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Extremely long-lived charge donor states formed by visible irradiation of quantum dots
No full textUsing cyclic voltammetry under illumination, we recently demonstrated that CdS quantum dots (QDs) form charge donor states that live for at least several minutes after illumination ends, ~12 orders of magnitude longer than expected for free carriers. This timescale suggests that the conventionally accepted mechanism of charge transfer, wherein charges directly transfer to an acceptor following exciton dissociation, cannot be complete. Because of these long timescales, this unconventional pathway is not readily observed using time-resolved spectroscopy to probe charge transfer dynamics. Here, we investigated the chemical nature of these charge donor states using cyclic voltammetry under illumination coupled with NMR spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and optical spectroscopy. Our data reveal that charges are stored locally rather than as free carriers, and the number of charges stored is dependent on the QD surface ligation and stoichiometry. Altogether, our results confirm that electrons are stored at ligated surface Cd, these sites are competent charge donors, and this storage is charge balanced by X-type ligand desorption. We found that charge storage occurs in every QD system studied, including CdS, CdSe, and InP capped with carboxylate and phosphonate ligands
Short catalytic peptides with tunable activity: Cys confers functionality and adaptability
No full textThis study explores the catalytic potential of short peptides containing Cys, a potent nucleophile, able to hydrolyze a variety of ester substrates, including p-NPP and ATP, while enabling control and direction of catalytic activity through thiol oxidation. We identified Ac-CTLGLGSHCGG-Am (CG11), as a potential tunable catalyst capable of hydrolyzing ester and phosphoester substrates. We synthesized multiple analogues with varying sequence compositions and lengths and determined the effect of these changes on the catalytic efficiency. We showed that cyclization through disulfide bridge formation offered tunability and reversibility, while head-to-side chain cyclization conferred excellent resistance to proteases. Additionally, we demonstrated the ability of inactive cy-CG11 to undergo reduction and ring opening to its linear functional form in a physiological setting, specifically in the presence of elevated glutathione levels. These findings provide valuable insights for fine-tuning the characteristics of peptide-based catalysts and pave the way to their potential applicability in a biological context such as targeting glutathione disbalance and providing phosphatase activity
More than an Amide Bioisostere: Discovery of 1,2,4-Triazole-containing Pyrazolo[1,5-a]pyrimidine Host CSNK2 Inhibitors for Combatting β-Coronavirus Replication
No full textThe pyrazolo[1,5-a]pyrimidine scaffold is a promising scaffold to develop potent and selective CSNK2 inhibitors with antiviral activity against β-coronaviruses. Herein, we describe the discovery of a 1,2,4-triazole group to substitute a key amide group for CSNK2 binding present in many potent pyrazolo[1,5-a]pyrimidine inhibitors. Crystallographic evidence demonstrates that the 1,2,4-triazole replaces the amide in forming key hydrogen bonds with Lys68 and a water molecule buried in the ATP-binding pocket. This isosteric replacement improves potency and metabolic stability at a cost of solubility. Optimization for potency, solubility and metabolic stability led to the discovery of the potent and selective CSNK2 inhibitor 53. Despite excellent in vitro metabolic stability, rapid decline in plasma concentration of 53 in vivo was observed and may be attributed to lung accumulation, although in vivo pharmacological effect was not observed. Further optimization of this novel chemotype may validate CSNK2 as an antiviral target in vivo
Total Synthesis of Carbazomycins E and F
No full textTotal synthesis of carbazomycins E and F was achieved by double functionalization of an aryne intermediate generated from a 2-aminobiphenyl derivative. The tethered amino group underwent nucleophilic addition to the aryne intermediate to construct the carbazole skeleton. The resulting carbanion was formylated to give the multiply substituted carbazole. This formyl group caused several problems. For example, it was difficult to perform regioselective demethylation of the methoxy group proximal to the formyl group without protecting the carbazole nitrogen. In addition, the formyl group was unexpectedly reduced to give a methoxymethyl group under heating conditions with copper iodide and sodium methoxide. Oxidation of this compound in the presence of water was effective for obtaining the formylated carbazole, leading to the first total synthesis of carbazomycin F
Scaling Laws for Optimal Herschel–Bulkley Yield Stress Fluid Flow in Self-Similar Tree-like Branching Networks
No full textThis study analyzes optimal flow conditions and structures in tree-like branching networks for yield stress Herschel–Bulkley fluids. We focus on maximizing flow conductance under volume constraints, assuming fully developed laminar flow in circular tubes. We propose a conjecture that if the tube-wall stress, remains the same in the network for all branches, then an optimal solution exists. We find that optimal network geometry depends on the number of branch splits , and independent of the power-law index and the yield stress . This optimal condition leads to an equal pressure drop across each branching level. Our results are validated with existing theory and extended to encompass shear-thinning and shear-thickening behaviors for any number of splits with and without yield stress. Additionally, we derive relationships between geometrical and flow characteristics for parent and daughter tubes, including wall stresses, length ratios. These findings provide valuable design principles for efficient transport systems involving yield stress fluids
Dynamic Implications of Non-Covalent Interactions in Amphiphilic Single-Chain Polymer Nanoparticles
