Low-energy photoredox catalysis
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Biomimetic 1,2-amino migration via photoredox catalysis
Synthetic organic chemists continually draw inspiration from biocatalytic processes to innovate synthetic methodologies beyond existing catalytic platforms. Within this context, although 1,2-amino migration represents a viable biochemical process, it remains underutilized within the synthetic organic chemistry community. Here we present a biomimetic 1,2-amino migration accomplished through the synergistic combination of biocatalytic mechanism and photoredox catalysis. This platform enables the modular synthesis of γ-substituted β-amino acids by utilizing abundant α-amino-acid derivatives and readily available organic molecules as coupling partners. This mild method features excellent substrate and functionality compatibility, affording a diverse range of γ-substituted β-amino acids (more than 80 examples) without the need for laborious multistep synthesis. Mechanistic studies, supported by both experimental observations and theoretical analysis, indicate that the 1,2-amino migration mechanism involves radical addition to α-vinyl-aldimine ester, 3-exo–trig cyclization and a subsequent rearrangement process. We anticipate that this transformation will serve as a versatile platform for the highly efficient construction of unnatural γ-substituted β-amino acids.
Enantioselective C–H annulations enabled by either nickel- or cobalt-electrocatalysed C–H activation for catalyst-controlled chemodivergence
Enantioselective electrocatalysis shows unique potential for the sustainable assembly of enantiomerically enriched molecules. This approach allows electro-oxidative C–H activation to be performed paired to the hydrogen evolution reaction. Recent progress has featured scarce transition metals with limited availability. Here we reveal that the earth-abundant 3d transition metals nickel and cobalt exhibit distinctive performance for enantioselective electrocatalysis with chemodivergent reactivity patterns. Enantioselective desymmetrizations of strained bicyclic alkenes were achieved through C–H annulations. A data-driven optimization of chiral N,O-bidentate salicyloxazoline-type ligands was crucial for enhancing enantioselectivity in nickel electrocatalysis. Notably, in the transition state of the enantio-determining step, secondary weak attractive π–π and CH–π interactions were identified, reflecting the informed adaptations in the ligand design. Detailed mechanistic investigations by experimental and computational studies revealed for the nickel electrocatalysis a C–N bond-forming reductive elimination from nickel(III) and for the cobalt electrocatalysis a C–C bond-forming nucleophilic addition from cobalt(III) as the product-determining steps.
Photo-assisted technologies for environmental remediation
Industrial processes can lead to air and water pollution, particularly from organic contaminants such as toluene and antibiotics, posing threats to human health. Photo-assisted chemical oxidation technologies leverage light energy to mineralize these contaminants. In this Review, we discuss the mechanisms and efficiencies of photo-assisted advanced oxidation processes for wastewater treatment and photothermal technologies for air purification. The integration of solar energy enhances degradation efficiency and reduces energy consumption, enabling more efficient remediation methods. We evaluate the technological aspects of photo-assisted technologies, such as photo-Fenton, photo-persulfate activation, photo-ozonation and photoelectrochemical oxidation, emphasizing their potential for practical applications. Finally, we discuss the challenges in scaling up photo-assisted technologies for specific environmental remediation needs. Photo-assisted technologies have demonstrated effectiveness in environmental remediation, although large-scale applications remain constrained by high costs. Future potential applications of photo-assisted technologies will require that technology selection be tailored to specific pollution scenarios and engineering processes optimized to minimize costs.
Decarbonizing urban residential communities with green hydrogen systems
Community green hydrogen systems, typically consisting of rooftop photovoltaic panels paired with hybrid hydrogen-battery storage, offer urban environments with improved access to clean, on-site energy. However, economically viable pathways for deploying hydrogen storage within urban communities remain unclear. Here we develop a bottom-up energy model linking climate, human behavior and community characteristics to assess the impacts of pathways for deploying community green hydrogen systems in North America from 2030 to 2050. We show that for the same community conditions, the cost difference between the best and worst pathways can be as high as 60%. In particular, the household centralized option emerges as the preferred pathway for most communities. Furthermore, enhancing energy storage demands within these deployment pathways can reduce system design costs up to fourfold. To achieve cost-effective urban decarbonization, the study underscores the critical role of selecting the right deployment pathway and prioritizing the integration of increased energy storage in pathway designs.
Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts
Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.
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