A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synth...A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.展开更多
Electrocatalytic nitric oxide(NO)reduction reaction(NORR)is a promising and sustainable process that can simultaneously realize green ammonia(NH3)synthesis and hazardous NO removal.However,current NORR performances ar...Electrocatalytic nitric oxide(NO)reduction reaction(NORR)is a promising and sustainable process that can simultaneously realize green ammonia(NH3)synthesis and hazardous NO removal.However,current NORR performances are far from practical needs due to the lack of efficient electrocatalysts.Engineering the lattice of metal-based nanomaterials via phase control has emerged as an effective strategy to modulate their intrinsic electrocatalytic properties.Herein,we realize boron(B)-insertion-induced phase regulation of rhodium(Rh)nanocrystals to obtain amorphous Rh_(4)B nanoparticles(NPs)and hexagonal close-packed(hcp)RhB NPs through a facile wet-chemical method.A high Faradaic efficiency(92.1±1.2%)and NH_(3) yield rate(629.5±11.0μmol h^(−1) cm^(−2))are achieved over hcp RhB NPs,far superior to those of most reported NORR nanocatalysts.In situ spectro-electrochemical analysis and density functional theory simulations reveal that the excellent electrocatalytic performances of hcp RhB NPs are attributed to the upshift of d-band center,enhanced NO adsorption/activation profile,and greatly reduced energy barrier of the rate-determining step.A demonstrative Zn-NO battery is assembled using hcp RhB NPs as the cathode and delivers a peak power density of 4.33 mW cm−2,realizing simultaneous NO removal,NH3 synthesis,and electricity output.展开更多
Lacto-N-neotetraose(LNn T)is a crucial neutral core human milk oligosaccharide(HMO).In this study,we established a LNn T-producing Saccharomyces cerevisiae cell factory through comprehensive metabolic engineering.Spec...Lacto-N-neotetraose(LNn T)is a crucial neutral core human milk oligosaccharide(HMO).In this study,we established a LNn T-producing Saccharomyces cerevisiae cell factory through comprehensive metabolic engineering.Specifically,the de novo biosynthetic pathway of LNn T was assembled by heterologously expressing the lactose permease(lac12)from Kluyveromyces lactis and the glycosyltransferase from Neisseria meningitidis in S.cerevisiae.Subsequently,carbon source regulation based on the glucose-sensitive GAL regulatory system was employed to optimize the expression time of heterologous genes,achieving a production of 15.61 mg/L of LNn T in shake-flask fermentation.In addition,the key rate-limiting steps involved in LNn T synthesis pathway were identified and the corresponding genes were overexpressed to enhance LNn T production,resulting in an 8-fold increase in LNn T titer compared to that of parental strain.To our knowledge,this is the first report on LNn T biosynthesis in S.cerevisiae,opening up the possibility of green production of LNn T using food-safe microorganisms.展开更多
The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to res...The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to reshape talent cultivation but also presents significant challenges,including skill hollowing,ethical risks,and a growing disconnect between education and industry needs.Currently,graduate-level software engineering education struggles with outdated curricula and insufficient alignment with practical demands.In this paper,we propose a dual-core collaborative framework driven by“GenAI technology”and“industry demand”.Under this framework,we design a four-dimensional capability development path to enhance graduate students’innovation in software engineering practice.This path focuses on①scientific research innovation,②engineering problem-solving,③cross-domain collaborative evolution,and④ethical risk governance.The proposed approach promotes a shift from traditional knowledge transfer to human-machine collaborative innovation,aligning talent cultivation with the demands of the NQPF.展开更多
The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytot...The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytotoxicity.These limitations have catalyzed the development of intelligent stimuli-responsive block copolymers-based bioimaging agents,which was engineered to dynamically respond to endogenous biochemical cues(e.g.,p H gradients,redox potential,enzyme activity,hypoxia environment) or exogenous physical triggers(e.g.,photoirradiation,thermal gradients,ultrasound(US)/magnetic stimuli).Through spatiotemporally controlled structural transformations,stimuli-responsive block copolymers enable precise contrast targeting,activatable signal amplification,and theranostic integration,thereby substantially enhancing signal-to-noise ratios of bioimaging and diagnostic specificity.Hence,this mini-review systematically