Ultrafine metal nanoparticles isolated on oxide nano-islands as exceptional sintering-resistant catalysts
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Optical sorting: past, present and future
Optical sorting combines optical tweezers with diverse techniques, including optical spectrum, artificial intelligence (AI) and immunoassay, to endow unprecedented capabilities in particle sorting. In comparison to other methods such as microfluidics, acoustics and electrophoresis, optical sorting offers appreciable advantages in nanoscale precision, high resolution, non-invasiveness, and is becoming increasingly indispensable in fields of biophysics, chemistry, and materials science. This review aims to offer a comprehensive overview of the history, development, and perspectives of various optical sorting techniques, categorised as passive and active sorting methods. To begin, we elucidate the fundamental physics and attributes of both conventional and exotic optical forces. We then explore sorting capabilities of active optical sorting, which fuses optical tweezers with a diversity of techniques, including Raman spectroscopy and machine learning. Afterwards, we reveal the essential roles played by deterministic light fields, configured with lens systems or metasurfaces, in the passive sorting of particles based on their varying sizes and shapes, sorting resolutions and speeds. We conclude with our vision of the most promising and futuristic directions, including AI-facilitated ultrafast and bio-morphology-selective sorting. It can be envisioned that optical sorting will inevitably become a revolutionary tool in scientific research and practical biomedical applications.
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.
Flash Joule heating for synthesis, upcycling and remediation
Electric heating methods are being developed and used to electrify industrial applications and lower their carbon emissions. Direct Joule resistive heating is an energy-efficient electric heating technique that has been widely tested at the bench scale and could replace some energy-intensive and carbon-intensive processes. In this Review, we discuss the use of flash Joule heating (FJH) in processes that are traditionally energy-intensive or carbon-intensive. FJH uses pulse current discharge to rapidly heat materials directly to a desired temperature; it has high-temperature capabilities (>3,000 °C), fast heating and cooling rates (>102 °C s−1), short duration (milliseconds to seconds) and high energy efficiency (~100%). Carbon materials and metastable inorganic materials can be synthesized using FJH from virgin materials and waste feedstocks. FJH is also applied in resource recovery (such as from e-waste) and waste upcycling. An emerging application is in environmental remediation, where FJH can be used to rapidly degrade perfluoroalkyl and polyfluoroalkyl substances and to remove or immobilize heavy metals in soil and solid wastes. Life-cycle and technoeconomic analyses suggest that FJH can reduce energy consumption and carbon emissions and be cost-efficient compared with existing methods. Bringing FJH to industrially relevant scales requires further equipment and engineering development.
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.
Anion vacancies activate N2 to ammonia on Ba–Si orthosilicate oxynitride-hydride
Anion vacancies on metal oxide surfaces have been studied as either active sites or promoting sites in various chemical reactions involving oxidation/reduction processes. However, oxide materials rarely work effectively as catalysts in the absence of transition metal sites. Here we report a Ba–Si orthosilicate oxynitride–hydride as a transition-metal-free catalyst for efficient ammonia synthesis via an anion-vacancy–mediated mechanism. The facile desorption of H− and N3− anions plus the flexibility of the crystal structure can accommodate a high density of electrons at vacancy sites, where N2 can be captured and directly activated to ammonia through hydrogenation processes. The ammonia synthesis rates reach 40.1 mmol g−1 h−1 at 300 °C by loading ruthenium nanoparticles. Although not found to dissociate N2, Ru instead facilitates the formation of anion vacancies at the Ru–support interface. This demonstrates a new route for anion-vacancy–mediated heterogeneous catalysis.
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