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Many chemical methods have been developed to favor a particular product in transformations of compounds that have two or more reactive sites. We explored a different approach to site selectivity using vibrational strong coupling (VSC) between a reactant and the vacuum field of a microfluidic optical cavity. Specifically, we studied the reactivity of a compound bearing two possible silyl bond cleavage sites—Si–C and Si–O, respectively—as a function of VSC of three distinct vibrational modes in the dark. The results show that VSC can indeed tilt the reactivity landscape to favor one product over the other. Thermodynamic parameters reveal the presence of a large activation barrier and substantial changes to the activation entropy, confirming the modified chemical landscape under strong coupling.

In the presence of Lewis acid salts, the cyclic ether, dioxolane (DOL), is known to undergo ring-opening polymerization inside electrochemical cells to form solid-state polymer batteries with good interfacial charge-transport properties. Here we report that LiNO₃, which is unable to ring-open DOL, possesses a previously unknown ability to coordinate with and strain DOL molecules in bulk liquids, completely arresting their crystallization. The strained DOL electrolytes exhibit physical properties analogous to amorphous polymers, including a prominent glass transition, elevated moduli, and low activation entropy for ion transport, but manifest unusually high, liquidlike ionic conductivities (e.g., 1 mS/cm) at temperatures as low as −50 °C. Systematic electrochemical studies reveal that the electrolytes also promote reversible cycling of Li metal anodes with high Coulombic efficiency (CE) on both conventional planar substrates (1 mAh/cm² over 1,000 cycles with 99.1% CE; 3 mAh/cm² over 300 cycles with 99.2% CE) and unconventional, nonplanar/three-dimensional (3D) substrates (10 mAh/cm² over 100 cycles with 99.3% CE). Our finding that LiNO₃ promotes reversibility of Li metal electrodes in liquid DOL electrolytes by a physical mechanism provides a possible solution to a long-standing puzzle in the field about the versatility of LiNO₃ salt additives for enhancing reversibility of Li metal electrodes in essentially any aprotic liquid electrolyte solvent. As a first step toward understanding practical benefits of these findings, we create functional Li∥lithium iron phosphate (LFP) batteries in which LFP cathodes with high capacity (5 to 10 mAh/cm²) are paired with thin (50 μm) lithium metal anodes, and investigate their galvanostatic electrochemical cycling behaviors.

We study the problem of training deep fully connected neural networks with Rectified Linear Unit (ReLU) activation function and cross entropy loss function for binary classification using gradient descent. We show that with proper random weight initialization, gradient descent can find the global minima of the training loss for an over-parameterized deep ReLU network, under certain assumption on the training data. The key idea of our proof is that Gaussian random initialization followed by gradient descent produces a sequence of iterates that stay inside a small perturbation region centered at the initial weights, in which the training loss function of the deep ReLU networks enjoys nice local curvature properties that ensure the global convergence of gradient descent. At the core of our proof technique is (1) a milder assumption on the training data; (2) a sharp analysis of the trajectory length for gradient descent; and (3) a finer characterization of the size of the perturbation region. Compared with the concurrent work (Allen-Zhu et al. in A convergence theory for deep learning via over-parameterization, 2018a; Du et al. in Gradient descent finds global minima of deep neural networks, 2018a) along this line, our result relies on milder over-parameterization condition on the neural network width, and enjoys faster global convergence rate of gradient descent for training deep neural networks.