examines molecular engineering principles for designing p H-,redox-,enzyme-,light-,thermo-,and US/magnetic-responsive polymers,with emphasis on structure-property relationships governing imaging performance modulation.Furthermore,we critically analyze emerging strategies for optical imaging,US synergies,and magnetic resonance imaging(MRI).Multimodal bioimaging has also been elaborated,which could overcome the inherent trade-offs between resolution,penetration depth,and functional specificity in single-modal approaches.By elucidating mechanistic insights and translational challenges,this mini-review aims to establish a design framework of stimuli-responsive block copolymersbased for high fidelity bioimaging agents and accelerate their clinical translation in precise diagnosis and therapy.展开更多
4-Bromo-3-methylphenol(BMP)is an important chemical intermediate with wide applications in the fields of medicine and pesticides.The synthesis of BMP from m-cresol via bromination is easy to carry out on an industrial...4-Bromo-3-methylphenol(BMP)is an important chemical intermediate with wide applications in the fields of medicine and pesticides.The synthesis of BMP from m-cresol via bromination is easy to carry out on an industrial scale.However,due to the formation of regioisomeric impurities during bromination and the low melting point of BMP,the separation process is prone to the formation of oily substances,resulting in low yield and purity.In this work,a new cocrystallization engineering approach was proposed to separate and purify BMP.Through design of experiments,the cocrystallization process of BMP and triethylenediamine(DABCO)was optimized using a minimum-run resolution IV screening design combined with response surface methodology.In addition,the obtained 2BMP-DABCO powder was characterized by thermal analysis,powder X-ray diffraction,infrared spectroscopy,and scanning electron microscopy.Single crystals of 2BMP-DABCO were grown from acetone by slow evaporation,and detailed structural information was obtained through single-crystal X-ray diffraction.The self-assembly mechanism was further clarified by density functional theory calculations.This study provides a simple,robust,and scalable method for the production of BMP and offers a reference for the separation and purification of phenolic substances.展开更多
In the realm of large-scale power system energy storage,sodium-based batteries represent a cost-effective post-lithium energy storage technology,making inorganic solid-state sodium batteries(ISSSB)a critical branch of...In the realm of large-scale power system energy storage,sodium-based batteries represent a cost-effective post-lithium energy storage technology,making inorganic solid-state sodium batteries(ISSSB)a critical branch of this development.Inorganic solid-state electrolytes(ISSEs)are the core components of sodium batteries;however,they face significant challenges such as insufficient ionic conductivity,interfacial instability,and dendrite growth,all of which severely hinder practical application.This review critically assesses experimental protocols and theoretical frameworks related to mainstream ISSEs and systematizes optimization strategies aimed at overcoming these challenges.Leveraging integrated insights from both experimental and computational studies,the review first categorizes and summarizes the primary types of ISSEs,namely oxide-,sulfide-,and halide-based electrolytes.It then details interfacial optimization strategies focused on addressing three core interfacial issues:ion transport barriers resulting from mechanical incompatibility,side reactions stemming from electrochemical mismatch,and dendrite formation.Finally,the review advocates prioritizing in-depth research that integrates experimental and theoretical approaches to establish a closed-loop methodology encompassing predictive design,multiscale investigation,mechanistic exploration,and high-throughput automated experimentation,with feedback-driven refinement.This work serves as a comprehensive reference and systematic roadmap for future research on solid-state electrolytes(SSEs).展开更多
Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three ...Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers:Basic,Conversion&Stability(efficiency and volatility across actions),and Advanced Interactions&Activity(crossbehavior synergies and intensity).Using real Taobao(Alibaba’s primary e-commerce platform)logs(57,976 records for 10,203 users;25 November–03 December 2017),we conducted a hierarchical,layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution.Across logistic regression(LR),decision tree,random forest,XGBoost,and CatBoost models with stratified 5-fold cross-validation,the performance improvedmonotonically fromBasic to Conversion&Stability to Advanced features.With LR,F1 increased from 0.613(Basic)to 0.962(Advanced);boosted models achieved high discrimination(0.995 AUC Score)and an F1 score up to 0.983.Calibration and precision–recall analyses indicated strong ranking quality and acknowledged potential dataset and period biases given the short(9-day)window.By making feature contributions measurable and reproducible,the framework complements model-centric advances and offers a transparent blueprint for production-grade behavioralmodeling.The code and processed artifacts are publicly available,and future work will extend the validation to longer,seasonal datasets and hybrid approaches that combine automated feature learning with domain-driven design.展开更多
