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A newly synthesized one-dimensional (1D) metal-organic framework (MOF) functionalized with the (trifluoromethyl)trifluoroborate anion was characterized by single-crystal X-ray diffraction, thermogravimetric analysis, CHN elemental analysis, Fourier-transform infrared (FT-IR) spectroscopy, scanning electron microscopy, and gas adsorption and separation experiments. The 1D MOF exhibits gate-type CO2 adsorption isotherms in the temperature range of 263-303 K with rectangular hysteresis loops. The CO2 gate-adsorption pressure is strongly temperature dependent, and this dependence is relatively large compared with those of other MOFs that exhibit a similar behavior. This property, which is associated with the structural flexibility of the material, makes the studied system particularly promising for carbon dioxide capture and separation by exploiting the temperature swing adsorption (TSA) technique.
Homochirality, the uniformity in single molecular handedness, is a defining feature of life. Although universal in biology, the evolutionary advantage of selecting one enantiomer over its mirror image remains unresolved. One possible clue may lie in catalysis itself: recent studies demonstrate that oxygen evolution reaction (OER), a key step in photosynthesis, is sensitive to chirality. Here, we report that electrochemical OER performance with chiral additives may be correlated to the alignment of their electric (ETDM) and magnetic (MTDM) transition dipole moments in the lowest-energy transition. Enantiomers with parallel ETDM-MTDM configurations consistently outperform their antiparallel counterparts. Notably, this bias also manifests in natural systems, suggesting a shared stereoelectronic principle. We define this stereoelectronic correlation as the Supplementary Angle Effect (SAE). Our findings establish SAE in electrocatalysis offering a quantitative descriptor for assessing how molecular handedness affects catalytic behavior and enantiodifferential performance.
In 2024, Garg and co-workers reported that norborn-1-enes, a class of anti-Bredt olefins, can be systematically prepared and trapped. This finding has prompted us to combine multistate, multiconfigurational quantum chemical gradients and multiscale modeling to simulate the light-induced dynamics and chemistry of norborn-1-ene in acetonitrile. The results predict the existence of an excited state intermediate with a unique electronic structure consisting of a zwitterion incorporating a nonclassical cationic moiety. A set of 200 room-temperature quantum-classical trajectories were propagated to show that such intermediate decay through a unique conical intersection leads to the simultaneous formation of a carbene and a diradical as primary photoproducts. A third zwitterionic photoproduct is instead predicted to have a transient existence. Thus, our simulation not only uncovers a new type of photochemical funnel but also points to novel chemistries only accessible when anti-Bredt olefins are prepared or trapped under illumination conditions.
Protein homeostasis depends on a delicate interplay between folding and degradation, orchestrated by molecular chaperones. Among them, Hsp90 is a central hub, regulating nearly 10% of the proteome through ATP-driven conformational cycles and selective interactions with cochaperones. The glucocorticoid receptor (GR) represents a paradigmatic Hsp90 client, whose maturation requires sequential remodeling steps involving multi-protein assemblies. While cryo-EM provided snapshots of these complexes, the dynamic determinants of GR activation and the antagonistic roles of cochaperones FKBP51 and FKBP52 remain poorly understood. Here, we integrate unbiased equilibrium atomistic molecular dynamics with nonequilibrium simulations of four different Hsp90-cochaperone-client assemblies that oversee distinct steps of GR maturation to elucidate how finely tuned dynamics and coordination/communication mechanisms determine functional emergence. Perturbations encoded by ligand insertion or removal reveal steroid binding as critical for both structural stability and inter-component communication. Ligand engagement not only stabilizes GR's active conformation but also feeds back to reshape chaperone and cochaperone dynamics, thereby modulating progression through the folding pathway. Steroid binding reinforces the interface in the Hsp90-p23-GR assembly, positioning cochaperone p23 as a molecular sensor for ligand occupancy. Comparative analyses of post-maturation complexes further uncover how immunophilins FKBP51 and FKBP52, despite structural similarity, elicit divergent allosteric effects on GR conformation and Hsp90-ATPase, determining opposing client fates. Our results establish ligand binding as an active modulator of chaperone-mediated folding, linking metabolic cues (ligand presence and levels) to client maturation. More broadly, they highlight cochaperones as dynamic checkpoints that selectively bias client outcomes, revealing generalizable principles of proteostasis regulation and opportunities for therapeutic intervention.
