B97-3c: A revised low-cost variant of the B97-D density functional method

Reversing selectivity of bambusuril macrocycles toward inorganic anions by installing spacious substituents on their portals

Two chiral bambusurils, which are diastereomers to each other, show remarkable differences in their binding affinity and selectivity toward inorganic anions as determined by isothermal titration calorimetry. These differences are explained by quantum-chemical calculations.

True Dynamics of Pillararene Host-Guest Binding

Accurate modeling of host-guest systems is challenging in modern computational chemistry. It requires intermolecular interaction patterns to be correctly described and, more importantly, the dynamic behaviors of macrocyclic hosts to be accurately modeled. Pillar[n]arenes as a crucial family of macrocycles play a critical role in host-guest chemistry and biomedical applications. The carboxylated form with 6 or 7 repeating units is of high popularity due to increased solubility and the compatibility between cavity size and drugs. While prefitted transferable force fields are dominantly applied in host-guest modeling, their reliability and accuracy for macrocyclic hosts remain unjustified. In the current work, based on solid numerical evidence about energetics and dynamics, we prove that all transferable force fields fail to provide a correct description of host dynamics for the most popular carboxylated pillararenes. Therefore, all existing simulation reports on this host family could be biased due to the unsuitability of the force-field description. Such huge modeling problems do not occur in other host families that are relatively rigid (e.g., octa acids and cucurbiturils), highlighting the difficulties in modeling pillararene host-guest interactions. To pursue the true picture of the pillararene dynamics and host-guest binding, we fit high-quality molecule-specific parameters for the carboxylated pillararene based on ab initio calculations and perform an exhaustive conformational search of host-guest binding modes with advanced sampling techniques. We provide estimates of binding thermodynamics, report the true dynamic behavior of the WP6 host in the bound and unbound states, and reveal a general multimodal binding behavior of pillararene host-guest complexes. The current work serves as a critical step toward a reliable all-atom description of pillararene host-guest coordination.

Data-Driven Improvement of Local Hybrid Functionals: Neural-Network-Based Local Mixing Functions and Power-Series Correlation Functionals

Local hybrid functionals (LHs) use a real-space position-dependent admixture of exact exchange (EXX), governed by a local mixing function (LMF). The systematic construction of LMFs has been hampered over the years by a lack of exact physical constraints on their valence behavior. Here, we exploit a data-driven approach and train a new type of "n-LMF" as a relatively shallow neural network. The input features are of meta-GGA character, while the W4-17 atomization-energy and BH76 reaction-barrier test sets have been used for training. Simply replacing the widely used "t-LMF" of the LH20t functional by the n-LMF provides the LH24n-B95 functional. Augmented by DFT-D4 dispersion corrections, LH24n-B95-D4 remarkably improves the WTMAD-2 value for the large GMTKN55 test suite of general main-group thermochemistry, kinetics, and noncovalent interactions (NCIs) from 4.55 to 3.49 kcal/mol. As we found the limited flexibility of the B95c correlation functional to disfavor much further improvement on NCIs, we proceeded to replace it by an optimized B97c-type power-series expansion. This gives the LH24n functional. LH24n-D4 gives a WTMAD-2 value of 3.10 kcal/mol, the so far lowest value of a rung 4 functional in self-consistent calculations. The new functionals perform moderately well for organometallic transition-metal energetics while leaving room for further data-driven improvements in that area. Compared to complete neural-network functionals like DM21, the present more tailored approach to train just the LMF in a flexible but well-defined human-designed LH functional retains the possibility of graphical LMF analyses to gain deeper understanding. We find that both the present n-LMF and the recent x-LMF suppress the so-called gauge problem of local hybrids without adding a calibration function as required for other LMFs. LMF plots show that this can be traced back to large LMF values in the small-density region between the interacting atoms in NCIs for n- and x-LMFs and low values for the t-LMF. We also find that the trained n-LMF has relatively large values in covalent bonds without deteriorating binding energies. The current approach enables fast and efficient routine self-consistent calculations using n-LMFs in Turbomole.

Selective Reduction of Esters to Access Aldehydes Using Fiddler Crab-Type Boranes

The partial reduction of esters to aldehydes is a fundamentally important transformation for the synthesis of numerous fine chemicals and consumer goods. However, despite the many efforts, limitations have persisted, such as competing overreduction, low reproducibility, use of exigent reaction conditions and hazardous chemicals. Here, we report a novel catalyst family with a unique steric design which promotes the catalytic partial reduction of esters with unprecedented, near-perfect selectivity and efficiency. This metal-free catalytic method is ready to be placed at the disposal of chemists to provide valuable aldehyde intermediates and products and shows promise for streamlining synthetic methods in academic and industrial settings.

A drug-drug co-amorphous system for highly improved solubility of breviscapine: an experimental and computational study

Drug-drug co-amorphous systems are a promising approach to improve the aqueous solubility of poorly water-soluble drugs. This study explores the combination of breviscapine (BRE) and matrine (MAT) form an amorphous salt, aiming to synergistically enhance the solubility and dissolution of BRE. In silico analysis of electrostatic potential and local ionization energy were conducted on BRE-MAT complex to predict the intermolecular interactions, and solvent-free energies were calculated using thermodynamic integration and density functional theory. The co-amorphous mixture, prepared by solvent evaporation, was characterized using various analytical techniques, including polarized microscopy, differential scanning calorimetry, and powder X-ray diffraction, confirming its amorphous nature. Fourier transform infrared spectroscopy and molecular dynamic simulations revealed strong hydrogen bonding, with a proton transfer from the carboxyl group of BRE to the tertiary amine nitrogen of MAT. The resulting co-amorphous salt demonstrated substantial solubility improvement (> 8000-fold in water) and enhanced in vitro dissolution of BRE. The study also confirmed that the co-amorphous salt maintained physical stability at 40 °C and 75% relative humidity over 6 months. These findings provide a viable strategy for developing drug-drug co-amorphous formulations to enhance solubility and stability, with significant potential for pharmaceutical applications.

From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy

Accurate calculation of solvation energies has long fascinated researchers, but complex interactions within bulk water molecules pose significant challenges. Currently, molecular solvation energy calculations are mostly based on implicit solvent approximations in which the solvent molecules are treated as continuum dielectric media. However, the implicit solvent approach is not ideal because it lacks certain real solvation effects, such as that of the first solvation shell, etc. Here, we propose an explicit solvent approach, interaction-reorganization solvation (IRS) method, for molecular solvation energy calculations. The IRS approach achieves predictive accuracy comparable to that of the widely recognized solvation model based on the density (SMD) method and is significantly more accurate than that of the Poisson-Boltzmann/generalized Born surface area (PB/GBSA) methods. This is demonstrated in both the correlation coefficient and the mean absolute error (MAE) with respect to the experimental data. The IRS method is based on molecular dynamics simulation in explicit solvent and does not need to solve Poisson-Boltzmann or Schrödinger equations. On the other hand, the accuracy of the IRS method does depend on the accuracy of the molecular force field used in MD simulations. We expect that the IRS method will be very useful for the solvation energy calculations of molecules.