Two-step-processed(TSP)inverted p-i-n perovskite solar cells(PSCs)have demonstrated significant promise in tandem applications.However,the power conversion efficiency(PCE)of TSP p-i-n PSCs rarely exceeds 24%.Here,we d...Two-step-processed(TSP)inverted p-i-n perovskite solar cells(PSCs)have demonstrated significant promise in tandem applications.However,the power conversion efficiency(PCE)of TSP p-i-n PSCs rarely exceeds 24%.Here,we demonstrate that TSP perovskite films exhibit a vertically gradient distribution of residual PbI_(2)clusters,which form Schottky heterojunctions with the perovskite,leading to substantial interfacial energy-level mismatches within NiO_(x)-based TSP p-i-n PSCs.These limitations were effectively addressed via a vertical interfacial engineering enabled by dual-interface modification incorporating tin trifluoromethanesulfonate(Sn(OTF)_(2))and 4-Fluorophenylethylamine chloride(F-PEA)at the NiO_(x)/perovskite and perovskite/C60 interfaces,respectively.The functional Sn(OTF)_(2)not only enhances the conductivity of NiO_(x)films but also suppresses ion migration,while inducing the formation of a Pb-Sn mixed perovskite interlayer that precisely regulates the energy level at the NiO_(x)/perovskite interface.Complementally,F-PEA post-treatment effectively converts surface residual PbI_(2)clusters into a 2D perovskite capping layer,which simultaneously passivates surface defects and enhances energy-level alignment at the perovskite/C60 interface.Consequently,the optimized NiO_(x)-based TSP p-i-n PSCs achieve a notable PCE of 25.6%with superior operational stability.This study elucidates the underlying mechanisms limiting the efficiency of TSP p-i-n PSCs,while establishing design principles for these devices targeting 26%efficiency.展开更多
基金supported by grants from the Guangxi Science and Technology Major Project(GKAA24206023)the Biological Breeding-National Science and Technology Major Project(2024ZD04077)+2 种基金the National Natural Science Foundation of China(32272120)the National Key Research and Development Program of China(2024YFF1000800)the Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops Major Project(FCBRCE-202502,FCBRCE-202504).
文摘A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.
基金funding support from General Research Fund[Project No.14300525]from the Research Grants Council(RGC)of Hong Kong SAR,Chinafunding support from Natural Science Foundation of China(NSFC)Young Scientists Fund(Project No.22305203)+2 种基金NSFC Projects Nos.22309123,22422303,22303011,22033002,92261112 and U21A20328support from the Hong Kong Branch of National Precious Metals Material Engineering Research Center(NPMM)at City University of Hong Kongsupport from Young Collaborative Research Grant[Project No.C1003-23Y]support from RGC of Hong Kong SAR,China.
文摘Electrocatalytic nitric oxide(NO)reduction reaction(NORR)is a promising and sustainable process that can simultaneously realize green ammonia(NH3)synthesis and hazardous NO removal.However,current NORR performances are far from practical needs due to the lack of efficient electrocatalysts.Engineering the lattice of metal-based nanomaterials via phase control has emerged as an effective strategy to modulate their intrinsic electrocatalytic properties.Herein,we realize boron(B)-insertion-induced phase regulation of rhodium(Rh)nanocrystals to obtain amorphous Rh_(4)B nanoparticles(NPs)and hexagonal close-packed(hcp)RhB NPs through a facile wet-chemical method.A high Faradaic efficiency(92.1±1.2%)and NH_(3) yield rate(629.5±11.0μmol h^(−1) cm^(−2))are achieved over hcp RhB NPs,far superior to those of most reported NORR nanocatalysts.In situ spectro-electrochemical analysis and density functional theory simulations reveal that the excellent electrocatalytic performances of hcp RhB NPs are attributed to the upshift of d-band center,enhanced NO adsorption/activation profile,and greatly reduced energy barrier of the rate-determining step.A demonstrative Zn-NO battery is assembled using hcp RhB NPs as the cathode and delivers a peak power density of 4.33 mW cm−2,realizing simultaneous NO removal,NH3 synthesis,and electricity output.