Simulations of vibrational spectra are important for interpreting experimental data as well as understanding molecular structure and dynamics. Herein, we present an approach for the efficient and accurate incorporation of anharmonicity into such simulations. Real-time nuclear-electronic orbital time-dependent density functional theory treats specified protons quantum mechanically on the same level as the electrons, propagating the electronic and protonic densities according to the time-dependent Schrödinger equation. This approach inherently includes the anharmonicity of the quantum protons and can be combined with Ehrenfest dynamics for the classical nuclei. Herein, this real-time nuclear-electronic orbital (NEO)-Ehrenfest approach is combined with the quasiclassical trajectory (QCT) approach for generating initial conditions that include the zero-point energy of the classical nuclei, thereby enabling sampling of the anharmonic regions of the potential energy surface. The resulting NEO-QCT approach is shown to capture the anharmonic heavy nuclear motion, as well as the anharmonicity of the quantum protons, for a series of molecular systems, including HCN, HNC, FHF-, CH2O, and HCOOH. The NEO-QCT method also captures the distinct spectral features of the formate-water complex (CHO2-⋅ H2O), including the redshifted and broadened OH stretch band due to strong anharmonicity arising from hydrogen bonding and coupling between the motions of the hydrogen nuclei and the heavy nuclei. The NEO-QCT method enables computationally practical simulations of vibrational spectra of molecules that exhibit significant anharmonicity and coupling between vibrational modes.
Active antimicrobial films based on polyethylene terephthalate (PET) were developed through atomic layer deposition (ALD) and plasma sputtering to obtain ZnO (≈15 nm) and ZnO/Cu (≈18 nm) coatings. Surface characterization by X-ray photoelectron spectroscopy confirmed zinc in ZnO form and copper as Cu2O/CuO, while mass spectrometry quantified approximately 10 µg/cm2 of Zn in both samples and about 130 ng/cm2 of Cu in the ZnO/Cu films. The antimicrobial performance of the coatings was evaluated on burrata cheese and turkey fillets stored under refrigeration, assessing microbial growth and sensory quality over time. The films exhibited different effects depending on food type and the initial contamination levels. On burrata cheese, PET-ZnO moderately extended the shelf life by inhibiting Pseudomonas spp., while PET-ZnO/Cu further enhanced preservation. Cheese packaged with PET-ZnO/Cu remained acceptable for over 21 days compared to 19-20 days for the controls. More pronounced effects were observed in turkey fillets, characterized by a higher initial contamination. In control samples, Staphylococcus spp. rapidly proliferated, leading to spoilage within one day. Both active films significantly delayed microbial growth and sensory decay, with PET-ZnO/Cu providing the best performance, extending acceptability beyond two days compared to less than one day for the controls.
Excited state molecular dynamics simulations are a powerful computational tool for the study of photoinduced phenomena. These are often used in conjunction with linear response TD-DFT to get the excited state energy and its gradients. At each step of molecular dynamics simulation, the new molecular geometry is relatively close to the previous ones, suggesting that some extrapolation strategy can be applied, such that the results of the previous calculations, which are available for free, can be used to predict the result of the upcoming calculation. The prediction can then be used as a guess for the iterative solver to lower the number of iterations and thus the cost. In this contribution, we present an extension of the Grassmann extrapolation scheme to linear response TD-DFT, in which the knowledge about the manifold structure to which the solutions belong is used to make the extrapolation more accurate. The new extrapolation strategy is then tested on four systems, showing a significant acceleration of the excited state molecular dynamics.
Purpose - Clinical imaging can resolve the main coronary arteries but not the smaller side branches that penetrate the heartwall. However, precise association between the main coronary branches and the myocardial mass they perfuse is crucial to achieve a correct description of haemodynamics from the large arteries to the cardiac tissue. In this work, we use ex-vivo detailed morphometric data of human coronary microcirculation to build and validate a tool for a personalized coronary-myocardium association, and we use it in a multiscale computational model of cardiac perfusion. Methods - From the digitalized dataset of an entire human coronary microcirculation, vascular beds associated to single branches are extracted and analysed to infer patterns in epicardial branching. 3D segmentations of the coronaries with and without this information are used to generate two different myocardial subdivisions, which are compared to the one obtained from the microcirculation data. The impact on haemodynamics is assessed through computational simulations. Results - Epicardial arteries exhibit characteristic patterns of transverse branching, with branching angles ≃ 90∘ and rate of branching, with respect to the distance along the vessel, depending on the core diameter. The addition of transverse outflows to the segmentations greatly increases accuracy in the myocardial subdivision, allowing discrimination between mass perfused by the proximal and distal arterial segments. Perfusion simulations including transverse outflows show more homogeneous blood flow across the myocardium, consistently with experimental findings. Conclusions - The inclusion of transverse outflows in 3D coronary segmentations is essential to correctly capture the coronary-myocardium association and the distribution of myocardial blood flow.