Canonical coupled cluster binding benchmark for nanoscale noncovalent complexes at the hundred-atom scale

In this study, we introduce two datasets for nanoscale noncovalent binding, featuring complexes at the hundred-atom scale, benchmarked using coupled cluster with single, double, and perturbative triple [CCSD(T)] excitations extrapolated to the complete basis set (CBS) limit. The first dataset, L14, comprises 14 complexes with canonical CCSD(T)/CBS benchmarks, extending the applicability of CCSD(T)/CBS binding benchmarks to systems as large as 113 atoms. The second dataset, vL11, consists of 11 even larger complexes, evaluated using the local CCSD(T)/CBS method with stringent thresholds, covering systems up to 174 atoms. We compare binding energies obtained from local CCSD(T) and fixed-node diffusion Monte Carlo (FN-DMC), which have previously shown discrepancies exceeding the chemical accuracy threshold of 1 kcal/mol in large complexes, with the new canonical CCSD(T)/CBS results. While local CCSD(T)/CBS agrees with canonical CCSD(T)/CBS within binding uncertainties, FN-DMC consistently underestimates binding energies in π-π complexes by over 1 kcal/mol. Potential sources of error in canonical CCSD(T)/CBS are discussed, and we argue that the observed discrepancies are unlikely to originate from CCSD(T) itself. Instead, the fixed-node approximation in FN-DMC warrants further investigation to elucidate these binding discrepancies. Using these datasets as reference, we evaluate the performance of various electronic structure methods, semi-empirical approaches, and machine learning potentials for nanoscale complexes. Based on computational accuracy and stability across system sizes, we recommend MP2+aiD(CCD), PBE0+D4, and ωB97X-3c as reliable methods for investigating noncovalent interactions in nanoscale complexes, maintaining their promising performance observed in smaller systems.

Stacking interactions in stabilizing supramolecular assembly of M[9C]2M complexes: dynamic stability with remarkable nonlinear optical features

Continual attempts have been made to discover excellent nonlinear optical (NLO) materials. Here, we investigate the role of stacking interactions and van der Waals forces in the designed parallel stacked complexes M[9C]2M (where M = Li, Na, K, Be, Mg, and Ca) using various quantum chemical and molecular dynamics methods. The thermodynamic stability of the present complexes is also revealed by the computed interaction energy, enthalpy of formation, and Gibbs free energy of formation (ΔGf). Molecular dynamics simulations were performed at room temperature to determine the stability of the dimer formation and their complexes. Alkali metals act as a more prominent source of excess electrons at long-range interaction distances. Charge decomposition analysis (CDA) and natural bonding orbital (NBO) analyses suggest excellent charge transfer in the alkalide complexes. In this series, Li[9C]2Li exhibits an excellent hyperpolarizability response up to 2.3 × 106 a.u., while Ca[9C]2Ca performs well in alkaline-earth metal complexes. The NLO response is mostly influenced by the alkalide and earthide characteristics. Dynamic NLO features were computed at externally applied frequencies. Scattering first hyperpolarizability (βHRS) and its associated components were also measured. The effect of solvents on hyperpolarizability is also considered. The quantum theory of atoms in molecules (QTAIM) and NCI are employed to investigate the bonding nature and vdW forces in addition to stacking interactions. TD-DFT and vibrational studies are also performed. We aim for this research to pave the way for the innovative strategies in designing supramolecular assemblies tailored for NLO applications.

A Benchmark Study of DFT-Computed p-Block Element Lewis Pair Formation Enthalpies Against Experimental Calorimetric Data

The quantification of Lewis acidity is of fundamental and applied importance in chemistry. While the computed fluoride ion affinity (FIA) is the most widely accepted thermodynamic metric, only sparse experimental values exist. Accordingly, a benchmark of methods for computing Lewis pair formation enthalpies, also with a broader set of Lewis bases against experimental data, is missing. Herein, we evaluate different density functionals against a set of 112 experimentally determined Lewis acid/base binding enthalpies and gauge influences such as solvation correction in structure optimization. From that, we can recommend r2SCAN-3c for robust quantification of this omnipresent interaction.

Bioinspired Synthesis of (-)-Hunterine A: Deciphering the Key Step in the Biogenetic Pathway

A concise, bioinspired, and enantioselective synthesis of (-)-hunterine A, an odd 6/7/6/6/5 pentacyclic natural product, is described. The key step in the synthesis of this complex structure is an interim-template directed 6-exo selective epoxide ring-opening reaction, which is interwoven with a hydrolysis step of the indolenine hemiaminal template to create the unusual 7-membered azepine bridge motif. Our work not only refines the previously proposed biogenetic pathway, but also reveals the possible stereochemical prerequisite of the unique skeletal rearrangement, which provides a vantage point for understanding how (-)-hunterine A is likely to be generated in nature.

A free radical interlocking co-deposition strategy based on the oxidative pyrolysis mechanism of polyethylene terephthalate to achieve green energy recovery

Accidental combustion and energy recovery of polyethylene terephthalate (PET) result in the formation of harmful organic substances and excessive emissions of CO2 and CO. This paper presents our recent efforts to unravel the formation mechanism of these harmful substances during the PET combustion process using thermal analysis and simulation calculations (DFT, CDFT, and ReaxFF). Our findings reveal that PET oxidative pyrolysis produces free radicals, harmful small molecule gases, and CO2. The interaction between aromatic free radicals and oxygen initiates unstable peroxy bonds, triggering uncontrollable chain exothermic reactions and producing oxygenated polycyclic aromatic hydrocarbon (OPAH) precursors. We propose a straightforward and eco-friendly free radical interlocking co-deposition inhibition strategy for PET by incorporating polycarbonate (PC). This strategy aims to facilitate green energy recovery by curbing OPAH formation and reducing CO2 and CO emissions during PET waste combustion. Our investigation into the oxidative pyrolysis of PET challenges conventional wisdom dominated by C-H bond fracture, paving the way for efficient, low-pollution green energy recovery.

Tetramethyl Cucurbit[6]uril-Porphyrin Supramolecular Polymer Enhances Photosensitization

Porphyrins serve as photosensitizers (PS) in the realm of cancer photodynamic therapy (PDT). Upon excitation by laser light, porphyrins are capable of converting molecular oxygen into highly cytotoxic singlet oxygen (1O2). However, the rigid π-conjugated structure of porphyrins frequently results in the formation of aggregates in aqueous solutions, which leads to the self-quenching of the excited state. Cucurbit[n]urils exhibit the capacity to stably bind with porphyrins via host-guest interactions, effectively inhibiting their aggregation and potentially enhancing the therapeutic efficacy of PDT. In this study, water-soluble tetramethyl cucurbit[6]uril (TMeQ[6]) was selected as the host, while four propionic acid group-appended porphyrin cationic (TPPOR) was utilized as guests to construct a supramolecular photosensitizer (TPPOR-2TMeQ[6]) in a molar ratio of 2:1. Further experimental findings demonstrate that the presence of TMeQ[6] inhibits the aggregation of TPPOR through non-covalent interactions. This inhibition reduces the energy difference between the excited singlet and triplet states, thereby enhancing the conversion efficiency of 1O2. Moreover, TPPOR-2TMeQ[6] exhibits favorable biocompatibility and minimal dark toxicity against breast cancer cells (4T1). Upon intracellular excitation, the levels of reactive oxygen species (ROS) significantly increase, inducing oxidative stress in 4T1 cells and leading to apoptosis. Consequently, the findings of this study suggest that the enhanced photosensitization achieved through this supramolecular approach is likely to promote the anticancer therapeutic effects of PDT, thereby broadening the application prospects of porphyrins within PDT systems.

Molecular Decoration and Unconventional Double Bond Migration in Irumamycin Biosynthesis

Irumamycin (Iru) is a complex polyketide with pronounced antifungal activity produced by a type I polyketide (PKS) synthase. Iru features a unique hemiketal ring and an epoxide group, making its biosynthesis and the structural diversity of related compounds particularly intriguing. In this study, we performed a detailed analysis of the iru biosynthetic gene cluster (BGC) to uncover the mechanisms underlying Iru formation. We examined the iru PKS, including the domain architecture of individual modules and the overall spatial structure of the PKS, and uncovered discrepancies in substrate specificity and iterative chain elongation. Two potential pathways for the formation of the hemiketal ring, involving either an olefin shift or electrocyclization, were proposed and assessed using 18O-labeling experiments and reaction activation energy calculations. Based on our findings, the hemiketal ring is likely formed by PKS-assisted double bond migration and TE domain-mediated cyclization. Furthermore, putative tailoring enzymes mediating epoxide formation specific to Iru were identified. The revealed Iru biosynthetic machinery provides insight into the complex enzymatic processes involved in Iru production, including macrocycle sculpting and decoration. These mechanistic details open new avenues for a targeted architecture of novel macrolide analogs through synthetic biology and biosynthetic engineering.