No full textSingle-chain polymer nanoparticles (SCNPs) combine the chemical diversity of synthetic polymers with the intricate structure of biopolymers, generating versatile biomimetic materials. The mobility of polymer chain segments at length scales similar to secondary structural elements in proteins are critical to SCNP structure and thus function. However, the influence of non-covalent interactions used to form SCNPs (e.g., hydrogen-bonding and biomimetic secondary-like structure) on these conformational dynamics is challenging to quantitatively assess. To isolate the effects of non-covalent interactions on SCNP structure and conformational dynamics, we synthesized a series of amphiphilic copolymers containing dimethylacrylamide and monomers capable of forming these different interactions: 1) di(phenylalanine) acrylamide that forms intramolecular β-sheet-like crosslinks, 2) phenylalanine acrylamide that forms hydrogen-bonds, but lacks a defined local structure, and 3) benzyl acrylamide that has lowest propensity for hydrogen-bonding. Each SCNP formed folded structures comparable to those of intrinsically disordered proteins, as observed by size exclusion chromatography and Small Angle Neutron Scattering. The dynamics of these polymers, as characterized by a combination of dynamic light scattering and Neutron Spin Echo spectroscopy, was well described using the Zimm with internal friction (ZIF) model, high-lighting the role of each non-covalent interaction to additively restrict the internal relaxations of SCNPs. These results demonstrate the utility of local scale interactions to control SCNP polymer dynamics, guiding the design of functional biomimetic materials with refined binding sites and tunable kinetics
Ligand field states control photocatalytic efficiency of transition metal oxides
No full textEfficient charge extraction in solar energy conversion devices requires materials that are capable of generating long-lived charge carriers. However, carrier lifetimes vary by orders of magnitude between photoabsorbers and there is no blueprint for the targeted design of materials with intrinsically long lifetimes. Here, we establish a fundamental link between the carrier lifetime and the electronic configuration of transition metal oxides (TMOs). By comparing their deactivation pathways across a range of electronic configurations, we identify a sub-ps relaxation mechanism via metal-centred ligand field (LF) states. These LF states open localised recombination channels that compromise charge and quantum yields in open d-shell TMOs (e.g., Fe2O3, Co3O4, Cr2O3, NiO), which is more reminiscent of molecular complexes than crystalline semiconductors. In contrast, in TMOs with d0 or d10 electronic configurations (e.g., TiO2, BiVO4), the absence of LF states enables larger yields of long-lived charges and thus more efficient photocatalysis. Notably, our results suggest that charge localisation in the form of polarons can mitigate rapid LF deactivation. These trends translate to other metal-containing semiconductors and open a new pathway to design absorbers with well-controlled non-radiative recombination channels for applications including photovoltaics, photocatalysis, and communication devices
Investigating Interaction Dynamics of an Enantioselective Peptide Catalyzed Acylation Reaction
No full textNuclear magnetic resonance (NMR) is a key method to investigate molecular recognition in biomacromolecules and to detect molecular motions on the µs to s timescale revealing transient conformational states. Changes in kinetics of interconversions between those states can be linked to binding, folding or catalytic events. Here, we investigated whether these methods allow detection of changes in the dynamics of a small, highly selective peptide catalyst during recognition of its enantiomeric substrates. The flexible tetrapeptide Boc-L-(π-Me)-His-AGly-L-Cha-L-Phe-OMe, used for the monoacetylation of cycloalkane-diols, is probed at natural abundance using carbon relaxation dispersion in the rotating frame (13C-R1ρ) and proton chemical exchange saturation transfer (1H-CEST). Indeed, we detected differences in dynamics of the peptide upon interaction with the diol. Importantly, these differ depending on the enantiomer of the substrate used providing insights into the recognition of the substrates. These enantiospecific influences of the substrates on the dynamics of the peptide catalyst revealed are rationalized using. computational techniques. Moreover, findings obtained are supported by experimental reaction monitoring of the acetylation reaction
Diffusion Mechanisms and Preferential Dynamics of Promoter Molecules in ZSM-5 Zeolite
No full textThe diffusion in ZSM-5 zeolite of methanol and of two series of promoters of the methanol to dimethyl
ether reaction (linear methyl esters, benzaldehyde, 4-n-alkyl benzaldehydes) has been studied using
classical molecular dynamics in the NVT ensemble. Whereas promoter diffusion coefficients decrease
with increasing alkyl chain length in methyl esters, the aromatic aldehyde promoters all have similar
diffusion coefficients. The lowest diffusion coefficient is that of benzaldehyde. All the promoters
exhibit a preference for moving in the straight pore, a preference that is most pronounced for the
4-n-alkyl benzaldehydes and least for the longest aliphatic esters. A novel diffusion mechanism, a
molecular ’3-point turn’, is observed. The diffusion coefficient of methanol is larger than that of all
the promoters. The more catalytically active aromatic aldehyde promoters limit methanol diffusion less than the aliphatic esters
AIMNet2: A Neural Network Potential to Meet your Neutral, Charged, Organic, and Elemental-Organic Needs
No full textMachine learned interatomic potentials (MLIPs) are reshaping computational chemistry practices because of their ability to drastically exceed the accuracy-length/time scale tradeoff. Despite this attraction, the benefits of such efficiency are only impactful when an MLIP uniquely enables insight into a target system or is broadly transferable outside of the training dataset, where models achieving the latter are seldom reported. In this work, we present the 2nd generation of our atoms-in-molecules neural network potential (AIMNet2), which is applicable to species composed of up to 14 chemical elements in both neutral and charged states, making it a valuable model for modeling the majority of non-metallic compounds. Using an exhaustive dataset of 20 million hybrid quantum chemical calculations, AIMNet2 combines ML-parameterized short-range and physics-based long-range terms to attain generalizability that reaches from simple organics to diverse molecules with “exotic” element-organic bonding. We show that AIMNet2 outperforms semi-empirical GFN-xTB and is on par with reference density functional theory for interaction energy contributions, conformer search tasks, torsion rotation profiles, and molecular-to-macromolecular geometry optimization. Overall, the demonstrated chemical coverage and computational efficiency of AIMNet2 is a significant step toward providing access to MLIPs that avoid the crucial limitation of curating additional quantum chemical data and retraining with each new application