Unlocking the surface chemistry of ionic minerals: a high-throughput pipeline for modeling realistic interfaces.

A systematic procedure is introduced for modeling charge-neutral non-polar surfaces of ionic minerals containing polyatomic anions. By integrating distance- and charge-based clustering to identify chemical species within the mineral bulk, our pipeline, PolyCleaver, renders a variety of theoretically viable surface terminations. As a demonstrative example, this approach was applied to forsterite (Mg2SiO4), unveiling a rich interface landscape based on interactions with formaldehyde, a relevant multifaceted molecule, and more particularly in prebiotic chemistry. This high-throughput method, going beyond techniques traditionally applied in the modeling of minerals, offers new insights into the potential catalytic properties of diverse surfaces, enabling a broader exploration of synthetic pathways in complex mineral systems.

Revisiting ion-pair interactions in phase transfer catalysis: from ionic compounds to real catalyst systems.

Ion-pairing is a fundamental phenomenon that significantly influences phase-transfer catalysis. In this study, we conduct a comprehensive investigation of ion-pair interactions, aiming to establish a comprehensive understanding of their nature and implications. The study begins with the examination of polar ionic compounds to define the concept of an ion-pair in the context of phase-transfer catalysis. Subsequently, a diverse range of ion-pair catalyst models were explored to gain insight into the factors governing their interactions. Finally, the focus shifts towards the characterisation of real phase-transfer catalysts, bridging the gap between theoretical models and practical applications. Through a combination of computational approaches and theoretical analysis, this work provides valuable insight into the nature of ion-pair interactions within phase-transfer catalysis fields.

Theoretical Perspectives in Organocatalysis.

It is clear that the field of organocatalysis is continuously expanding during the last decades. With increasing computational capacity and new techniques, computational methods have provided a more economic approach to explore different chemical systems. This review offers a broad yet concise overview of current state-of-the-art studies that have employed novel strategies for catalyst design. The evolution of the all different theoretical approaches most commonly used within organocatalysis is discussed, from the traditional approach, manual-driven, to the most recent one, machine-driven.

Tuning the local chemical environment of ZnSe quantum dots with dithiols towards photocatalytic CO2 reduction.

Sunlight-driven CO2 reduction to renewable fuels is a promising strategy towards a closed carbon cycle in a circular economy. For that purpose, colloidal quantum dots (QDs) have emerged as a versatile light absorber platform that offers many possibilities for surface modification strategies. Considerable attention has been focused on tailoring the local chemical environment of the catalytic site for CO2 reduction with chemical functionalities ranging from amino acids to amines, imidazolium, pyridines, and others. Here we show that dithiols, a class of organic compounds previously unexplored in the context of CO2 reduction, can enhance photocatalytic CO2 reduction on ZnSe QDs. A short dithiol (1,2-ethanedithiol) activates the QD surface for CO2 reduction accompanied by a suppression of the competing H2 evolution reaction. In contrast, in the presence of an immobilized Ni(cyclam) co-catalyst, a longer dithiol (1,6-hexanedithiol) accelerates CO2 reduction. 1H-NMR spectroscopy studies of the dithiol-QD surface interactions reveal a strong affinity of the dithiols for the QD surface accompanied by a solvation sphere governed by hydrophobic interactions. Control experiments with a series of dithiol analogues (monothiol, mercaptoalcohol) render the hydrophobic chemical environment unlikely as the sole contribution of the enhancement of CO2 reduction. Density functional theory (DFT) calculations provide a framework to rationalize the observed dithiol length dependent activity through the analysis of the non-covalent interactions between the dangling thiol moiety and the CO2 reduction intermediates at the catalytic site. This work therefore introduces dithiol capping ligands as a straightforward means to enhance CO2 reduction catalysis on both bare and co-catalyst modified QDs by engineering the particle's chemical environment.

Successes and challenges in multiscale modelling of artificial metalloenzymes: the case study of POP-Rh2 cyclopropanase.

Molecular modelling applications in metalloenzyme design are still scarce due to a series of challenges. On top of that, the simulations of metal-mediated binding and the identification of catalytic competent geometries require both large conformational exploration and simulation of fine electronic properties. Here, we demonstrate how the incorporation of new tools in multiscale strategies, namely substrate diffusion exploration, allows taking a step further. As a showcase, the enantioselective profiles of the most outstanding variants of an artificial Rh2-based cyclopropanase (GSH, HFF and RFY) developed by Lewis and co-workers (Nat. Commun., 2015, 6, 7789 and Nat. Chem., 2018, 10, 318-324) have been rationalized. DFT calculations on the free-cofactor-mediated process identify the carbene insertion and the cyclopropanoid formation as crucial events, the latter being the enantiodetermining step, which displays up to 8 competitive orientations easily altered by the protein environment. The key intermediates of the reaction were docked into the protein scaffold showing that some mutated residues have direct interaction with the cofactor and/or the co-substrate. These interactions take the form of a direct coordination of Rh in GSH and HFF and a strong hydrophobic patch with the carbene moiety in RFY. Posterior molecular dynamics sustain that the cofactor induces global re-arrangements of the protein. Finally, massive exploration of substrate diffusion, based on the GPathFinder approach, defines this event as the origin of the enantioselectivity in GSH and RFY. For HFF, fine molecular dockings suggest that it is likely related to local interactions upon diffusion. This work shows how modelling of long-range mutations on the catalytic profiles of metalloenzymes may be unavoidable and software simulating substrate diffusion should be applied.

