Extending MoS_(2)-based materials into the catalysis of non-acidic hydrogen evolution:challenges,progress,and perspectives

Water splitting is regarded as among the most prospective methods of generating green hydrogen.Switching electrolytes of water electrolysis from acidic to non-acidic ones will enable the use of noble-metal-free electrocatalysts and mitigate material corrosion,thus lowering the capital cost of water electrolyzers and improving their operational stability.However,increasing electrolyte pH will degrade the hydrogen evolution reaction(HER)activity because of the reduced concentration of H_(3)O^(+)as reactants,making non-acidic HER sluggish.To accelerate HER,MoS_(2)-based materials with the advantages of unique atomistic structure,low cost,and high abundance have been considered prospective electrocatalysts to substitute for Pt in acid.Great efforts are being spent on extending MoS_(2)-based materials into the catalysis of non-acidic HER,and their further development requires clarification of the existing challenges and current progress.However,it has not yet been discussed for non-acidic HER on MoS_(2)-based electrocatalysts.To mitigate the disparity,we systematically overview MoS_(2)-based electrocatalysts for non-acidic HER,covering catalytic mechanisms,modulation strategies,materials development,current challenges,research progress,and perspectives.This review will contribute to the rational design of MoS_(2)-based materials for high-performance HER in non-acidic conditions.

The application of artificial intelligence in the management of sepsis

Sepsis is a complex and heterogeneous syndrome that remains a serious challenge to healthcare worldwide.Patients afflicted by severe sepsis or septic shock are customarily placed under intensive care unit(ICU)supervision,where a multitude of apparatus is poised to produce high-granularity data.This reservoir of high-quality data forms the cornerstone for the integration of AI into clinical practice.However,existing reviews currently lack the inclusion of the latest advancements.This review examines the evolving integration of artificial intelligence(AI)in sepsis management.Applications of artificial intelligence include early detection,subtyping analysis,precise treatment and prognosis assessment.AI-driven early warning systems provide enhanced recognition and intervention capabilities,while profiling analyzes elucidate distinct sepsis manifestations for targeted therapy.Precision medicine harnesses the potential of artificial intelligence for pathogen identification,antibiotic selection,and fluid optimization.In conclusion,the seamless amalgamation of artificial intelligence into the domain of sepsis management heralds a transformative shift,ushering in novel prospects to elevate diagnostic precision,therapeutic efficacy,and prognostic acumen.As AI technologies develop,their impact on shaping the future of sepsis care warrants ongoing research and thoughtful implementation.