High-entropy metal-organic frameworks (HE-MOFs) hold promise as versatile materials, yet current rare examples are confined to low-valence elements in the fourth period, constraining their design and optimization for diverse applications. Here, a novel high-entropy, defect-rich and small-sized (32 nm) UiO-66 (ZrHfCeSnTi HE-UiO-66) has been synthesized for the first time, leveraging increased configurational entropy to achieve high tolerance to doping with diverse metal ions. The lattice distortion of HE-UiO-66 induces high exposure of metal nodes to create coordination unsaturated metal sites with a concentration of 322.4 μmol/g, which increases the abundance of Lewis acid-base sites, thereby achieving a significant improvement in the performance of the catalytic transfer hydrogenation (CTH) reaction. Systematic investigation manifests that the special electronic structure of HE-UiO-66 enhances the interaction and bonding with substrate molecules and reduces the energy barrier of the hydrogen transfer process. Our approach offers a new strategy for constructing coordination unsaturated metal sites in MOFs. High-entropy metal-organic frameworks offer significant potential as versatile materials, but existing examples are largely limited to low-valence elements in the fourth period, restricting their design and optimization for various applications. Here, a novel high-entropy, defect-rich, and small-sized UiO-66 framework has been synthesized to enhance catalytic transfer hydrogenation.

Pd catalysts are widely used in alkynol semi-hydrogenation. However, due to the existence of scaling relationships of adsorption energies between the key adsorbed species, the increase in conversion is frequently accompanied by side reactions, thereby reducing the selectivity to alkenols. We report that the simultaneous increase in alkenol selectivity and alkynol conversion is achieved by manipulating interstitial atoms including B, P, C, S and N in Pd catalysts. A negative linear relationship is observed between the activation entropies of 2-methyl-3-butyn-2-ol and 2-methyl-3-buten-2-ol which is highly related to the filling of d -orbital of Pd catalysts by the modification of p -block elements. A catalyst co-modified by B and C atoms has the maximum d charge of Pd that achieves a 17-fold increase in the turn-over frequency values compared to the Lindlar catalysts in the semi-hydrogenation of 2-methyl-3-butyn-2-ol. When the conversion is close to 100%, the selectivity can be as high as 95%. Circumventing the linear scaling relationship in the semi-hydrogenation is challenging. Here the authors report a method for breaking the scaling relationships using ordered mesoporous carbon-supported Pd nanocatalysts with d -electron gain by p -block atoms occupying interstitial sites in the lattice as a greener alternative to Lindlar catalysts for the selective hydrogenation of alkynols.

Tricyclo-DNA (tcDNA) is a sugar-modified analogue of DNA currently tested for the treatment of Duchenne muscular dystrophy in an antisense approach. Tandem mass spectrometry plays a key role in modern medical diagnostics and has become a widespread technique for the structure elucidation and quantification of antisense oligonucleotides. Herein, mechanistic aspects of the fragmentation of tcDNA are discussed, which lay the basis for reliable sequencing and quantification of the antisense oligonucleotide. Excellent selectivity of tcDNA for complementary RNA is demonstrated in direct competition experiments. Moreover, the kinetic stability and fragmentation pattern of matched and mismatched tcDNA heteroduplexes were investigated and compared with non-modified DNA and RNA duplexes. Although the separation of the constituting strands is the entropy-favored fragmentation pathway of all nucleic acid duplexes, it was found to be only a minor pathway of tcDNA duplexes. The modified hybrid duplexes preferentially undergo neutral base loss and backbone cleavage. This difference is due to the low activation entropy for the strand dissociation of modified duplexes that arises from the conformational constraint of the tc-sugar-moiety. The low activation entropy results in a relatively high free activation enthalpy for the dissociation comparable to the free activation enthalpy of the alternative reaction pathway, the release of a nucleobase. The gas-phase behavior of tcDNA duplexes illustrates the impact of the activation entropy on the fragmentation kinetics and suggests that tandem mass spectrometric experiments are not suited to determine the relative stability of different types of nucleic acid duplexes. Graphical Abstract ᅟ