Imidazolium-modification enhances photocatalytic CO2 reduction on ZnSe quantum dots.

Colloidal photocatalysts can utilize solar light for the conversion of CO2 to carbon-based fuels, but controlling the product selectivity for CO2 reduction remains challenging, in particular in aqueous solution. Here, we present an organic surface modification strategy to tune the product selectivity of colloidal ZnSe quantum dots (QDs) towards photocatalytic CO2 reduction even in the absence of transition metal co-catalysts. Besides H2, imidazolium-modified ZnSe QDs evolve up to 2.4 mmolCO gZnSe -1 (TONQD > 370) after 10 h of visible light irradiation (AM 1.5G, λ > 400 nm) in aqueous ascorbate solution with a CO-selectivity of up to 20%. This represents a four-fold increase in CO-formation yield and 13-fold increase in CO-selectivity compared to non-functionalized ZnSe QDs. The binding of the thiolated imidazolium ligand to the QD surface is characterized quantitatively using 1H-NMR spectroscopy and isothermal titration calorimetry, revealing that a subset of 12 to 17 ligands interacts strongly with the QDs. Transient absorption spectroscopy reveals an influence of the ligand on the intrinsic charge carrier dynamics through passivating Zn surface sites. Density functional theory calculations indicate that the imidazolium capping ligand plays a key role in stabilizing the surface-bound *CO2 - intermediate, increasing the yield and selectivity toward CO production. Overall, this work unveils a powerful tool of using organic capping ligands to modify the chemical environment on colloids, thus enabling control over the product selectivity within photocatalyzed CO2 reduction.

Effect of Chiral Ligand Concentration and Binding Mode on Chiroptical Activity of CdSe/CdS Quantum Dots.

Chiroptically active fluorescent semiconductor nanocrystals, quantum dots (QDs), are of high interest from a theoretical and technological point of view, because they are promising candidates for a range of potential applications. Optical activity can be induced in QDs by capping them with chiral molecules, resulting in circular dichroism (CD) signals in the range of the QD ultraviolet-visible (UV-vis) absorption. However, the effects of the chiral ligand concentration and binding modes on the chiroptical properties of QDs are still poorly understood. In the present study, we report the strong influence of the concentration of a chiral amino acid (cysteine) on its binding modes upon the surface of CdSe/CdS QDs, resulting in varying QD chiroptical activity and corresponding CD signals. Importantly, we demonstrate that the increase of cysteine concentration is accompanied by the growth of the QD CD intensity, reaching a certain critical point, after which it starts to decrease. The intensity of the CD signal varies by almost an order of magnitude across this range. Nuclear magnetic resonance and Fourier transform infrared data, supported by density functional theory calculations, reveal a change in the binding mode of cysteine molecules from tridentate to bidentate when going from low to high concentrations, which results in a change in the CD intensity. Hence, we conclude that the chiroptical properties of QDs are dependent on the concentration and binding modes of the capping chiral ligands. These findings are very important for understanding chiroptical phenomena at the nanoscale and for the design of advanced optically active nanomaterials.

Universal scaling relations for the rational design of molecular water oxidation catalysts with near-zero overpotential.

A major roadblock in realizing large-scale production of hydrogen via electrochemical water splitting is the cost and inefficiency of current catalysts for the oxygen evolution reaction (OER). Computational research has driven important developments in understanding and designing heterogeneous OER catalysts using linear scaling relationships derived from computed binding energies. Herein, we interrogate 17 of the most active molecular OER catalysts, based on different transition metals (Ru, Mn, Fe, Co, Ni, and Cu), and show they obey similar scaling relations to those established for heterogeneous systems. However, we find that the conventional OER descriptor underestimates the activity for very active OER complexes as the standard approach neglects a crucial one-electron oxidation that many molecular catalysts undergo prior to O-O bond formation. Importantly, this additional step allows certain molecular catalysts to circumvent the "overpotential wall", leading to enhanced performance. With this knowledge, we establish fundamental principles for the design of ideal molecular OER catalysts.

Untangling Cooperative Effects of Pyridinic and Graphitic Nitrogen Sites at Metal-Free N-Doped Carbon Electrocatalysts for the Oxygen Reduction Reaction.

Metal-free carbon electrodes with well-defined composition and smooth topography are prepared via sputter deposition followed by thermal treatment with inert and reactive gases. X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy show that three carbons of similar N/C content that differ in N-site composition are thus prepared: an electrode consisting of almost exclusively graphitic-N (NG ), an electrode with predominantly pyridinic-N (NP ), and one with ≈1:1 NG :NP composition. These materials are used as model systems to investigate the activity of N-doped carbons in the oxygen reduction reaction (ORR) using voltammetry. Results show that selectivity toward 4e-reduction of O2 is strongly influenced by the NG /NP site composition, with the material possessing nearly uniform NG /NP composition being the only one yielding a 4e-reduction. Computational studies on model graphene clusters are carried out to elucidate the effect of N-site homogeneity on the reaction pathway. Calculations show that for pure NG -doping or NP -doping of model graphene clusters, adsorption of hydroperoxide and hydroperoxyl radical intermediates, respectively, is weak, thus favoring desorption prior to complete 4e-reduction to hydroxide. Clusters with mixed NG /NP sites display synergistic effects, suggesting that co-presence of these sites improves activity and selectivity by achieving high theoretical reduction potentials while facilitating retention of intermediates.