In recent years, the focus on luminescent solar concentrator (LSC) materials has been renewed thanks to their properties that support their integration into PV technologies in buildings and in the urban environment. In this work, three dyes bearing push-pull units and presenting anthracene (compound 1) or 2,1,3-benzothiadiazole (BTZ-P6t, compound 2, and TBTZ-P12t, compound 3) as the central chromophore module are investigated as luminophores for the LSCs based on polyacrylate. The optical and luminescence characterization of the dyes in solution and in polyacrylate panels has been carried out to examine the impact of medium polarity and stiffening on the photophysical behavior of the dyes. The photoluminescence quantum yield (PLQY), decay times, and radiative and nonradiative rate constants have been evaluated together with the overlap integral to rationalize the reabsorption phenomena. The photophysical parameters highlight that medium polarity and matrix stiffening have an impact on the photoluminescence properties. The evaluation of the photovoltaic performance, performed by placing an edge of dye panels in contact with a silicon PV device, shows that the panels act as LSCs. In particular, compound 3 exhibits the highest value of PLQY (81%), resulting in the highest value of PV light-to-energy conversion efficiencies (ηopt%, 2.8%). This study proposes a thorough and correlated examination of the photophysical characteristics of molecular systems when the media are switched from solution to acrylate panels in order to rationalize the photovoltaic performance of the prepared LSCs. Although the prepared dye-acrylate panels fall outside accepted standard dimensions for LSC size, this study is relevant to designing chromophore architecture for enhanced efficiencies for LSCs.
We propose a TD-DFT protocol for computing unrelaxed excited-state absorption (ESA) oscillator strengths in solution. Our model is formulated within the popular PCM framework and includes both linear-response and state-specific solvent effects through the cLR2 scheme. This protocol can be applied in two regimes: fast and slow. The former corresponds to situations where the time scale of the entire photophysical process is too short to allow relaxation of the nuclear degrees of freedom of the solvent, whereas the latter allows such relaxation. For selected illustrative examples of S1-Sn ESA transitions in organic dyes, we compare solvated and gas phase transition energies, oscillator strengths, and transition dipole moments. This analysis reveals that solvent-induced shifts in oscillator strengths are predominantly driven by the variations of the transition dipole moment. The magnitude of the solvent effect is strongly system- and state-dependent. For transitions for which S0-geometry states could be unambiguously assigned to their S1-geometry counterparts, we found that the two solvation regimes can lead to significantly different effects on the ESA transition properties. This observation is further confirmed by comparing the two solvation regimes, as well as gas phase results, with experimental ESA spectra extracted from transient spectroscopy measurements. Our scheme exhibits clear improvement over the in vacuo outcomes and correctly reproduces the main regions with intense ESA, although an unambiguous choice between the two regimes remains challenging.
In this study, the design and the synthesis of a thiophene-based phosphoric acid based on a chiral decahydroquinoxaline scaffold derived from enantiopure trans-1,2-diaminocyclohexane was reported. This catalyst was then employed in stereoselective transformations such as the enantioselective Friedel-Crafts reaction of indoles with imines to afford 3-indolyl methanamines. High yields (up to 98%) and high enantioselectivities (up to 98% ee) were obtained. DFT calculations were performed to investigate the key transition states, providing mechanistic insight and confirming the origin and sense of the observed stereochemical outcome.
Computational vibrational spectroscopy beyond the harmonic approximation relies on the molecular potential and ideally dipole and possibly higher moments of charge distributions. In the past decade, there has been a paradigm shift in generating highly accurate Machine-Learned potentials (MLPs). These are precise fits to thousands of electronic energies, using modern methods of regression. With such MLPs, it is possible to combine these with a variety of post-harmonic quantum methods ranging from perturbation theory to full variational calculations. After a short review of these methods, we focus on vibrational self-consistent field and configuration interaction (VSCF + VCI) calculations, as implemented in the code MULTIMODE. Two applications of this software to complex parts of the infrared spectra of formic acid dimer and the protonated oxalate anion are presented. Two new interfaces to MULTIMODE are then given. One is a Python-based GUI to enable user-friendly input to MULTIMODE. The second interface, PyFort, which is written in Fortran, uses MLPs written in Python in MULTIMODE via a C wrapper. Demonstrations of this are given for a PhysNet potential of Meuwly and co-workers for protonated oxalate anion (C2O4H-) and for the "universal" force field MACE-OFF of Csányi and co-workers. MULTIMODE VSCF + VCI vibrational energies of C2O4H- using the PhysNet MLP agree well with those using a permutationally invariant potential, trained on the datasets used to train the PhysNet MLP. A test of the MACE-OFF interface is done for H2CO. The PyFort software for both these examples is provided in the supplementary material.
