Comparative Screening of DalPhos/Ni Catalysts in C-N Cross-couplings of (Hetero)aryl Chlorides Enables Development of Aminopyrazole Cross-couplings with Amine Base.

A systematic competitive evaluation of the DalPhos ligand family in nickel-catalyzed N-arylation chemistry is reported, involving primary (linear and branched) and secondary alkylamines, as well as a primary five-membered heteroarylamine (aminopyrazole), in combination with a diverse set of test electrophiles and bases (NaOtBu, K2 CO3 , DBU/NaTFA). In addition to providing optimal ligand/catalyst identification, and bringing to light methodology limitations (e. g., unwanted C-O cross-coupling with NaOtBu), our survey enabled the development of the first efficient catalyst system for heteroatom-dense C-N cross-coupling of aminopyrazoles and related nucleophiles with (hetero)aryl chlorides by use of an amine 'dual-base' system.

Going Beyond Silver in Ethylene Epoxidation with First-Principles Catalyst Screening.

Ethylene epoxidation is industrially and commercially one of the most important selective oxidations. Silver catalysts have been state-of-the-art for decades, their efficiency steadily improving with empirical discoveries of dopants and co-catalysts. Herein, we perform a computational screening of the metals in the periodic table, identify prospective superior catalysts and experimentally demonstrate that Ag/CuPb, Ag/CuCd and Ag/CuTl outperform the pure-Ag catalysts, while they still confer an easily scalable synthesis protocol. Furthermore, we show that to harness the potential of computationally-led discovery of catalysts fully, it is essential to include the relevant in situ conditions e.g., surface oxidation, parasitic side reactions and ethylene epoxide decomposition, as neglecting such effects leads to erroneous predictions. We combine ab initio calculations, scaling relations, and rigorous reactor microkinetic modelling, which goes beyond conventional simplified steady-state or rate-determining modelling on immutable catalyst surfaces. The modelling insights have enabled us to both synthesise novel catalysts and theoretically understand experimental findings, thus, bridging the gap between first-principles simulations and industrial applications. We show that the computational catalyst design can be easily extended to include larger reaction networks and other effects, such as surface oxidations. The feasibility was confirmed by experimental agreement.

Using a Nitrophenol Cocktail Screen to Improve Catalyst Down-selection.

The catalytic reduction of 4-nitrophenol (4NP) with excess NaBH4 is the benchmark model for quantifying catalytic activity of nanoparticles. Although broadly useful, the reaction can be very selective. This can lead to false positives and negatives when utilized for catalyst down-selection from a broader materials candidate pool. We report a multi-nitrophenol cocktail screening methodology incorporating 4NP and other amino-nitrophenols, utilizing Ag, Au, Pt, and Pd nanoparticles on carbon support. The reduction of the cocktail proceeds with no deleterious side reactions on the time-scale tested. The resulting kinetic rates provide an improved correlation of relative catalyst activity when compared to performance with other reducible moieties (e. g. azo bonds), or when compared to solely 4NP screening.

Design of Complex Solid-Solution Electrocatalysts by Correlating Configuration, Adsorption Energy Distribution Patterns, and Activity Curves.

Complex solid-solution electrocatalysts (also referred to as high-entropy alloy) are gaining increasing interest owing to their promising properties which were only recently discovered. With the capability of forming complex single-phase solid solutions from five or more constituents, they offer unique capabilities of fine-tuning adsorption energies. However, the elemental complexity within the crystal structure and its effect on electrocatalytic properties is poorly understood. We discuss how addition or replacement of elements affect the adsorption energy distribution pattern and how this impacts the shape and activity of catalytic response curves. We highlight the implications of these conceptual findings on improved screening of new catalyst configurations and illustrate this strategy based on the discovery and experimental evaluation of several highly active complex solid solution nanoparticle catalysts for the oxygen reduction reaction in alkaline media.

A Screening Platform to Identify and Tailor Biocompatible Small-Molecule Catalysts.