A comprehensive guide for accurate conformational energies of microsolvated Li+ clusters with organic carbonates

Organic carbonates and their mixtures are frequently used in electrolyte solutions in lithium-ion batteries. Rationalization and tuning of the related Li+ solvation processes are rooted in the proper identification of the representative low-energy spatial structures of the microsolvated Li+(S)n clusters. In this study, we introduce an automatically generated database of conformational energies (CEs), LICARBCONF806, comprising 806 diverse conformers of Li+ clusters with 7 common organic carbonates. A number of standard and composite density functional theory (DFT) approaches and fast semi-empirical methods are examined to reproduce the reference CEs obtained at the RI-SCS-MP2/CBS level of theory. A hybrid PBE0-D4 functional paired with the def2-QZVP basis set is the most robust in reproducing the reference values while composite B97-3c demonstrates the best cost-benefit ratio. Contemporary tight-binding semi-empirical methods GFNn-xTB can be used for the filtering of high-energy structures, but their performance worsens significantly when the limited number of low-energy (CE < 3 kcal mol-1) conformers are to be sorted. Thermal corrections used to convert electronic energies to respective Gibbs free energies and especially corrections imposed by a continuum solvation model can significantly influence both the conformer ranking and the width of the CE distribution. These should be appropriately taken into account to identify lowest energy conformers in solution and at non-zero temperatures. The almost black-box conformation generation workflow used in this work successfully predicts representitative low-energy four-coordinated conformers of Li+ clusters with cyclic carbonates and unravels the complex conformational nature of the clusters with flexible linear carbonates.

Phase-dependent polymerization isomerism in the coordination complexes of a flexible bis(β-diketonato) ligand

First prepared in the late 70s, the pro-ligand 1,3-bis(3,5-dioxo-1-hexyl)benzene (H2bdhb) contains two acetoacetyl terminations linked to a central 1,3-phenylene unit through dimethylene bridges. Since each termination can be either in diketonic or keto-enolic form, in organic solution it exists as a mixture of three spectroscopically resolvable tautomers. In the presence of pyridine, Co2+ and the bdhb2- anion form a crystalline dimeric compound with formula [Co2(bdhb)2(py)4] (2) and a Co⋯Co separation of more than 11 Å. Complex 2 contains two pseudo-octahedrally coordinated and non-interacting high-spin cobalt(II) ions (S = 3/2) displaying a large easy-plane anisotropy (D ∼ 70 cm-1), as consistently indicated by magnetic measurements, X-band EPR spectra, and complete active space self-consistent field/N-electron valence state perturbation theory (CASSCF/NEVPT2) calculations. At cryogenic temperatures (T < 7 K) and in an applied static magnetic field, the compound shows detectably slow magnetic relaxation, which occurs through direct and Raman mechanisms. Combined mass spectrometry, UV-Vis, and 1H/2H NMR data, including an isotopic labelling experiment and a determination of molecular weight by diffusion ordered spectroscopy (DOSY), show that 2 rearranges to monomeric high-spin [Co(bdhb)(py)x] species (x = 0, 1, or 2) in organic solution (CH2Cl2, THF) with concomitant partial dissociation of the py ligands. The X-band EPR spectra in a frozen CH2Cl2/toluene matrix concurrently suggest a significant alteration of the coordination environment upon dissolution. These observations are fairly well reproduced by density functional theory (DFT) and CASSCF/NEVPT2 calculations on the lowest Gibbs free energy conformers of each species, as provided by an extensive conformational search based on meta-dynamics simulations and semiempirical tight-binding methods. After the vanadyl analogue, compound 2 provides the second example of polymerization isomerism in the 1 : 1 adducts of bdhb2- with divalent metal ions.

The Bond Energy of the Carbon Skeleton in Polyaromatic Halohydrocarbon Molecules

We have investigated the thermochemical stability of the carbon skeleton in polycyclic aromatic (halo) hydrocarbons using a systematic collection of molecules (the PAHH343 set). With high-level quantum chemistry methods such as W1X-2, we have obtained chemically accurate (i. e.,±~5 kJ mol-1) "normalized carbon skeleton" bond energies. They are calculated by removing the C-H and C-X (X=F, Cl) bond energies from the total atomization energy, and then normalizing on a per-carbon basis. For species with isomeric halogen-substitution pattern, the energetic variation is generally small, though larger difference can also be seen due to structural distortion from steric repulsion. The skeleton energy becomes smaller with an increasing number of halogen atoms due to the withdrawal of electron density from the bonding orbitals, mainly through the σ-bonds. We have further assessed the performance of some low-cost quantum chemistry methods for the PAHH343 set. The deviations from reference values are largely systematic, and can thus be compensated for, yielding errors that are on average below 10 kJ mol-1. This provides the prospect for the study of an even wider range of PAHH and related systems.

Lentinan-based pH-responsive nanoparticles achieve the combination therapy of tumors

Cancer poses a significant threat to human health, and there is an urgent need for more effective treatments. Combining chemotherapy and immunotherapy is an effective strategy to enhance curative outcomes and holds great potential for widespread application. The natural phytochemical genistein (GEN) exhibits cytotoxicity against tumors and is a potential chemotherapeutic agent. Lentinan (LTN) is a natural polysaccharide with immune-enhancing properties that has been utilized in tumor treatment. This study constructed a pH-responsive nanoparticle GEN@LTN-BDBA with chemotherapy and immunotherapy functions using GEN and LTN. After characterizing the nanoparticles, the molecular mechanism of GEN@LTN-BDBA formation was explored using in silico simulation. GEN@LTN-BDBA can significantly inhibit the proliferation of A549 and HepG2 cells in vitro. The in vivo experiment results demonstrated that treatment with GEN@LTN-BDBA can significantly reduce tumor cell mass and prevent metastasis. In this nanoparticle, GEN induced oxidative stress and apoptosis of tumor cells. Meanwhile, the released LTN initiated an anti-tumor immune response by promoting dendritic cell (DC) maturation and upregulating the expression of costimulatory molecules and major histocompatibility complex. The construction method of GEN@LTN-BDBA can be extended to the preparation of other polysaccharides and hydrophobic chemotherapy molecules, offering a novel strategy to enhance the efficacy of monotherapy.

Predicting redox potentials by graph-based machine learning methods

The evaluation of oxidation and reduction potentials is a pivotal task in various chemical fields. However, their accurate prediction by theoretical computations, which is a complementary task and sometimes the only alternative to experimental measurement, may be often resource-intensive and time-consuming. This paper addresses this challenge through the application of machine learning techniques, with a particular focus on graph-based methods (such as graph edit distances, graph kernels, and graph neural networks) that are reviewed to enlighten their deep links with theoretical chemistry. To this aim, we establish the ORedOx159 database, a comprehensive, homogeneous (with reference values stemming from density functional theory calculations), and reliable resource containing 318 one-electron reduction and oxidation reactions and featuring 159 large organic compounds. Subsequently, we provide an instructive overview of the good practice in machine learning and of commonly utilized machine learning models. We then assess their predictive performances on the ORedOx159 dataset through extensive analyses. Our simulations using descriptors that are computed in an almost instantaneous way result in a notable improvement in prediction accuracy, with mean absolute error (MAE) values equal to 5.6 kcal mol- 1 for reduction and 7.2 kcal mol- 1 for oxidation potentials, which paves a way toward efficient in silico design of new electrochemical systems.

