In-situ study of the hydrogen peroxide photoproduction in seawater on carbon dot-based metal-free catalyst under operation condition

Hydrogen peroxide(H_(2)O_(2))photoproduction in seawater with metal-free photocatalysts derived from biomass materials is a green,sustainable,and ultra environmentally friendly way.However,most photocatalysts are always corroded or poisoned in seawater,resulting in a significantly reduced catalytic performance.Here,we report the metal-free photocatalysts(RUT-1 to RUT-5)with in-situ generated carbon dots(CDs)from biomass materials(Rutin)by a simple microwave-assisted pyrolysis method.Under visible light(λ≥420 nm,81.6 mW/cm^(2)),the optimized catalyst of RUT-4 is stable and can achieve a high H_(2)O_(2)yield of 330.36μmol/L in seawater,1.78 times higher than that in normal water.New transient potential scanning(TPS)tests are developed and operated to in-situ study the H_(2)O_(2)photoproduction of RUT-4 under operation condition.RUT-4 has strong oxygen(O_(2))absorption capacity,and the O_(2)reduction rate in seawater is higher than that in water.Metal cations in seawater further promote the photo-charge separation and facilitate the photo-reduction reaction.For RUT-4,the conduction band level under operating conditions only satisfies the requirement of O_(2)reduction but not for hydrogen(H2)evolution.This work provides new insights for the in-situ study of photocatalyst under operation condition,and gives a green and sustainable path for the H_(2)O_(2)photoproduction with metal-free catalysts in seawater.

Highly efficient metal-free catalyst from cellulose for hydrogen peroxide photoproduction instructed by machine learning and transient photovoltage technology

Great attention has been paid to green procedures and technologies for the design of environmental catalytic systems.Biomassderived catalysts represent one of the greener alternatives for green catalysis.Photocatalytic production of hydrogen peroxide(H_(2)O_(2))from O_(2) and H_(2)O is an ideal green way and has attracted widespread attention.Here,we show a metal-free photocatalyst from cellulose,which has a high photocatalytic activity for the photoproduction of H_(2)O_(2) with the reaction rate up to 2,093μmol/(h·g)and the apparent quantum efficiency of 2.33%.Importantly,a machine learning model was constructed to guide the synthesis of this metal-free photocatalyst.With the help of transient photovoltage(TPV)tests,we optimized their fabrication and catalytic activity,and clearly showed that the formation of carbon dots(CDs)facilitates the generation,separation,and transfer of photo-induced charges on the catalyst surface.This work provides a green way for the highly efficient metal-free photocatalyst design and study from biomass materials with the machine learning and TPV technology.