Interfacing biocompatible, small-molecule catalysis with cellular metabolism promises a straightforward introduction of new function into organisms without the need for genetic manipulation. However, identifying and optimizing synthetic catalysts that perform new-to-nature transformations under conditions that support life is a cumbersome task. To enable the rapid discovery and fine-tuning of biocompatible catalysts, we describe a 96-well screening platform that couples the activity of synthetic catalysts to yield non-canonical amino acids from appropriate precursors with the subsequent incorporation of these nonstandard building blocks into GFP (quantifiable readout). Critically, this strategy does not only provide a common readout (fluorescence) for different reaction/catalyst combinations, but also informs on the organism's fitness, as stop codon suppression relies on all steps of the central dogma of molecular biology. To showcase our approach, we have applied it to the evaluation and optimization of transition-metal-catalyzed deprotection reactions.

Electrostatic Origins of Linear Scaling Relationships at Bifunctional Metal/Oxide Interfaces: A Case Study of Au Nanoparticles on Doped MgO Substrates.

Linear scaling relationships (SRs), which relate binding energies of adsorbates across a space of catalyst surfaces, have been extensively explored for metal and oxide surfaces, but little is known about their properties at interfaces between metal nanoparticles and oxide supports, which are ubiquitous in heterogeneous catalysis. Using periodic DFT calculations, scaling principles are extended to bifunctional Au/oxide interfaces. Adopting a Au nanorod on doped MgO (100) as a model, SRs for species participating in water gas shift, methanol synthesis, and oxidation reactions are reported. SR slopes are not constrained by the bond order conservation rule postulated for metals, oxides, and zeolites, potentially permitting greater flexibility in catalyst design strategies. The deviation from bond counting, along with the physical origin of scaling behavior at interfaces, are explored using a conceptual framework involving electrostatic interactions at the Au/oxide interface.

Dynamic covalent organocatalysts discovered from catalytic systems through rapid deconvolution screening.

The first example of a bifunctional organocatalyst assembled through dynamic covalent chemistry (DCC) is described. The catalyst is based on reversible imine chemistry and can catalyze the Morita-Baylis-Hillman (MBH) reaction of enones with aldehydes or N-tosyl imines. Furthermore, these dynamic catalysts were shown to be optimizable through a systemic screening approach, in which large mixtures of catalyst structures were generated, and the optimal catalyst could be directly identified by using dynamic deconvolution. This strategy allowed one-pot synthesis and in situ evaluation of several potential catalysts without the need to separate, characterize, and purify each individual structure. The systems were furthermore shown to catalyze and re-equilibrate their own formation through a previously unknown thiourea-catalyzed transimination process.

Studies of asymmetric styrene cyclopropanation with a rhodium(II) metallopeptide catalyst developed with a high-throughput screen.

Dirhodium metallopeptides have been developed as selective catalysts for asymmetric cyclopropanation reactions. A selective ligand sequence has been identified by screening on-bead metallopeptide libraries in a 96-well plate format. Efficient ligand synthesis and screening allows a 200-member library to be created and assayed in less than three weeks. These metallopeptides catalyze efficient cyclopropanation of aryldiazoacetates, providing asymmetric access to cyclopropane products in high diastereoselectivity.

Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects.

Energy crisis and environmental pollution have become the bottleneck of human sustainable development. Therefore, there is an urgent need to develop new catalysts for energy production and environmental remediation. Due to the high cost caused by blind screening and limited valuable computing resources, the traditional experimental methods and theoretical calculations are difficult to meet with the requirements. In the past decades, computer science has made great progress, especially in the field of machine learning (ML). As a new research paradigm, ML greatly accelerates the theoretical calculation methods represented by first principal calculation and molecular dynamics, and establish the physical picture of heterogeneous catalytic processes for energy and environment. This review firstly summarized the general research paradigms of ML in the discovery of catalysts. Then, the latest progresses of ML in light-, electricity- and enzyme-mediated heterogeneous catalysis were reviewed from the perspective of catalytic performance, operating conditions and reaction mechanism. The general guidelines of ML for heterogeneous catalysis were proposed. Finally, the existing problems and future development trend of ML in heterogeneous catalysis mediated by light, electricity and enzyme were summarized. We highly expect that this review will facilitate the interaction between ML and heterogeneous catalysis, and illuminate the development prospect of heterogeneous catalysis.