Controlling achiral and chiral conformations of benzyl alcohol by ortho-halogenation, collisional relaxation and dimerisation

Ortho-Halogenated benzyl alcohol can exist in two different low energy chiral conformations, only one of them with an OH-X contact (X = Cl, Br, I). A third, achiral conformation is enabled by the halogen substitution. We show by IR spectroscopy in supersonic jets that the achiral monomer is less stable than the chiral conformation with OH-X contact, but both can be produced in similar amounts using helium as a carrier gas. The robust OH transition observed for the achiral monomer is a sensitive benchmark for the conformational energy sequence, since the chiral conformation without OH-X contact is at least an order of magnitude less abundant, although it is often predicted by DFT to be slightly more stable and separated from the achiral conformation by a low barrier. This competing chiral conformation must be energetically higher by at least a few tenths of a kJ mol-1 to be consistent with experimental observations. That is indeed predicted by high-level energy calculations at the DFT-optimised structures. The most stable dimers of ortho-halogenated benzyl alcohols involve torsionally homo- and heterochiral pairings of the two OH groups, where the hydrogen bond-accepting OH group forms a cooperative intramolecular OH-X contact. The achiral monomer conformation is suppressed in these dimers. A homochiral dimer is formed almost exclusively for Cl, whereas its heterochiral variant is progressively co-stabilised with increasing halogen size. The stretching wavenumber of the donor OH in the dimers depends on the relative chirality of the donor and acceptor conformations. The consistent picture that emerges for Cl, Br and I substitution in ortho-position of benzyl alcohol is discussed in the context of interconversion barriers, heavy atom tunneling, π-π stacking, suppression of OH-π bonding, chirality synchronisation, and shortcomings of DFT approaches in reproducing the observations. The homochiral aggregation preference observed for simple benzyl alcohol is conserved and even enhanced upon ortho-halogenation, albeit partly by different interactions.

Cryptate binding energies towards high throughput chelator design: metadynamics ensembles with cluster-continuum solvation

A tiered forcefield/semiempirical/meta-GGA pipeline together with a thermodynamic scheme designed with error cancellation in mind was developed to calculate binding energies of [2.2.2] cryptate complexes of mono- and divalent cations. Stable complexes of Na, K, Rb, Ca, Zn and Pb were generated, revealing consistent cation-N lengths but highly variable cation-O lengths and an amine stacking mechanism potentially augmenting the cation size selectivity. Metadynamics, used for searching the high-dimensional potential energy surface, together with a cluster-continuum model for affordable - yet accurate - solvation modeling, enabled the discovery of more stable geometries than those previously reported. Similar solvation energy curve shapes for lone vs. coordinated ions enabled rapid solvation convergence via the cancellation of errors stemming from finite cluster sizes. An R2 of 0.850 vs. experimental aqueous binding energies was obtained, validating this scheme as the backbone of a high-throughput workflow for chelator design.

Machine learning-driven investigation of the structure and dynamics of the BMIM-BF4 room temperature ionic liquid

Room-temperature ionic liquids are an exciting group of materials with the potential to revolutionize energy storage. Due to their chemical structure and means of interaction, they are challenging to study computationally. Classical descriptions of their inter- and intra-molecular interactions require time intensive parametrization of force-fields which is prone to assumptions. While ab initio molecular dynamics approaches can capture all necessary interactions, they are too slow to achieve the time and length scales required. In this work, we take a step towards addressing these challenges by applying state-of-the-art machine-learned potentials to the simulation of 1-butyl-3-methylimidazolium tetrafluoroborate. We demonstrate a learning-on-the-fly procedure to train machine-learned potentials from single-point density functional theory calculations before performing production molecular dynamics simulations. Obtained structural and dynamical properties are in good agreement with computational and experimental references. Furthermore, our results show that hybrid machine-learned potentials can contribute to an improved prediction accuracy by mitigating the inherent shortsightedness of the models. Given that room-temperature ionic liquids necessitate long simulations to address their slow dynamics, achieving an optimal balance between accuracy and computational cost becomes imperative. To facilitate further investigation of these materials, we have made our IPSuite-based training and simulation workflow publicly accessible, enabling easy replication or adaptation to similar systems.

Massive Assessment of the Geometries of Atmospheric Molecular Clusters

Atmospheric molecular clusters are important for the formation of new aerosol particles in the air. However, current experimental techniques are not able to yield direct insight into the cluster geometries. This implies that to date there is limited information about how accurately the applied computational methods depict the cluster structures. Here we massively benchmark the molecular geometries of atmospheric molecular clusters. We initially assessed how well different DF-MP2 approaches reproduce the geometries of 45 dimer clusters obtained at a high DF-CCSD(T)-F12b/cc-pVDZ-F12 level of theory. Based on the results, we find that the DF-MP2/aug-cc-pVQZ level of theory best resembles the DF-CCSD(T)-F12b/cc-pVDZ-F12 reference level. We subsequently optimized 1283 acid-base cluster structures (up to tetramers) at the DF-MP2/aug-cc-pVQZ level of theory and assessed how more approximate methods reproduce the geometries. Out of the tested semiempirical methods, we find that the newly parametrized atmospheric molecular cluster extended tight binding method (AMC-xTB) is most reliable for locating the correct lowest energy configuration and yields the lowest root mean square deviation (RMSD) compared to the reference level. In addition, we find that the DFT-3c methods show similar performance as the usually employed ωB97X-D/6-31++G(d,p) level of theory at a potentially reduced computational cost. This suggests that these methods could prove to be valuable for large-scale screening of cluster structures in the future.

Ultrafast Two-Color X-Ray Emission Spectroscopy Reveals Excited State Landscape in a Base Metal Dyad

Effective photoinduced charge transfer makes molecular bimetallic assemblies attractive for applications as active light-induced proton reduction systems. Developing competitive base metal dyads is mandatory for a more sustainable future. However, the electron transfer mechanisms from the photosensitizer to the proton reduction catalyst in base metal dyads remain so far unexplored. A Fe─Co dyad that exhibits photocatalytic H2 production activity is studied using femtosecond X-ray emission spectroscopy, complemented by ultrafast optical spectroscopy and theoretical time-dependent DFT calculations, to understand the electronic and structural dynamics after photoexcitation and during the subsequent charge transfer process from the FeII photosensitizer to the cobaloxime catalyst. This novel approach enables the simultaneous measurement of the transient X-ray emission at the iron and cobalt K-edges in a two-color experiment. With this methodology, the excited state dynamics are correlated to the electron transfer processes, and evidence of the Fe→Co electron transfer as an initial step of proton reduction activity is unraveled.

Mapping the correlations between bandgap, HOMO, and LUMO trends for meta substituted Zn-MOFs

Bandgap is a key property that determines electrical and optical properties in materials. Modulating the bandgap thus is critical in developing novel materials particularly semiconductors with improved features. This study examines the bandgap, highest occupied molecular orbital (HOMO), and lowest unoccupied molecular orbital (LUMO) energy level trends in a metal organic framework, metal-organic framework 5 (MOF-5), as a function of Hammett substituent effect (with the constant σm in the meta-position of the benzene ring) and solvent dielectric effect (with the constant ε). Specifically, experimental design and response surface methodologies helped to assess the significance of trends and correlations between these molecular properties with σm and ε. While the HOMO and LUMO decrease with increasing σm, the LUMO exhibits greater sensitivity to the substituent's electron withdrawing capability. The relative difference in these trends helps to explain why the bandgap tends to decrease with increasing σm.

A semi-automated quantum-mechanical workflow for the generation of molecular monolayers and aggregates

Organic electronics (OE) such as organic light-emitting diodes or organic solar cells represent an important and innovative research area to achieve global goals like environmentally friendly energy production. To accelerate OE material discovery, various computational methods are employed. For the initial generation of structures, a molecular cluster approach is employed. Here, we present a semi-automated workflow for the generation of monolayers and aggregates using the GFNn-xTB methods and composite density functional theory (DFT-3c). Furthermore, we present the novel D11A8MERO dye interaction energy benchmark with high-level coupled cluster reference interaction energies for the assessment of efficient quantum chemical and force-field methods. GFN2-xTB performs similar to low-cost DFT, reaching DFT/mGGA accuracy at two orders of magnitude lower computational cost. As an example application, we investigate the influence of the dye aggregate size on the optical and electrical properties and show that at least four molecules in a cluster model are needed for a qualitatively reasonable description.

