Accelerating the separation of carriers in the heterojunction plays vital role in the photoelectrocatalytic(PEC)process,yet it remains a challenging undertaking.Herein,a MOF-on-MOF based dual S-scheme heterojunction(B...Accelerating the separation of carriers in the heterojunction plays vital role in the photoelectrocatalytic(PEC)process,yet it remains a challenging undertaking.Herein,a MOF-on-MOF based dual S-scheme heterojunction(BiVO_(4)/NH_(2)-MIL-125(Ti)/NH_(2)-MIL-53(Fe),denoted as BVO/NM125/NM53)was rationally designed and prepared for PEC removing and detoxification of organic contaminants(phenol,tetracycline hydrochloride,ciprofloxacin and norfloxacin).The S-scheme heterojunction was double confirmed by DFT calculation and XPS analysis.The charge transfer resistance of BVO/NM125/NM53 photoanode decreases to 1/11 of bare BiVO_(4) photoanode.Meanwhile,the photocurrent densitywas 3 times higher,demonstrating a marked improvement in carrier separation efficiency due to dual S-scheme heterojunction.The photoanode achieved 94.3%removal of phenol within 60 min and maintained stable performance over 10 consecutive cycles,demonstrating good PEC efficiency and structural stability.The BVO/NM125/NM53 photoanode also showed effectiveness in removing antibiotics,with chlorophyll fluorescence imaging confirming a significant reduction in the ecotoxicity of intermediates.For example,wheat seed germination,growth,chlorophyll and Carotenoid production were not affected,which was similar to that of deionized water.Radical trapping experiments and electron paramagnetic resonance(EPR)analysis identified·O_(2)^(-)and·OH as the primary active species.This work demonstrates the effectiveness of developing MOF-on-MOF heterojunctions for visible-light response and enhancing charge separation in PEC.展开更多
Oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)are key catalytic processes in various renewable energy conversion and energy storage technologies.Herein,we systematically investigated the ORR and OER ...Oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)are key catalytic processes in various renewable energy conversion and energy storage technologies.Herein,we systematically investigated the ORR and OER catalytic activity of the single-atom catalysts(SACs)composed of 4d/5d period transition metal(TM)atoms embedded on MBene substrates(TM-M_(2)B_(2)O_(2),M=Ti,Mo,and W).We found that TM dominates the catalytic activity compared to the MBene substrates.The SACs embedded with Rh,Pd,Au,and Ir exhibit excellent ORR or OER catalytic activity.Specifically,Rh-Mo2B2O2and Rh-W2B2O2are promising bifunctional catalysts with ultra-low ORR/OER overpotentials of 0.39/0.21 V and0.19/0.32 V,respectively,lower than that of Pt/RuO_(2)(0.45/0.42 V).Importantly,through machine learning,the models containing 10 element features of SACs were developed to quickly and accurately identify the superior ORR and OER electrocatalysts.Our findings provide several promising SACs for ORR and OER,and offer effective models for catalyst design.展开更多
The electrocatalytic nitrogen reduction reaction(NRR)is currently constrained by sluggish reaction kinetics and poor selectivity because of the difficulties in activating inert N≡N triple bonds and the existence of c...The electrocatalytic nitrogen reduction reaction(NRR)is currently constrained by sluggish reaction kinetics and poor selectivity because of the difficulties in activating inert N≡N triple bonds and the existence of competing hydrogen evolution reaction(HER).Therefore,electrocatalysts with high activity,selectivity,and stability are highly desired.Herein,by means of first-principles calculations,we investigated the electrocatalytic NRR performance of a series of transition metal atoms(e.g.,3d,4d,and 5d)embedded in defective hexagonal MBene nanosheets[h-Zr(Hf)_(2)B_(2)O_(2)]and identified that h-Zr(Hf)_(2)B_(2)O_(2) could be an excellent platform for electrocatalytic NRR.On the basis of our proposed screening criteria,16 candidates are efficiently selected out from 50 systems,among which,Zr_(2)B_(2)O_(2)-Cr stands out with high selectivity to NRR against HER and the ultralow limiting potential(−0.10 V).The value is much lower than that of the well-established stepped Ru(0001)surface(−0.43 V).The origin of the high activity toward NRR is attributed to the synergistic effect of the single atom(SA)and the M atoms in the substrate.More impressively,a composition descriptor is further proposed on the basis of the inherent characteristics of the catalysts[number of valence electrons of SA and electronegativity of the SA and Zr(Hf)atoms],which helps to better predict the catalytic performance.Our work not only contributes to the development of highly efficient NRR electrocatalysts but also extend the application of h-MBenes in electrocatalysis.展开更多
Symbolic regression(SR),exploring mathematical expressions from a given data set to construct an interpretable model,emerges as a powerful computational technique with the potential to transform the“black box”machin...Symbolic regression(SR),exploring mathematical expressions from a given data set to construct an interpretable model,emerges as a powerful computational technique with the potential to transform the“black box”machining learning methods into physical and chemistry interpretable expressions in material science research.In this review,the current advancements in SR are investigated,focusing on the underlying theories,fundamental flowcharts,various techniques,implemented codes,and application fields.More predominantly,the challenging issues and future opportunities in SR that should be overcome to unlock the full potential of SR in material design and research,including graphics processing unit accelera-tion and transfer learning algorithms,the trade-off between expression accuracy and complexity,physical or chemistry interpretable SR with generative large language models,and multimodal SR methods,are discussed.展开更多
