Trends in Chemistry最新文献

Plasmonic photocatalysis, which represents a paradigm-shifting approach to solar-to-chemical energy conversion, has become a rapidly evolving research field full of opportunities, challenges, and open questions. Plasmon-driven photocatalytic reactions are mechanistically complex, dictated not only by multiple interplaying photophysical effects but also by local chemical environments at the catalyst–adsorbate interfaces. This review article highlights the unique value of plasmon-enhanced Raman spectroscopy in mechanistic studies of plasmonic photocatalysis. Using plasmon-driven reductive coupling of nitroarene derivative adsorbates as a model reaction system, this article elaborates on how the rich information extracted from deliberately designed plasmon-enhanced Raman spectroscopic measurements can be carefully analyzed and further rationalized to generate critical insights into the exact roles of hot carriers, photothermal transduction, and catalyst–adsorbate interactions in plasmonic photocatalysis.

Lithium-sulfur (Li-S) batteries are restricted by cathode polysulfide shuttling and anode lithium dendrite formation. Jin, Zuo, and coworkers recently showed that Li-S batteries with high capacities and cycling stabilities emerge from intentionally designed covalent organic framework (COF) electrodes. This report highlights how COF design can address fundamental challenges in organic electrode engineering.

The presence of entanglements in polymer networks has been known since the 1940s. These topological crosslinks have been found to strongly affect mechanical properties of the materials, including stiffness, extensibility, and toughness. However, control over the entanglement density and topology remains a challenge. Furthermore, entanglements are invisible to conventional chemical characterization methods, rendering their characterization a challenge in its own right. Recent endeavors in the realm of polymer entanglements have focused on unraveling the nature of entanglements and leveraging this knowledge to enhance the mechanical properties of soft materials. This review covers the latest breakthroughs in controlling and characterizing the formation of trapped entanglements in polymer networks and offers an outlook on the trajectory of this evolving field.

Ligands play a pivotal role in catalysis, yet crafting and purifying them often requires toxic reagents and results in solvent waste. Thus, curtailing their sustainability repercussions demands a meticulous synthetic process, robust design leading to minimal usage, and entirely ligand-free methodologies.

Carbon-based emitters (CBEs) hold promise for display technology due to their abundance, flexibility, tunable photoluminescence (PL), and environmental friendliness. However, uncontrolled vibronic coupling in CBEs often results in inferior-color-purity emissions, posing a significant challenge in realizing the Rec. 2020 standard. This review offers an overview of narrow-bandwidth emissive CBEs including small molecules, polymers, and carbon dots (CDs). We focus primarily on the relationship between molecular structure and optical properties, ranging from their aromatic conjugated skeletons to functional groups. We also delve into the key challenges and potential prospects in this field. It is hoped that this review will inspire more elaborate structure design of narrow-bandwidth emissive CBEs from a fresh perspective and facilitate the practical application of CBE-based light-emitting diodes (LEDs) in wide-color-gamut display technology.

The integration of artificial intelligence (AI)–machine learning (ML) in the field of electrochemistry is expected to reduce the burden of time and cost associated with experimental procedures. The application of AI–ML has pioneered a novel approach and has heralded a paradigm shift in catalyst development, optimization of operational conditions, prediction of battery lifespan, and the development of innovative descriptors. This review delves deep into these critical objectives, highlighting the intersection of AI–ML in the fields of water electrolysis, fuel cells, batteries, and carbon dioxide reduction. This review also underscores the potential of AI–ML to bridge theoretical computations with practical applications and to advance the electrochemical field.

Principal investigators (PI) are usually treated by their group members as the ‘boss’ or even the ‘big brother’, because of the PI’s status and power. This kind of imbalanced situation can result in unhealthy mentorship, especially when the mentor and mentee are in their early career. This article highlights the critical importance of effective mentorship practices for new PIs, drawing insights from personal mentorship experience.