Toward Reliable Conformational Energies of Amino Acids and Dipeptides─The DipCONFS Benchmark and DipCONL Datasets

Simulating peptides and proteins is becoming increasingly important, leading to a growing need for efficient computational methods. These are typically semiempirical quantum mechanical (SQM) methods, force fields (FFs), or machine-learned interatomic potentials (MLIPs), all of which require a large amount of accurate data for robust training and evaluation. To assess potential reference methods and complement the available data, we introduce two sets, DipCONFL and DipCONFS, which cover large parts of the conformational space of 17 amino acids and their 289 possible dipeptides in aqueous solution. The conformers were selected from the exhaustive PeptideCS dataset by Andris et al. [ J. Phys. Chem. B 2022, 126, 5949-5958]. The structures, originally generated with GFN2-xTB, were reoptimized using the accurate r2SCAN-3c density functional theory (DFT) composite method including the implicit CPCM water solvation model. The DipCONFS benchmark set contains 918 conformers and is one of the largest sets with highly accurate coupled cluster conformational energies so far. It is employed to evaluate various DFT and wave function theory (WFT) methods, especially regarding whether they are accurate enough to be used as reliable reference methods for larger datasets intended for training and testing more approximated SQM, FF, and MLIP methods. The results reveal that the originally provided BP86-D3(BJ)/DGauss-DZVP conformational energies are not sufficiently accurate. Among the DFT methods tested as an alternative reference level, the revDSD-PBEP86-D4 double hybrid performs best with a mean absolute error (MAD) of 0.2 kcal mol-1 compared with the PNO-LCCSD(T)-F12b reference. The very efficient r2SCAN-3c composite method also shows excellent results, with an MAD of 0.3 kcal mol-1, similar to the best-tested hybrid ωB97M-D4. With these findings, we compiled the large DipCONFL set, which includes over 29,000 realistic conformers in solution with reasonably accurate r2SCAN-3c reference conformational energies, gradients, and further properties potentially relevant for training MLIP methods. This set, also in comparison to DipCONFS, is used to assess the performance of various SQM, FF, and MLIP methods robustly and can complement training sets for those.

High Rotational Barrier Atropisomers

Atropisomers have attracted a great deal of attention lately due to their numerous applications in organic synthesis and to their employment in drug discovery. However, the synthetic arsenal at our disposal with which to access them remains limited. The research described herein is two-pronged; we both demonstrate the use of MCR chemistry as a synthetic strategy for the de novo synthesis of a class of atropisomers having high barriers to rotation with the simultaneous insertion of multiple chiral elements and we study these unprecedented molecular systems by employing a combination of crystallography, NMR and DFT calculations. By fully exploiting the synthetic capabilities of our chemistry, we have been able to monitor a range of different types of interaction, i. e. π-π, CH-π, heteroatom-π and CD-π, in order to conduct structure-property studies. The results could be applied both to atroposelective synthesis and in drug discovery.

Emerging Conformational-Analysis Protocols from the RTCONF55-16K Reaction Thermochemistry Conformational Benchmark Set

RTCONF55-16K is a new, reactive conformational data set based on cost-efficient methods to assess different conformational analysis protocols. Our reference calculations underpinned the accuracy of the CENSO (Grimme et al. J. Phys. Chem. A, 2021, 125, 4039) procedure and resulted in alternative recipes with different cost-accuracy compromises. Our general-purpose and economical protocols (CENSO-light and zero, respectively) were found to be 10-30 times faster than the original algorithm, adding only 0.4-0.7 kcal/mol absolute error to the relative free energy estimates.

Cryo-EM structures of a mycobacterial ABC transporter that mediates rifampicin resistance

Drug-resistant Tuberculosis (TB) is a global public health problem. Resistance to rifampicin, the most effective drug for TB treatment, is a major growing concern. The etiological agent, Mycobacterium tuberculosis (Mtb), has a cluster of ATP-binding cassette (ABC) transporters which are responsible for drug resistance through active export. Here, we describe studies characterizing Mtb Rv1217c-1218c as an ABC transporter that can mediate mycobacterial resistance to rifampicin and have determined the cryo-electron microscopy structures of Rv1217c-1218c. The structures show Rv1217c-1218c has a type V exporter fold. In the absence of ATP, Rv1217c-1218c forms a periplasmic gate by two juxtaposed-membrane helices from each transmembrane domain (TMD), while the nucleotide-binding domains (NBDs) form a partially closed dimer which is held together by four salt-bridges. Adenylyl-imidodiphosphate (AMPPNP) binding induces a structural change where the NBDs become further closed to each other, which downstream translates to a closed conformation for the TMDs. AMPPNP binding results in the collapse of the outer leaflet cavity and the opening of the periplasmic gate, which was proposed to play a role in substrate export. The rifampicin-bound structure shows a hydrophobic and periplasm-facing cavity is involved in rifampicin binding. Phospholipid molecules are observed in all determined structures and form an integral part of the Rv1217c-1218c transporter system. Our results provide a structural basis for a mycobacterial ABC exporter that mediates rifampicin resistance, which can lead to different insights into combating rifampicin resistance.

Partial to Total Generation of 3D Transition-Metal Complexes

The design of transition-metal complexes (TMCs) has drawn much attention over the years because of their important applications as metallodrugs and functional materials. In this work, we present an extension of our recently reported approach, LigandDiff [Jin et al. J. Chem. Theory Comput. 20, 4377(2024)]. The new model, which we call multi-LigandDiff, is more flexible and greatly outperforms its predecessor. This scaffold-based diffusion model allows de novo ligand design with either existing ligands or without any ligand. Moreover, it allows users to predefine the denticity of the generated ligand. Our results indicate that multi-LigandDiff can generate well-defined ligands and is transferable to multiple transition metals and coordination geometries. In terms of its application, multi-LigandDiff successfully designed 338 Fe(II) spin-crossover (SCO) complexes from only 47 experimentally validated SCO complexes. And these generated complexes are configurationally diverse and structurally reasonable. Overall, the results show that multi-LigandDiff is an ideal tool to design novel TMCs from scratch.

State-of-the-art local correlation methods enable affordable gold standard quantum chemistry for up to hundreds of atoms

In this feature, we review the current capabilities of local electron correlation methods up to the coupled cluster model with single, double, and perturbative triple excitations [CCSD(T)], which is a gold standard in quantum chemistry. The main computational aspects of the local method types are assessed from the perspective of applications, but the focus is kept on how to achieve chemical accuracy (i.e., <1 kcal mol-1 uncertainty), as well as on the broad scope of chemical problems made accessible. The performance of state-of-the-art methods is also compared, including the most employed DLPNO and, in particular, our local natural orbital (LNO) CCSD(T) approach. The high accuracy and efficiency of the LNO method makes chemically accurate CCSD(T) computations accessible for molecules of hundreds of atoms with resources affordable to a broad computational community (days on a single CPU and 10-100 GB of memory). Recent developments in LNO-CCSD(T) enable systematic convergence and robust error estimates even for systems of complicated electronic structure or larger size (up to 1000 atoms). The predictive power of current local CCSD(T) methods, usually at about 1-2 order of magnitude higher cost than hybrid density functional theory (DFT), has become outstanding on the palette of computational chemistry applicable for molecules of practical interest. We also review more than 50 LNO-based and other advanced local-CCSD(T) applications for realistic, large systems across molecular interactions as well as main group, transition metal, bio-, and surface chemistry. The examples show that properly executed local-CCSD(T) can contribute to binding, reaction equilibrium, rate constants, etc. which are able to match measurements within the error estimates. These applications demonstrate that modern, open-access, and broadly affordable local methods, such as LNO-CCSD(T), already enable predictive computations and atomistic insight for complicated, real-life molecular processes in realistic environments.