Antarctica hosts a highly endemic and diverse benthic marine fauna. Despite this biodiversity, the Antarctic marine food web remains structurally simple, rendering the ecosystem particularly vulnerable to environmental stressors. Benthic organisms, due to their sedentary nature, long lifespans, and close interaction with the sediment-water interface, are widely regarded as effective sentinels of ecological change. In this study, we extended a previously validated QuEChERS-based extraction protocol, originally developed for Adamussium colbecki organisms, to assess its applicability across additional Antarctic benthic taxa, including Sphaerotylus antarcticus, Odontaster validus, Trematomus bernacchii, and Laternula elliptica. The extraction method was used in combination with LC-MS/MS analysis for the determination of emerging contaminants in both targeted and suspect screening modes. Method performance was evaluated for 23 targeted emerging contaminants (ECs), yielding recovery rates of 58-116% and matrix effects between 62 and 108% for most compounds, confirming the method's suitability for taxonomically diverse matrices. Samples collected during Antarctic expeditions from 2018 to 2022 revealed the presence of multiple ECs, including perfluorooctanoic acid (PFOA), caffeine, pharmaceuticals and personal care products (PPCPs), and UV filters. Complementarily, a preliminary suspect screening via high-resolution mass spectrometry was attempted, revealing the potential presence of a broader spectrum of drugs, PPCPs, and lifestyle-related compounds in all studied species. This work represents one of the first applications of a QuEChERS-based analytical framework for ECs detection in Antarctic marine fauna, offering a reliable approach for long-term contaminant monitoring in one of the planet's most fragile ecosystems.
Protonated species play a key role in ion-molecule chemistry relevant to astrochemical environments. In this work, we present a high-level theoretical characterization of the low-lying isomers of the [H,H,C,N,O]+ system. The exploration of the ground-state potential energy surface, using coupled-cluster (CC) theory, led to the identification of ten protonated isomers. Equilibrium structures and relative energies have been determined using composite schemes rooted in CC theory and accounting for extrapolation to the complete basis set limit and the effects of core correlation. H2NCO+ and HNCOH+ are confirmed as the two most stable forms. For all isomers, rotational spectroscopy parameters together with fundamental vibrational frequencies and infrared intensities are accurately predicted. Proton affinities of the HNCO isomers are evaluated to elucidate preferred protonation sites. In addition, the patterns of the lowest singlet and triplet electronic states of these species, which exhibit strong valence-Rydberg character, are also presented. This work is expected to help in the identification of these protonated species in laboratory and astrophysical media.
Controlling lattice-oxygen reactivity in earth-abundant OER catalysts requires precise tuning of defect chemistry in the oxide lattice. Here, we combine DFT + U calculations with plasma-assisted synthesis to show how O2 and H2O in the discharge govern vacancy formation, electronic structure, and catalytic predisposition in NiO thin films. Oxygen-rich plasmas generate isolated and clustered Ni vacancies that stabilize oxygen-ligand-hole states and produce shallow O 2p-Ni 3d hybrid levels, enhancing Ni-O covalency. In contrast, introducing H2O during growth drives local hydroxylation that compensates vacancy-induced Ni3+ centers, restoring Ni2+-like coordination, suppressing deep divacancy-derived in-gap states, and introducing shallow Ni-O-H-derived valence-band tails. EXAFS confirms that hydroxylation perturbs only the local environment while preserving the medium-range NiO lattice, and Ni L-edge spectroscopy shows a persistent but redistributed ligand-hole population. These complementary vacancy- and hydroxylation-driven pathways provide a plasma-controlled route to predefine electronic defect landscapes in NiO and to tune its activation toward OER-relevant NiOOH formation.
