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Photocatalysis has emerged as an effective tool for addressing the contemporary challenges in organic synthesis. However, the trial-and-error-based screening of feasible substrates and optimal reaction conditions remains time-consuming and potentially expensive in industrial practice. Here, we demonstrate an electrochemical-based data-acquisition approach that derives a simple set of redox-relevant electro-descriptors for effective mechanistic analysis and performance evaluation through machine learning (ML) in photocatalytic synthesis. These electro-descriptors correlate to the quantification of shifted charge transfer processes in response to the photoirradiation and enabled construction of reactivity diagram where high-yield reactive "hot zones" can reflect subtle changes of the reaction system. For the model reaction of photocatalytic deoxygenation reaction, the influence of varying carboxylic acids (substrate A, oxidation-intended) and alkenes (substrate B, reduction-intended) and varying reaction conditions on the reaction yield can be visualized, while mathematical analysis of the electro-descriptor patterns further revealed distinct mechanistic/kinetic impacts from different substrates and conditions. Additionally, in the application of ML algorithms, the experimentally derived electro-descriptors reflect an overall redox kinetic outcome contributed from vast reaction parameters, serving as a capable means to reduce the dimensionality in the case of complex multiparameter chemical space. As a result, utilization of electro-descriptors enabled efficient and robust quantitative evaluation of chemical reactivity, demonstrating promising potential of introducing operando-relevant experimental insights in the data-driven chemistry.
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Nitrate-containing industrial wastewater poses a serious threat to the global food security and public health safety. As compared to the traditional microbial denitrification, electrocatalytic nitrate reduction shows better sustainability with ultrahigh energy efficiency and the production of high-value ammonia (NH3 ). However, nitrate-containing wastewater from most industrial processes, such as mining, metallurgy, and petrochemical engineering, is generally acidic, which contradicts the typical neutral/alkaline working conditions for both denitrifying bacteria and the state-of-the-art inorganic electrocatalysts, leading to the demand for pre-neutralization and the problematic hydrogen evaluation reaction (HER) competition and catalyst dissolution. Here, we report a series of Fe2 M (M=Fe, Co, Ni, Zn) trinuclear cluster metal-organic frameworks (MOFs) that enable the highly efficient electrocatalytic nitrate reduction to ammonium under strong acidic conditions with excellent stability. In pH=1 electrolyte, the Fe2 Co-MOF demonstrates the NH3 yield rate of 20653.5â µg h-1 mg-1 site with 90.55 % NH3 -Faradaic efficiency (FE), 98.5 % NH3 -selectivity and up to 75â hr of electrocatalytic stability. Additionally, successful nitrate reduction in high-acidic conditions directly produce the ammonium sulfate as nitrogen fertilizer, avoiding the subsequent aqueous ammonia extraction and preventing the ammonia spillage loss. This series of cluster-based MOF structures provide new insights into the design principles of high-performance nitrate reduction catalysts under environmentally-relevant wastewater conditions.
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Replacing the oxygen evolution reaction (OER) with water-assisted oxidation of organic molecules represents a promising approach for achieving sustainable electrochemical biomass utilization. Among numerous OER catalysts, spinels have received substantial attention due to their manifold compositions and valence states, yet their application in biomass conversions remains rare. Herein, a series of spinels were investigated for the selective electrooxidation of furfural and 5-hydroxymethylfurfural, two model substrates for versatile value-added chemical products. Spinel sulfides universally exhibit superior catalytic performance compared to that of spinel oxides, and further investigations show that the replacement of oxygen with sulfur led to the complete phase transition of spinel sulfides into amorphous bimetallic oxyhydroxides during electrochemical activation, serving as the active species. Excellent values of conversion rate (100%), selectivity (100%), faradaic efficiency (>95%), and stability were achieved via sulfide-derived amorphous CuCo-oxyhydroxide. Furthermore, a volcano-like correlation was established between their BEOR and OER activities based on an OER-assisted organic oxidation mechanism.