Halogen-Bonded Organic Frameworks (XOFs) Based on N⋅⋅⋅Br+⋅⋅⋅N Bonds: Robust Organic Networks Constructed by Fragile Bonds

Organic frameworks face a trade-off between the framework stability and the bond dynamics, which necessitates the development of innovative linkages that can generate stable frameworks without hindering efficient synthesis. Although iodine(I)-based halogen-bonded organic frameworks (XOFs) have been developed, constructing XOFs based on bromine(I) is desirable yet challenging due to the high sensitivity of bromine(I) species. In this work, we present the inaugural construction of stable bromine(I)-bridged two-dimensional (2D) halogen-bonded organic frameworks, XOF(Br)-TPy-BF4/OTf, based on sensitive [N⋅⋅⋅Br⋅⋅⋅N]+ halogen bonds. The formation of XOF(Br)-TPy-BF4/OTf was monitored by 1H NMR, XPS, IR, SEM, TEM, HR-TEM, SEAD. Their framework structures were established by the results from PXRD, theoretical simulations and SAXS. More importantly, XOF(Br) displayed excellent chemical and thermal stabilities. They exhibited stable two-dimensional framework structures in various organic solvents and aqueous media, even over a wide pH range (pH 3-12), while the corresponding model compounds BrPy2BF4/OTf decomposed quickly even in the presence of minimal water. Furthermore, the influence of the counterions were investigated by replacing BF4 with OTf, which improved the stability of XOF(Br). This characteristic enabled XOF(Br) to serve as an efficient oxidizing reagent in aqueous environments, in contrast with the sensitivity of BrPy2BF4/OTf, which performed well only in organic media. This study not only deepens our fundamental understanding of organic frameworks but also opens new avenues for the development and application of multifunctional XOFs.

Molecular Interactions of Perfluorinated and Branched Fluorine-Free Surfactants at Interfaces: Insights from a New Reliable Force Field

Per- and polyfluoroalkyl substances (PFAS) constitute a class of synthetic compounds with exceptional interfacial properties. Their widespread use in many industrial applications and consumer products, combined with their remarkable chemical and thermal stability, has led to their ubiquitous presence in environmental matrices, including surface water and groundwater. To replace PFAS with fluorine-free surfactants, it is necessary first to develop a deep molecular-level understanding of the mechanisms responsible for the exceptional properties of PFAS. For instance, it has been shown that fluorine-free surfactants with highly branched or methylated chains can achieve low surface tensions at air-water interfaces and can provide highly hydrophobic surface coatings. Although molecular simulations combined with experiments are promising for uncovering these mechanisms, the reliability of simulation results depends strongly on the accuracy of the force fields implemented. At the moment, atomistic force fields are not available to describe PFAS in a variety of environments. Ab initio methods could help fill this knowledge gap, but they are computationally demanding. As an alternative, ab initio calculations could be used to develop accurate force fields for atomistic simulations. In this work, a new algorithm is proposed, which, built from accurate ab initio calculations, yields force fields for perfluorinated sulfonic and perfluoroalkyl acids. The accuracy of the new force field was benchmarked against solvation free energy and interfacial tension data. The new force fields were then used to probe the interfacial behavior of the PFAS surfactants. The interfacial properties observed in our simulations were compared with those manifested by two branched fluorine-free surfactants. The good agreement achieved with experiments and ab initio calculations suggests that the proposed protocol could be implemented to study other perfluorinated substances and help in the design of fluorine-free surfactants for targeted applications.

dxtb-An efficient and fully differentiable framework for extended tight-binding

Automatic differentiation (AD) emerged as an integral part of machine learning, accelerating model development by enabling gradient-based optimization without explicit analytical derivatives. Recently, the benefits of AD and computing arbitrary-order derivatives with respect to any variable were also recognized in the field of quantum chemistry. In this work, we present dxtb-an open-source, fully differentiable framework for semiempirical extended tight-binding (xTB) methods. Developed entirely in Python and leveraging PyTorch for array operations, dxtb facilitates extensibility and rapid prototyping while maintaining computational efficiency. Through comprehensive code vectorization and optimization, we essentially reach the speed of compiled xTB programs for high-throughput calculations of small molecules. The excellent performance also scales to large systems, and batch operability yields additional benefits for execution on parallel hardware. In particular, energy evaluations are on par with existing programs, whereas the speed of automatically differentiated nuclear derivatives is only 2 to 5 times slower compared to their analytical counterparts. We showcase the utility of AD in dxtb by calculating various molecular and spectroscopic properties, highlighting its capacity to enhance and simplify such evaluations. Furthermore, the framework streamlines optimization tasks and offers seamless integration of semiempirical quantum chemistry in machine learning, paving the way for physics-inspired end-to-end differentiable models. Ultimately, dxtb aims to further advance the capabilities of semiempirical methods, providing an extensible foundation for future developments and hybrid machine learning applications. The framework is accessible at https://github.com/grimme-lab/dxtb.

Extension of the D3 and D4 London dispersion corrections to the full actinides series

Efficient dispersion corrections are an indispensable component of modern density functional theory, semi-empirical quantum mechanical, and even force field methods. In this work, we extend the well established D3 and D4 London dispersion corrections to the full actinides series, francium, and radium. To keep consistency with the existing versions, the original parameterization strategy of the D4 model was only slightly modified. This includes improved reference Hirshfeld atomic partial charges at the ωB97M-V/ma-def-TZVP level to fit the required electronegativity equilibration charge (EEQ) model. In this context, we developed a new actinide data set called AcQM, which covers the most common molecular actinide compound space. Furthermore, the efficient calculation of dynamic polarizabilities that are needed to construct CAB6 dispersion coefficients was implemented into the ORCA program package. The extended models are assessed for the computation of dissociation curves of actinide atoms and ions, geometry optimizations of crystal structure cutouts, gas-phase structures of small uranium compounds, and an example extracted from a small actinide complex protein assembly. We found that the novel parameterizations perform on par with the computationally more demanding density-dependent VV10 dispersion correction. With the presented extension, the excellent cost-accuracy ratio of the D3 and D4 models can now be utilized in various fields of computational actinide chemistry and, e.g., in efficient composite DFT methods such as r2SCAN-3c. They are implemented in our freely available standalone codes (dftd4, s-dftd3) and the D4 version will be also available in the upcoming ORCA 6.0 program package.

Dynamic and solid-state behaviour of bromoisotrianglimine

Solid-state materials formed from discrete imine macrocycles have potential in industrial separations, but dynamic behaviour during both synthesis and crystallisation makes them challenging to exploit. Here, we explore opportunities for structural control by investigating the dynamic nature of a C-5 brominated isotrianglimine in solution and under crystallisation conditions. In solution, the equilibrium between the [3 + 3] and the less reported [2 + 2] macrocycle was investigated, and both macrocycles were fully characterised. Solvent templating during crystallisation was used to form new packing motifs for the [3 + 3] macrocycle and a previously unreported [4 + 4] macrocycle. Finally, chiral self-sorting was used to demonstrate how crystallisation conditions can not only influence packing arrangements but also shift the macrocycle equilibrium to yield new structures. This work thus exemplifies three strategies for exploiting dynamic behaviour to form isotrianglimine materials, and highlights the importance of understanding the dynamic behaviour of a system when designing and crystallising functional materials formed using dynamic covalent chemistry.