基金supported by the National Natural Science Foundation of China(Nos.22276168 and 21876154)A Project Supported by Scientific Research Fund of Zhejiang Provincial Education Department(No.Y202456226)。
文摘Accelerating the separation of carriers in the heterojunction plays vital role in the photoelectrocatalytic(PEC)process,yet it remains a challenging undertaking.Herein,a MOF-on-MOF based dual S-scheme heterojunction(BiVO_(4)/NH_(2)-MIL-125(Ti)/NH_(2)-MIL-53(Fe),denoted as BVO/NM125/NM53)was rationally designed and prepared for PEC removing and detoxification of organic contaminants(phenol,tetracycline hydrochloride,ciprofloxacin and norfloxacin).The S-scheme heterojunction was double confirmed by DFT calculation and XPS analysis.The charge transfer resistance of BVO/NM125/NM53 photoanode decreases to 1/11 of bare BiVO_(4) photoanode.Meanwhile,the photocurrent densitywas 3 times higher,demonstrating a marked improvement in carrier separation efficiency due to dual S-scheme heterojunction.The photoanode achieved 94.3%removal of phenol within 60 min and maintained stable performance over 10 consecutive cycles,demonstrating good PEC efficiency and structural stability.The BVO/NM125/NM53 photoanode also showed effectiveness in removing antibiotics,with chlorophyll fluorescence imaging confirming a significant reduction in the ecotoxicity of intermediates.For example,wheat seed germination,growth,chlorophyll and Carotenoid production were not affected,which was similar to that of deionized water.Radical trapping experiments and electron paramagnetic resonance(EPR)analysis identified·O_(2)^(-)and·OH as the primary active species.This work demonstrates the effectiveness of developing MOF-on-MOF heterojunctions for visible-light response and enhancing charge separation in PEC.
基金supported by the National Key Research and Development Program of China(2022YFB3807200)
文摘Oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)are key catalytic processes in various renewable energy conversion and energy storage technologies.Herein,we systematically investigated the ORR and OER catalytic activity of the single-atom catalysts(SACs)composed of 4d/5d period transition metal(TM)atoms embedded on MBene substrates(TM-M_(2)B_(2)O_(2),M=Ti,Mo,and W).We found that TM dominates the catalytic activity compared to the MBene substrates.The SACs embedded with Rh,Pd,Au,and Ir exhibit excellent ORR or OER catalytic activity.Specifically,Rh-Mo2B2O2and Rh-W2B2O2are promising bifunctional catalysts with ultra-low ORR/OER overpotentials of 0.39/0.21 V and0.19/0.32 V,respectively,lower than that of Pt/RuO_(2)(0.45/0.42 V).Importantly,through machine learning,the models containing 10 element features of SACs were developed to quickly and accurately identify the superior ORR and OER electrocatalysts.Our findings provide several promising SACs for ORR and OER,and offer effective models for catalyst design.
基金National Key Research and Development Program of China(2022YFB3807200).
文摘The electrocatalytic nitrogen reduction reaction(NRR)is currently constrained by sluggish reaction kinetics and poor selectivity because of the difficulties in activating inert N≡N triple bonds and the existence of competing hydrogen evolution reaction(HER).Therefore,electrocatalysts with high activity,selectivity,and stability are highly desired.Herein,by means of first-principles calculations,we investigated the electrocatalytic NRR performance of a series of transition metal atoms(e.g.,3d,4d,and 5d)embedded in defective hexagonal MBene nanosheets[h-Zr(Hf)_(2)B_(2)O_(2)]and identified that h-Zr(Hf)_(2)B_(2)O_(2) could be an excellent platform for electrocatalytic NRR.On the basis of our proposed screening criteria,16 candidates are efficiently selected out from 50 systems,among which,Zr_(2)B_(2)O_(2)-Cr stands out with high selectivity to NRR against HER and the ultralow limiting potential(−0.10 V).The value is much lower than that of the well-established stepped Ru(0001)surface(−0.43 V).The origin of the high activity toward NRR is attributed to the synergistic effect of the single atom(SA)and the M atoms in the substrate.More impressively,a composition descriptor is further proposed on the basis of the inherent characteristics of the catalysts[number of valence electrons of SA and electronegativity of the SA and Zr(Hf)atoms],which helps to better predict the catalytic performance.Our work not only contributes to the development of highly efficient NRR electrocatalysts but also extend the application of h-MBenes in electrocatalysis.
基金National Natural Science Foundation of China,Grant/Award Number:52332005National Key Research and Development Program of China,Grant/Award Number:2022YFB3807200China Postdoctoral Science Foundation,Grant/Award Number:2022TQ0019。
文摘Symbolic regression(SR),exploring mathematical expressions from a given data set to construct an interpretable model,emerges as a powerful computational technique with the potential to transform the“black box”machining learning methods into physical and chemistry interpretable expressions in material science research.In this review,the current advancements in SR are investigated,focusing on the underlying theories,fundamental flowcharts,various techniques,implemented codes,and application fields.More predominantly,the challenging issues and future opportunities in SR that should be overcome to unlock the full potential of SR in material design and research,including graphics processing unit accelera-tion and transfer learning algorithms,the trade-off between expression accuracy and complexity,physical or chemistry interpretable SR with generative large language models,and multimodal SR methods,are discussed.