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Precise understanding of interfacial metal-hydrogen interactions, especially under in operando conditions, is crucial to advancing the application of metal catalysts in clean energy technologies. To this end, while Pd-based catalysts are widely utilized for electrochemical hydrogen production and hydrogenation, the interaction of Pd with hydrogen during active electrochemical processes is complex, distinct from most other metals, and yet to be clarified. In this report, the hydrogen surface adsorption and sub-surface absorption (phase transition) features of Pd and its alloy nanocatalysts are identified and quantified under operando electrocatalytic conditions via on-chip electrical transport measurements, and the competitive relationship between electrochemical carbon dioxide reduction (CO2RR) and hydrogen sorption kinetics is investigated. Systematic dynamic and steady-state evaluations reveal the key impacts of local electrolyte environment (such as proton donors with different pKa) on the hydrogen sorption kinetics during CO2RR, which offer additional insights into the electrochemical interfaces and optimization of the catalytic systems.
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Operando reconstruction of solid catalyst into a distinct active state frequently occurs during electrocatalytic processes. The correlation between initial and operando states, if ever existing, is critical for the understanding and precise design of a catalytic system. Inspired by recently established intermediate metallic state of Bi-based catalysts during electrocatalytic carbon dioxide reduction (CO2RR), here we investigate a series of Bi oxide catalysts (Bi, Bi2O3, BiO2) and demonstrate that the operando surface/subsurface oxygen loading, positively correlated to the initial oxygen content, plays a critical role in determining Bi-based CO2RR performance. Higher initial oxygen loading indicates a better electrocatalytic efficiency. Further analysis shows that this conclusion generally applies to all Bi-based electrocatalysts reported up to date. Following this principle, cost-effective BiO2 nanocrystals demonstrated the highest formate Faradaic efficiency (FE) and current density compared to Bi/Bi2O3, further allowing a pair-electrolysis system with 800 mA/cm2 current density and an overall 175% FE for formate production.
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Selective oxidation to synthesize nitriles is critical for feedstock manufacturing in the chemical industry. Current strategies typically involve substitutions of alkyl halides with toxic cyanides or the use of strong oxidation reagents (oxygen or peroxide) under ammoxidation/oxidation conditions, setting considerable challenges in energy efficiency, sustainability, and production safety. Herein, we demonstrate a facile, green, and safe electrocatalytic route for selective oxidation of amines to nitriles under ambient conditions, assisted by the anodic water oxidation on metal-doped α-Ni(OH)2 (a typical oxygen evolution reaction catalyst). By controlling the balance between co-adsorption of the amine molecule and hydroxyls on the catalyst surface, we demonstrate that Mn doping significantly promotes the subsequent chemical oxidation of amines, resulting in Faradaic efficiencies of 96% for nitriles under ≥99% conversion. This anodic oxidation is further coupled with cathodic hydrogen evolution for overall atomic economy and additional green energy production.
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Single-atom catalysts represent a unique catalytic system with high atomic utilization and tunable reaction pathway. Despite current successes in their optimization and tailoring through structural and synthetic innovations, there is a lack of dynamic modulation approach for the single-atom catalysis. Inspired by the electrostatic interaction within specific natural enzymes, here we show the performance of model single-atom catalysts anchored on two-dimensional atomic crystals can be systematically and efficiently tuned by oriented external electric fields. Superior electrocatalytic performance have been achieved in single-atom catalysts under electrostatic modulations. Theoretical investigations suggest a universal "onsite electrostatic polarization" mechanism, in which electrostatic fields significantly polarize charge distributions at the single-atom sites and alter the kinetics of the rate determining steps, leading to boosted reaction performances. Such field-induced on-site polarization offers a unique strategy for simulating the catalytic processes in natural enzyme systems with quantitative, precise and dynamic external electric fields.