Quantum chemical package Jaguar: A survey of recent developments and unique features

This paper is dedicated to the quantum chemical package Jaguar, which is commercial software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific features that are relevant to chemical research as well as describe those aspects of the program that are pertinent to the user interface, the organization of the computer code, and its maintenance and testing. Among the scientific topics that feature prominently in this paper are the quantum chemical methods grounded in the pseudospectral approach. A number of multistep workflows dependent on Jaguar are covered: prediction of protonation equilibria in aqueous solutions (particularly calculations of tautomeric stability and pKa), reactivity predictions based on automated transition state search, assembly of Boltzmann-averaged spectra such as vibrational and electronic circular dichroism, as well as nuclear magnetic resonance. Discussed also are quantum chemical calculations that are oriented toward materials science applications, in particular, prediction of properties of optoelectronic materials and organic semiconductors, and molecular catalyst design. The topic of treatment of conformations inevitably comes up in real world research projects and is considered as part of all the workflows mentioned above. In addition, we examine the role of machine learning methods in quantum chemical calculations performed by Jaguar, from auxiliary functions that return the approximate calculation runtime in a user interface, to prediction of actual molecular properties. The current work is second in a series of reviews of Jaguar, the first having been published more than ten years ago. Thus, this paper serves as a rare milestone on the path that is being traversed by Jaguar's development in more than thirty years of its existence.

Molecular simulations guide immobilization of lipase on nest-like ZIFs with regulatable hydrophilic/hydrophobic surface

The catalytic performance of immobilized lipase is greatly influenced by functional support, which attracts growing interest for designing supports to achieve their promotive catalytic activity. Many lipases bind strongly to hydrophobic surfaces where they undergo interfacial activation. Herein, the behavioral differences of lipases with distinct lid structures on interfaces of varying hydrophobicity levels were firstly investigated by molecular simulations. It was found that a reasonable hydrophilic/hydrophobic surface could facilitate the lipase to undergo interfacial activation. Building on these findings, a novel "nest"-like superhydrophobic ZIFs (ZIFN) composed of hydrophobic ligands was prepared for the first time and used to immobilize lipase from Aspergillus oryzae (AOL@ZIFN). The AOL@ZIFN exhibited 2.0-folds higher activity than free lipase in the hydrolysis of p-Nitrophenyl palmitate (p-NPP). Especially, the modification of superhydrophobic ZIFN with an appropriate amount of hydrophilic tannic acid can significantly improve the activity of the immobilized lipase (AOL@ZIFN-TA). The AOL@ZIFN-TA exhibited 30-folds higher activity than free lipase, and still maintained 82% of its initial activity after 5 consecutive cycles, indicating good reusability. These results demonstrated that nanomaterials with rational arrangement of the hydrophilic/hydrophobic surface could facilitate the lipase to undergo interfacial activation and improve its activity, displaying the potential of the extensive application.

Use of Interfacial Interactions and Complexation of Carbon Dots to Construct Ultra-Robust and Efficient Photothermal Film From Micro-Carbonized Polysaccharides

Solar energy conversion technologies, particularly solar-driven photothermal conversion, are both clean and manageable. Although much progress has been made in designing solar-driven photothermal materials, significant challenges remain, not least the photobleaching of organic dyes. To tackle these issues, micro-carbonized polysaccharide chains, with carbon dots (CDs) suspended from the chains, are conceived, just like grapes or tomatoes hanging from a vine. Carbonization of sodium carboxymethyl cellulose (CMC) produces just such a structure (termed CMC-g-CDs), which is used to produce an ultra-stable, robust, and efficient solar-thermal film by interfacial interactions within the CMC-g-CDs. The introduction of the CDs into the matrix of the photothermal material effectively avoided the problem of photobleaching. Manipulating the interfacial interactions (such as electrostatic interactions, van der Waals interactions, π-π stacking, and hydrogen bonding) between the CDs and the polymer chains markedly enhances the mechanical properties of the photothermal film. The CMC-g-CDs are complexed with Fe3+ to eliminate leakage of the photothermal reagent from the matrix and to solve the problem of poor water resistance. The resulting film (CMC-g-CDs-Fe) has excellent prospects for practical application as a photothermal film.

ΔDFT Predicts Inverted Singlet-Triplet Gaps with Chemical Accuracy at a Fraction of the Cost of Wave Function-Based Approaches

Efficient OLEDs need to quickly convert singlet and triplet excitons into photons. Molecules with an inverted singlet-triplet energy gap (INVEST) are promising candidates for this task. However, typical INVEST molecules have drawbacks like too low oscillator strengths and excitation energies. High-throughput screening could identify suitable INVEST molecules, but existing methods are problematic: The workhorse method TD-DFT cannot reproduce gap inversion, while wave function-based methods are too slow. This study proposes a state-specific method based on unrestricted Kohn-Sham DFT with common hybrid functionals. Tuned on the new INVEST15 benchmark set, this method achieves an error of less than 1 kcal/mol, which is traced back to error cancellation between spin contamination and dynamic correlation. Applied to the larger and structurally diverse NAH159 set in a black-box fashion, the method maintains a small error (1.2 kcal/mol) and accurately predicts gap signs in 83% of cases, confirming its robustness and suitability for screening workflows.

A co-assembly process for high strength and injectable dual network gels with sustained doxorubicin release performance

Adopting a non-covalent co-assembly strategy shows great potential in loading drugs efficiently and safely in drug delivery systems. However, finding an efficient method for developing high strength gels with thixotropic characteristics is still challenging. In this work, by hybridizing the low molecular weight gelator fluorenylmethyloxycarbonyl-phenylalanine (Fmoc-F) (first single network, 1st SN) and alginate (second single network, 2nd SN) into a dual network (DN) gel, gels with high strength as well as thixotropy were prepared efficiently. The DN gels showed high strength (103 Pa in SN gels and 105 Pa in DN gels) and thixotropic characteristics (yield strain <25%; recovery ratio >85% within 100 seconds). The application performance was verified by loading doxorubicin (DOX), showing better encapsulation capacity (77.06% in 1st SN, 59.11% in 2nd SN and 96.71% in DN) and sustained release performance (lasting one week under physiological conditions) than single network gels. Experimental and DFT results allowed the elaboration of the specific non-covalent co-assembly mechanism for DN gel formation and DOX loading. The DN gels were formed by co-assembly driven by H-bond and π-π stacking interactions and then strengthened by Ca2+-coupling. Most DOX molecules co-assembled with Fmoc-F and alginate through π-π stacking and H-bond interactions (DOX-I), with a few free DOX molecules (DOX-II) left. Proven by the release dynamics test, DOX was released through a diffusion-erosion process, in an order of DOX-I first and then DOX-II. This work suggests that non-covalent co-assembly is a useful technique for effective material strengthening and drug delivery.

Reconstruction of zinc-metal battery solvation structures operating from -50 ~ +100 °C

Serious solvation effect of zinc ions has been considered as the cause of the severe side reactions (hydrogen evolution, passivation, dendrites, and etc.) of aqueous zinc metal batteries. Even though the regulation of cationic solvation structure has been widely studied, effects of the anionic solvation structures on the zinc metal were rarely examined. Herein, co-reconstruction of anionic and cationic solvation structures was realized through constructing a new multi-component electrolyte (Zn(BF4)2-glycerol-boric acid-chitosan-polyacrylamide, simplified as ZGBCP), which incorporates double crosslinking network via the esterification, protonation and polymerization reactions, thereby combining multiple advantages of 'liquid-like' high conductivity, 'gel-like' robust interface, and 'solid-like' high Zn2+ transfer number. Based on the ZGBCP electrolyte, the Zn anodes achieve record-low polarization and stable cycling. Furthermore, the ZGBCP electrolyte renders the AZMBs ultrawide working temperature (-50 °C ~ +100 °C) and ultralong cycle life (30000 cycles), which further validates the feasibility of the dual solvation structure strategy and provides a innovative perspective for the development of high-performance AZMBs.