Perfluoroalkyl substances (PFAS) are a family of over seven million chemicals found in a vast number of industrial and consumer applications. Often referred to as the "forever chemicals," they have gained increasing attention due to their environmental and health implications. The growing awareness and interest in these perfluorinated pollutants demand the exploitation of an integrated approach where the use of computational pipelines can play a major role in the understanding and prediction of their behavior. To this end, we developed an accurate and transferable coarse-grain PFAS model in the framework of the Martini 3 force field. Given the large amount of PFAS already reported, 18 linear perfluorocarboxylic acids and perfluorosulfonic acids of different chain lengths were considered in the parametrization. The model was validated following the standard Martini procedure and complemented with additional studies on self-aggregation and the interaction with graphene, which is a common substrate for sensors and wastewater remediation adsorbents. The results are highly consistent with both all-atom simulations and experimental data, successfully reproducing the key structural and physical properties. We believe that our study opens the way for high-throughput simulations to explore the interaction between PFAS and nanoparticles/(bio)molecules.
Non-fused-ring electron acceptors have recently gathered substantial interest for the application in organic solar cells because of their competitive photovoltaic properties and other advantages, including easy synthesis and high yields, facilitating the production of cost-efficient devices. In this work, a pair of fluorene-based acceptors, FHM-Cl and FHM-F, respectively featuring a chlorinated and a fluorinated 1,1-dicyanomethylene-3-indanone end group, π-bridged through alkyl-substituted thiophene units to a fluorene core, were synthesized through a three-step synthesis from commercially available precursors. Organic solar cells utilizing these acceptor molecules were subsequently fabricated and optimized with various donor materials. Notably, the combinations D18:FHM-Cl and D18:FHM-F achieved power conversion efficiencies of 10.7% and 7.6%, respectively. A comprehensive study involving optical and electrical characterization, along with morphological analysis, demonstrated that the FHM-Cl-based solar cells exhibited superior light absorption, enhanced solid-state packing and reduced trap-assisted recombination. Moreover, the shelf and thermal stability of the devices further highlight the potential of these acceptors in the design of low-cost and efficient organic solar cells.
The neutral Cu2+ complex [Cu(dttt)2], in which dttt- is the 1,3,2-dithiazole-4-thione-5-thiolate ligand, is a promising molecular spin qubit where a hydrogen-free and sulfur-rich scaffold has been designed to enhance the spin coherence. In bulk, the structural organization induces strong intermolecular antiferromagnetic exchange couplings up to about 100 cm-1, mediated by van der Waals interactions and propagated along 1D chains of molecules within the crystal structure. Here, the deposition by sublimation in ultra-high vacuum conditions of [Cu(dttt)2] on a graphene surface is studied, focusing on investigating the topology and magnetism of ultrathin films. These deposits are characterized by combining X-ray photoelectron spectroscopy and scanning tunneling microscopy; the latter indicates an ordered chain-like arrangement of the assembled monolayer. Synchrotron-based X-ray absorption techniques flanked by density functional theory and wavefunction-based simulations confirm the molecular ordering. These reveal that the magnetic coupling observed in bulk is also present at the monolayer level, highlighting the persistence of a 1D antiferromagnetic intermolecular coupling of about 50 cm-1 with a non-negligible contribution coming from a through-surface exchange path.
In the rational design of novel polymers, the role of simulation methods based on classical physics is often hindered by the limited accuracy and transferability of the available models, at both the full-atomistic (FA) and coarse-grained (CG) level. Here, we introduce a first-principles-based, fully modular computational protocol for the generation of accurate and consistent FA and CG force fields, tailored on a specific material, and requiring as the sole input the chemical formula of one repeating monomeric unit of the target polymer. The proposed workflow is aimed to connect, across multiple scales, Quantum Mechanical (QM) calculations, FA and CG quantum-mechanically derived force fields (QMD-FFs), and Molecular Dynamics (MD), integrating them into a single, consistent, and reproducible framework. The protocol is tested on poly(ethylene terephthalate) (PET), a well-known polymeric material, widely used in the packaging industry. MD simulations carried out with our FA and CG QMD-FFs are found to significantly outperform standard general-purpose models in predicting key properties such as density, glass transition temperature, as well as the intra- and supra-molecular structure. Such improvement is traced back to the accuracy of the parent QM description by controlling the adherence of the lower level models to the reference set, monitoring this flow of information at each step of the applied procedure. The performances obtained for PET confirm the reliability of a general and tunable approach, which supports systematic refinement and hence stands as a promising tool for in silico design of novel polymers. Subjected to further automation, the procedure could also be integrated into computational machine-learning-based high-throughput schemes, paving the way toward an efficient data-driven polymer discovery.