The interface between electrocatalyst and electrolyte is highly dynamic. Even in absence of major structural changes, the intermediate coverage and interfacial solvent are bias and time dependent. This is not accounted for in current kinetic models. Here, we study the kinetics of the hydrogen evolution, ammonia oxidation and oxygen reduction reactions on polycrystalline Pt with distinct intrinsic rates and intermediates (e.g. *H, *OH, *NH 2 , *N). Despite these differences, we discover shared relationships between the pre-exponential factor and the activation energy that we link to solvation kinetics in the presence of electronic excess charge and charged intermediates. Further, we study dynamic changes of these kinetic parameters with a millisecond time resolution during electrosorption and double layer charging and dynamic *N and *NO poisoning. Finally, we discover a pH-dependent activation entropy that explains non-Nernstian overpotential shifts with pH. In sum, our results demonstrate the importance of accounting for a bias and time-dependent interfacial solvent and catalyst surface. Interfacial ion solvation is omnipresent in electrochemistry. Sarabia et al. now explore solvation kinetics with a millisecond time resolution and shine light on the critical role of the solvent during dynamic catalyst and electrosorption kinetics.

Supported gold nanoparticles are emerging catalysts for heterogeneous catalytic reactions, including selective hydrogenation. The traditionally used supports such as silica do not favor the heterolytic dissociation of hydrogen on the surface of gold, thus limiting its hydrogenation activity. Here we use gold catalyst particles partially embedded in the pore walls of mesoporous carbon with carbon atoms occupying interstitial sites in the gold lattice. This catalyst allows improved electron transfer from carbon to gold and, when used for the chemoselective hydrogenation of 3-nitrostyrene, gives a three times higher turn-over frequency (TOF) than that for the well-established Au/TiO 2 system. The d electron gain of Au is linearly related to the activation entropy and TOF. The catalyst is stable, and can be recycled ten times with negligible loss of both reaction rate and overall conversion. This strategy paves the way for optimizing noble metal catalysts to give an enhanced hydrogenation catalytic performance. Gold is among the least active metals toward molecules at a solid-liquid or solid-gas interface. Here the authors demonstrate that the gold nanocatalysts with d electron gain due to C occupying interstitial sites in its lattice boost catalytic hydrogenation.

Mapping free-energy landscapes has proved to be a powerful tool for studying reaction mechanisms. Many complex biomolecular assembly processes, however, have remained challenging to access using this approach, including the aggregation of peptides and proteins into amyloid fibrils implicated in a range of disorders. Here, we generalize the strategy used to probe free-energy landscapes in protein folding to determine the activation energies and entropies that characterize each of the molecular steps in the aggregation of the amyloid-β peptide (Aβ42), which is associated with Alzheimer’s disease. Our results reveal that interactions between monomeric Aβ42 and amyloid fibrils during fibril-dependent secondary nucleation fundamentally reverse the thermodynamic signature of this process relative to primary nucleation, even though both processes generate aggregates from soluble peptides. By mapping the energetic and entropic contributions along the reaction trajectories, we show that the catalytic efficiency of Aβ42 fibril surfaces results from the enthalpic stabilization of adsorbing peptides in conformations amenable to nucleation, resulting in a dramatic lowering of the activation energy for nucleation.

Ion (de)solvation at solid–electrolyte interfaces is pivotal for energy and chemical conversion technology, such as (electro)catalysis, batteries and bipolar membranes. For example, during the electrocatalytic hydrogen evolution reaction in alkaline media, water needs to be dissociated and hydroxide ions solvated—a process that is not well understood. Here we study water dissociation and ion solvation kinetics in isolation at polymeric bipolar membrane and electrolyte–metal interfaces. We discover bias-dependent relationships between the activation entropy and enthalpy, which we link to a bias-dependent dispersion of interfacial capacitance. Furthermore, our results indicate that OH − solvation is kinetically slower than H + solvation and that the solvation kinetics display characteristics that are independent of the catalyst structure. We attribute this to a universal amount of excess charge needed to induce electric fields that alter the interfacial entropy of water. Of fundamental interest, these results are critical to enable knowledge-driven bipolar membrane and electrocatalyst design. Ion solvation at solid–electrolyte interfaces is crucial in various components of energy conversion technologies, including water splitting electrocatalysts and bipolar membranes, but is poorly understood. Here the authors study ion solvation kinetics in these systems, highlighting the key role of interfacial capacitance in determining behaviour.