Mutual synergistic regulation of chloride anion and cesium cation binding using a new designed macrocyclic multi-functional sites receptor: A case of DFT computational prediction

The mutual synergistic regulation of the multi-functional sites on a single receptor molecule for ion-binding/recognition is vital for the new receptor design and needs to be well explored from experiment and theory. In this work, a new macrocyclic ion receptor (BEBUR) with three functional zones, including two ether holes and one biurea groups, is designed expecting to mutually enhance the ion-binding performance. The binding behaviors of BEBUR mainly for Cl- and Cs+ are deeply investigated by using density functional theoretical calculations. It is found that Cl-/Cs+ binding can be mutually enhanced and synergistically regulated via corresponding conformational changes of the receptor, well reflecting an electrical complementary matching and mutual reinforcement effect. Moreover, solvent effect calculations indicate that BEBUR may be an excellent candidate structure for Cl--binding with the enhancement of counter ion (Cs+) in water and toluene. In addition, visualization of intermolecular noncovalent interaction is used for analysis on the nature of the binding interactions between receptor and ions.

Air-Stable Arene Manganese Complexes as Catalysts for the Syngas-Assisted Direct Reductive Amination, Cyanation of Aldehyde, and CO2 Fixation by Epoxide with High Functional Groups Tolerance

Manganese complexes [(arene)Mn(CO)3]+ were prepared in one step from arenes and Mn(CO)5Br. They were found to be efficient catalysts in the carbonyl cyanation with TMSCN, CO2 fixation by epoxides, and direct reductive amination in the presence of syngas. The amination reaction tolerated various reducible functional groups. The synergy of carbon monoxide and hydrogen in syngas provides high efficiency of the catalytic system. The developed protocols do not require an inert atmosphere, and the catalysts can be handled in air.

Computational methods for investigating organic radical species

Computational analysis of organic radical species presents significant challenges. This study compares the efficacy of various DFT and wavefunction methods in predicting radical stabilisation energies, bond dissociation energies, and redox potentials for organic radicals. The hybrid meta-GGA M062X-D3(0), and the range-separated hybrids ωB97M-V and ωB97M-D3(BJ) emerged as the most reliable functionals, consistently providing accurate predictions across different basis sets including 6-311G**, cc-pVTZ, and def2-TZVP.

Solubility and Mass Transfer Performance of Ethane and n-Butane in Menthol and Decanoic Acid Deep Eutectic Solvent

The absorption performance and mechanism of the deep eutectic solvent (DES), composed of menthol and decanoic acid, were investigated. The solubility of volatile organic compounds (VOCs) in the DES was studied through saturation solution experiments, wherein the solubility of ethane and n-butane increases with a decrease in temperature and increasing pressure. Henry's law constants of ethane and n-butane in the DES at 288.2 K were 2.089 and 0.136 MPa, respectively, demonstrating the high solubility for light hydrocarbons that surpasses or equals that of ionic liquids. The mass transfer and regeneration performance of the DES were investigated by using dynamic bubbling experiments. Results demonstrated that the removal rate of both ethane and n-butane increased as the gas flow rate decreased and the VOC concentration in the model gas increased. Specifically, the removal rate of ethane reached 99.50% at a temperature of 293.2 K, a VOC concentration VOC of 10,000 μmol/mol, and a gas flow rate of 30 mL/min, while the removal rate of n-butane was higher than that of ethane under the same conditions, achieving a removal rate exceeding 99.99%. Furthermore, no significant decrease in the removal rate for n-butane was observed during the four regeneration processes. Interaction energies between the VOC molecule and DES were calculated using the quantum chemistry method. It was found that the interactions between the VOC molecule and DES are primarily attributed to dispersion attractive effects which belong to weak interactions; therefore, the absorption of light hydrocarbon by the DES belongs to a physical process. The DES has been proven to be effective for the recovery of light hydrocarbons, providing a promising approach to address the key challenge in comprehensive treatment of VOCs in the petrochemical industry.

Interfacial behaviour of short-chain fluorocarbon surfactants at the n-hexane/water interface: a molecular dynamics study

The utilization of long-chain fluorocarbon surfactants is restricted due to environmental regulations, prompting a shift in the focus of research towards short-chain fluorocarbon surfactants. The present study employs molecular dynamics techniques to model the behaviour of potassium perfluorobutylsulfonate (PFBS) at the n-hexane/water interface, aiming to investigate the efficacy of short-chain fluorocarbon surfactants in enhancing oil recovery. The findings suggest that ionized PFBS- has the ability to autonomously migrate to the oil/water interface, forming a layered thin film, with the sulfonic acid group being submerged in water, while the fluorocarbon chain is oriented towards the oil phase. This phenomenon aligns with the fundamental concept of surfactants in reducing interfacial tension between oil and water. The spontaneous dispersion process is supported by changes in the number of water molecules surrounding each PFBS- anion, as is well indicated by the number density distribution within the simulation box. Based on the analysis conducted by IGMH (Independent Gradient Model based on Hirshfeld partition), it was determined that sulfonic acid molecules are capable of forming hydrogen bonds with water molecules, whereas the interaction between fluorocarbon chains and the oil phase is predominantly characterized by weak van der Waals interactions.

Electrophotocatalysis Versus Indirect Electrolysis: Electrochemical Selenocyclization of 3-Aza-1,5-dienes Facilitated by Energy Transfer, Direct Photolysis or N-Hydroxyphthalimide

Three hybrid electrochemical protocols, which involve the energy transfer, direct photolysis and N-hydroxyphthalimide catalyst, respectively, are presented for the selenylation/cyclization of the fragile substrates of 3-aza-1,5-dienes with diorganyl diselenides to afford 3-selenomethyl-4-pyrrolin-2-ones. The two electrophotocatalytic reactions and the indirect electrolysis one are both regioselective and external-oxidant- and transition-metal-free, and are associated with a broad substrate scope and high Se-economy, and all three methods are amenable to gram-scale syntheses, late-stage functionalizations, sunlight-induced experiments and all-solar-driven syntheses.

Will We Witness Enzymatic or Pd-(Oligo)Peptide Catalysis in Suzuki Cross-Coupling Reactions?

Despite the development of numerous advanced ligands for Pd-catalyzed Suzuki cross-coupling reaction, the potential of (oligo)peptides serving as ligands remains unexplored. This study demonstrates via density functional theory (DFT) modeling that (oligo)peptide ligands can drive superior activity compared to classic phosphines in these reactions. The utilization of natural amino acids such as Met, SeMet, and His leads to strong binding of the Pd center, thereby ensuring substantial stability of the system. The increasing sustainability and economic viability of (oligo)peptide synthesis open new prospects for applying Pd-(oligo)peptide systems as greener catalysts. The feasibility of de novo engineering an artificial Pd-based enzyme for Suzuki cross-coupling is discussed, laying the groundwork for future innovations in catalytic systems.

Combining low-cost electronic structure theory and low-cost parallel computing architecture

The computational efficiency of low-cost electronic structure methods can be further improved by leveraging heterogenous computing architectures. The software package TeraChem has been developed since 2008 to make use of graphical processing units (GPUs), particularly their strong single-precision performance, for the acceleration of quantum chemical calculations. Here, we present the implementation of three low-cost methods, namely HF-3c, PBEh-3c, and the recently introduced ωB97X-3c. We show that these can benefit in terms of performance when combined with "consumer grade" GPUs by leveraging the mixed precision integral handling in TeraChem. The current limitation of the latter's GPU integral library is that Gaussian integrals only for functions with angular momentum l < 3 can be computed, which generally restricts the achievable accuracy in terms of the one-particle basis set. Particularly, the implementation of the ωB97X-3c method now enables higher accuracy with this setting which, in turn, provides the most efficient implementation accessible with consumer-grade hardware. We furthermore show that the implemented 3c methods can be combined with the hh-TDA formalism. This gives new and efficient low-cost multi-configurational excited states methods, which are benchmarked for the description of lowest vertical excitation energies in this work. All in all, the combination of these efficient electronic structure theory methods with affordable highly parallelized computing hardware provides an optimal computational and monetary cost to accuracy ratio.