic therapy of cancer. The synthesized photosensitizers consisted of chlorin-e6 metallocomplexes (Zn, In, or Pd) conjugated with arylaminoquinazoline ligands with high affinity for EGFR receptors. Through the incorporation of cationic moieties, we successfully prepared water-soluble conjugated drugs suitable for intravenous administration. Comprehensive SAR studies were conducted to evaluate the influence of structural features on the photodynamic activity of these conjugates. Additionally, the selectivity and antitumor properties of the conjugates were investigated in EGFR-expressing A431 human tumor cell line in vitro. Among the tested molecules, the In-containing conjugate effectively inhibited tumor cell proliferation at nanomolar concentrations, a rare property for conventional photosensitizers. In in vivo experiments, the conjugates rapidly accumulated at the tumor site in nude mice bearing A431 xenograft tumors. Subsequent distribution analysis among different tissues was carried out using fluorescence imaging and elemental analysis. Finally, we demonstrated that the most promising In-containing conjugate was capable of inhibiting xenograft tumor growth in mice through combinational therapy
Multiconfigurational Surface Hopping: A Time-Dependent Variational Approach with Momentum-Jump Trajectories
No full textThe Ehrenfest mean field dynamics and trajectory surface hopping have been widely used in nonadiabatic dynamics simulations. Based on the time-dependent variational principle (TDVP), the multiconfigurational Ehrenfest (MCE) method has also been developed and can be regarded as a multiconfigurational extension of the traditional Ehrenfest dynamics. However, it is not straightforward to apply the TDVP to surface hopping trajectories because there exists momentum jump during surface hops. To solve this problem, we here propose a multiconfigurational surface hopping (MCSH) method, where continuous momenta are obtained by linear interpolation and the interpolated trajectories are used to construct the basis functions for TDVP in a post-processing manner. As demonstrated in a series of representative spin-boson models, MCSH achieves high accuracy with only several hundred trajectory bases and can uniformly improve the performance of surface hopping. In principle, MCSH can be combined with all kinds of mixed quantum-classical trajectories, and thus has the potential to properly describe general nonadiabatic dynamics
Validating Small-Molecule Force Fields for Macrocyclic Compounds Using NMR Data in Different Solvents
No full textMacrocycles are a promising class of compounds as therapeutics for difficult drug targets due to a favourable combination of properties: They often exhibit improved binding affinity compared to their linear counterparts due to their reduced conformational flexibility, while still being able to adapt to environments of different polarity. To assist in the rational design of macrocyclic drugs, there is need for computational methods that can accurately predict conformational ensembles of macrocycles in different environments. Molecular dynamics (MD) simulations remain one of the most accurate methods to predict ensembles quantitatively, although the accuracy is governed by the underlying force field. In this work, we benchmark four different force fields for their application to macrocycles by performing replica exchange with solute tempering (REST2) simulations of eleven macrocyclic compounds and comparing the obtained conformational ensembles to nuclear Overhauser effect (NOE) upper distance bounds from NMR experiments. Especially, the modern force fields OpenFF 2.0 and XFF yield good results, outperforming force fields like GAFF2 and OPLS/AA. We conclude that REST2 in combination with modern force fields can often produce accurate ensembles of macrocyclic compounds. However, we also highlight examples for which all examined force fields fail to produce ensembles that fulfill the experimental constraints
A Foundational Model for Reaction Networks on Metal Surfaces
No full textProcess optimization in heterogeneous catalysis relies on the control of competing reactions. The reaction mechanisms based on chemical knowledge can be evaluated via density functional theory unveiling experimental catalytic trends. However, this approach finds its limits when applied to complex reaction networks or large molecules, disregarding alternative paths and rare events. Here we present CARE, a foundational model for catalysis on metal surfaces with a rule-based reaction network generator for CxHyOz species built with GAME-Net-UQ, a graph neural network with uncertainty quantification targeting thermodynamic and kinetic parameters, coupled to microkinetic modeling. CARE reproduces experimental activity trends in methanol decomposition, selectivity to C3 products in electrochemical reduction processes, and models the Fischer-Tropsch synthesis to C6 products, including 370k reactions, breaking the current limits of network exploration. This comprehensive model opens the path towards the exploration of thermal and electrocatalytic surface processes previously not amenable to atomistic simulations
Hybridized Local and Charge Transfer Modulated Triplet Decay Brightens Ultra-Long Circularly Polarized Afterglow and Chiral Diradical Activity
No full textThe design and construction of chiral phosphors with significant long-lived triplet exciton decay have received great attention because of their prospective applications in ultra-long circularly polarized roomtemperature phosphorescence (CP-RTP) for chiral optics. However, the practical utilization of pure organics as triplet incubators is often hindered by their spin-forbidden transition. Therefore, it is a substantial challenge for the developments of organic-derived CPRTP emitters with both long lifetimes and asymmetry factors. Herein, via precisely manipulating hybridized local and charge transfer (HLCT) and multiple n−π* effects, we report the first P,N-embedded tactic to construct the BINAP-derived emitters, which show tunable circularly polarized luminescence (CPL) with near-unity photoluminescence quantum efficiency (PLQY = 95.3%), |glum| values (1.2 to 6.2 × 10−3), and ultra-long RTP with remarkable lifetime as long as 448 ms in the polymethyl methacrylate. Experiments and quantum chemistry simulations unveil that the abovementioned triplet decay is derived from tunable HLCT and a balanced electric-magnetic dipole moment environment. Moreover, the synergetic enhancement of chemical and configurational stability enables stable chiral diradicals with a high diradical character (y0 = 0.953) and near-infrared ray (NIR) optical activity. This work provides important clues for CP-RTP phosphors and chiral diradical materials
Atomistics-consistent continuum models and pore-collapse-generated hotspot temperatures in energetic crystals I: beta-1,3,5,7-tetranitro-1,3,5,7-tetrazocane (beta-HMX)
No full textHotspot formation due to pore collapse is a key mechanism for initiating detonation of shocked energetic materials. Energy localization at and around the pore collapse site leads to high-temperature hotspots, initiating chemical reactions. Because chemical reaction rates depend sensitively on temperature, predictive continuum models need to get the pore-collapse dynamics and resulting hotspot temperatures right; this imposes stringent demands on the fidelity of thermophysical model forms and parameters, and on the numerical methods employed to perform high-resolution meso-scale calculations. Here, continuum material models for beta-HMX are examined in the context of nanoscale shock-induced pore collapse, treating predictions from molecular dynamics (MD) simulations as ground truth. Using MD-consistent material properties, we show that the currently available strength models for HMX fail to correctly capture pore collapse and hotspot temperatures. Insights from MD are then employed to advance a Modified Johnson-Cook (M-JC) strength model form that captures aspects of shear strain and strain-rate dependency not represented by the standard JC form, but which are shown to be critical for accurately describing the nanoscale physics of shock-induced localization in HMX. The study culminates in a fully MD-determined strength model for beta-HMX that produces continuum pore-collapse results well aligned in all aspects with those predicted by MD, including pore-collapse mechanism and rate, shear-band formation in the collapse zone, and temperature, strain, and stress fields in the hotspot zone and surrounding material. The resulting MD-informed/MD-determined M-JC model should improve the fidelity of simulations to predict the detonation initiation of HMX-based energetic materials in microstructure-aware multi-scale frameworks