Enhancing Catalyzed Decomposition of Na2CO3 with Co2MnO x Nanowire-Decorated Carbon Fibers for Advanced Na-CO2 Batteries.

The metal-CO2 batteries, especially Na-CO2, batteries come into sight owing to their high energy density, ability for CO2 capture, and the abundance of sodium resource. Besides the sluggish electrochemical reactions at the gas cathodes and the instability of the electrolyte at a high voltage, the final discharge product Na2CO3 is a solid and poor conductor of electricity, which may cause the high overpotential and poor cycle performance for the Na-CO2 batteries. The promotion of decomposition of Na2CO3 should be an efficient strategy to enhance the electrochemical performance. Here, we design a facile Na2CO3 activation experiment to screen the efficient cathode catalyst for the Na-CO2 batteries. It is found that the Co2MnO x nanowire-decorated carbon fibers (CMO@CF) can promote the Na2CO3 decomposition at the lowest voltage among all these metal oxide-decorated carbon fiber structures. After assembling the Na-CO2 batteries, the electrodes based on CMO@CF show lower overpotential and better cycling performance compared with the electrodes based on pristine carbon fibers and other metal oxide-modified carbon fibers. We believe this catalyst screening method and the freestanding structure of the CMO@CF electrode may provide an important reference for the development of advanced Na-CO2 batteries.

Quantitative methylene blue decolourisation assays as rapid screening tools for assessing the efficiency of catalytic reactions.

Identifying the most efficient oxidation process to achieve maximum removal of a target pollutant compound forms the subject of much research. There exists a need to develop rapid screening tools to support research in this area. In this work we report on the development of a quantitative assay as a means for identifying catalysts capable of decolourising methylene blue through the generation of oxidising species from hydrogen peroxide. Here, a previously described methylene blue test strip method was repurposed as a quantitative, aqueous-based spectrophotometric assay. From amongst a selection of metal salts and metallophthalocyanine complexes, monitoring of the decolourisation of the cationic dye methylene blue (via Fenton-like and non-Fenton oxidation reactions) by the assay identified the following to be suitable oxidation catalysts: CuSO4 (a Fenton-like catalyst), iron(II)phthalocyanine (a non-Fenton oxidation catalyst), as well as manganese(II) phthalocyanine. The applicability of the method was examined for the removal of bisphenol A (BPA), as measured by HPLC, during parallel oxidation experiments. The order of catalytic activity was identified as FePc > MnPc > CuSO4 for both BPA and MB. The quantitative MB decolourisation assay may offer a rapid method for screening a wide range of potential catalysts for oxidation processes.

Optimizing Open Iron Sites in Metal-Organic Frameworks for Ethane Oxidation: A First-Principles Study.

Activation of the C-H bonds in ethane to form ethanol is a highly desirable, yet challenging, reaction. Metal-organic frameworks (MOFs) with open Fe sites are promising candidates for catalyzing this reaction. One advantage of MOFs is their modular construction from inorganic nodes and organic linkers, allowing for flexible design and detailed control of properties. In this work, we studied a series of single-metal atom Fe model systems with ligands that are commonly used as MOF linkers and tried to understand how one can design an optimal Fe catalyst. We found linear relationships between the binding enthalpy of oxygen to the Fe sites and common descriptors for catalytic reactions, such as the Fe 3d energy levels in different reaction intermediates. We further analyzed the three highest-barrier steps in the ethane oxidation cycle (including desorption of the product) with the Fe 3d energy levels. Volcano relationships are revealed with peaks toward higher Fe 3d energy and stronger electron-donating group functionalization of linkers. Furthermore, we found that the Fe 3d energy levels positively correlate with the electron-donating strength of functional groups on the linkers. Finally, we validated our hypotheses on larger models of MOF-74 iron sites. Compared with MOF-74, functionalizing the MOF-74 linkers with NH2 groups lowers the enthalpic barrier for the most endothermic step in the reaction cycle. Our findings provide insight for catalyst optimization and point out directions for future experimental efforts.