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Electricidad , Catálisis , Electricidad EstáticaRESUMEN
Ammonia production plays a central role in modern industry and agriculture with a continuous surge in its demand, yet the current industrial Haber-Bosch process suffers from low energy efficiency and accounts for high carbon emissions. Direct electrochemical conversion of nitrate to ammonia therefore emerges as an appealing approach with satisfactory sustainability while reducing the environmental impact from nitrate pollution. To this end, electrocatalysts for efficient conversion of eight-electron nitrate to ammonia require collective contributions at least from high-density reactive sites, selective reaction pathways, efficient multielectron transfer, and multiproton transport processes. Here, we report a catalytic metal-organic framework (two-dimensional (2D) In-MOF In8) catalyst integrated with multiple functional motifs with atomic precision, including uniformly dispersed, high-density, single-atom catalytic sites, high proton conductivity (efficient proton transport channel), high electron conductivity (promoted by the redox-active ligands), and confined microporous environments. These eventually lead to a direct and efficient electrochemical reduction of nitrate to ammonia and record high yield rate, FE, and selectivity for NH3 production. A novel "dynamic ligand dissociation" mechanism provides an unprecedented working principle that allows for the use of a high-quality MOF crystalline structure to function as highly ordered, high-density, single-atom catalyst (SAC)-like catalytic systems and ensures the maximum utilization of the metal centers within the MOF structure. Further, the atomically precise assembly of multiple functional motifs within a MOF catalyst offers an effective and facile strategy for the future development of framework-based enzyme-mimic systems.
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Motivated by in silico predictions that Co, Rh, and Ir dopants would lead to low overpotentials to improve OER activity of Ni-based hydroxides, we report here an experimental confirmation on the altered OER activities for a series of metals (Mo, W, Fe, Ru, Co, Rh, Ir) doped into γ-NiOOH. The in situ electrical conductivity for metal doped γ-NiOOH correlates well with the trend in enhanced OER activities. Density functional theory (DFT) calculations were used to rationalize the in situ conductivity of the key intermediate states of metal doped γ-NiOOH during OER. The simultaneous increase of OER activity with intermediate conductivity was later rationalized by their intrinsic connections to the double exchange (DE) interaction between adjacent metal ions with various d orbital occupancies, serving as an indicator for the key metal-oxo radical character, and an effective descriptor for the mechanistic evaluation and theoretical guidance in design and screening of efficient OER catalysts.
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Electrochemical organic synthesis has attracted increasing attentions as a sustainable and versatile synthetic platform. Quantitative assessment of the electro-organic reactions, including reaction thermodynamics, electro-kinetics, and coupled chemical processes, can lead to effective analytical tool to guide their future design. Herein, we demonstrate that electrochemical parameters such as onset potential, Tafel slope, and effective voltage can be utilized as electro-descriptors for the evaluation of reaction conditions and prediction of reactivities (yields). An "electro-descriptor-diagram" is generated, where reactive and non-reactive conditions/substances show distinct boundary. Successful predictions of reaction outcomes have been demonstrated using electro-descriptor diagram, or from machine learning algorithms with experimentally-derived electro-descriptors. This method represents a promising tool for data-acquisition, reaction prediction, mechanistic investigation, and high-throughput screening for general organic electro-synthesis.
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Preparative electrochemical synthesis is an ideal method for establishing green, sustainable processes. The major benefits of an electro-organic strategy over that of conventional chemical synthesis are the avoidance of reagent waste and mild reaction conditions. Here, an intermolecular cross-dehydrogenative coupling between phenols and ß-dicarbonyl compounds has been developed to build various benzofurans under undivided electrolytic conditions. Neither transition metals nor external chemical oxidants are required to facilitate the dehydrogenation and dehydration processes. The key factor in success was the use of nBu4 NBF4 as the electrolyte and hexafluoroisopropanol as the solvent, which play key roles in the cyclocondensation step. This electrolysis is scalable and can be used as a key step in drug synthesis. On the basis of several experimental results, the mechanism, particularly of the remarkable anodic oxidation and cyclization process, was illustrated.