基金funded by the National Key Research and Development Program of China(2022YFF1100300)National Natural Science Foundation of China(22108097)+2 种基金Key Research and Development Program of Jiangsu Province(BE2022850)Taihu Innovation-Leading Talent of Wuxi City(1026010241230040)Cross-Integration Innovation Funding of SFST(SFST2023-KY-10).
文摘Lacto-N-neotetraose(LNn T)is a crucial neutral core human milk oligosaccharide(HMO).In this study,we established a LNn T-producing Saccharomyces cerevisiae cell factory through comprehensive metabolic engineering.Specifically,the de novo biosynthetic pathway of LNn T was assembled by heterologously expressing the lactose permease(lac12)from Kluyveromyces lactis and the glycosyltransferase from Neisseria meningitidis in S.cerevisiae.Subsequently,carbon source regulation based on the glucose-sensitive GAL regulatory system was employed to optimize the expression time of heterologous genes,achieving a production of 15.61 mg/L of LNn T in shake-flask fermentation.In addition,the key rate-limiting steps involved in LNn T synthesis pathway were identified and the corresponding genes were overexpressed to enhance LNn T production,resulting in an 8-fold increase in LNn T titer compared to that of parental strain.To our knowledge,this is the first report on LNn T biosynthesis in S.cerevisiae,opening up the possibility of green production of LNn T using food-safe microorganisms.
基金supported in part by the Graduate Education Reform Research Project of Hubei University of Technology under Grant 2024YB003the Hubei University of Arts and Science,Teaching Research Project,under Grant JY2025018.
文摘The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to reshape talent cultivation but also presents significant challenges,including skill hollowing,ethical risks,and a growing disconnect between education and industry needs.Currently,graduate-level software engineering education struggles with outdated curricula and insufficient alignment with practical demands.In this paper,we propose a dual-core collaborative framework driven by“GenAI technology”and“industry demand”.Under this framework,we design a four-dimensional capability development path to enhance graduate students’innovation in software engineering practice.This path focuses on①scientific research innovation,②engineering problem-solving,③cross-domain collaborative evolution,and④ethical risk governance.The proposed approach promotes a shift from traditional knowledge transfer to human-machine collaborative innovation,aligning talent cultivation with the demands of the NQPF.
基金supported by the National Natural Science Foundation of China (Nos.22208218,22078196,and 22278268)the Natural Science Foundation of Shanghai (No.22ZR1460400)Collaborative Innovation Center of Fragrance Flavour and Cosmetics,and Collaborative Innovation Project of Shanghai Institute of Technology (No.XTCX2023-07)。
文摘The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytotoxicity.These limitations have catalyzed the development of intelligent stimuli-responsive block copolymers-based bioimaging agents,which was engineered to dynamically respond to endogenous biochemical cues(e.g.,p H gradients,redox potential,enzyme activity,hypoxia environment) or exogenous physical triggers(e.g.,photoirradiation,thermal gradients,ultrasound(US)/magnetic stimuli).Through spatiotemporally controlled structural transformations,stimuli-responsive block copolymers enable precise contrast targeting,activatable signal amplification,and theranostic integration,thereby substantially enhancing signal-to-noise ratios of bioimaging and diagnostic specificity.Hence,this mini-review systematically examines molecular engineering principles for designing p H-,redox-,enzyme-,light-,thermo-,and US/magnetic-responsive polymers,with emphasis on structure-property relationships governing imaging performance modulation.Furthermore,we critically analyze emerging strategies for optical imaging,US synergies,and magnetic resonance imaging(MRI).Multimodal bioimaging has also been elaborated,which could overcome the inherent trade-offs between resolution,penetration depth,and functional specificity in single-modal approaches.By elucidating mechanistic insights and translational challenges,this mini-review aims to establish a design framework of stimuli-responsive block copolymersbased for high fidelity bioimaging agents and accelerate their clinical translation in precise diagnosis and therapy.
基金supported by the National Natural Science Foundation of China(22177011(R.Z.Qiao),21977012(R.Z.Qiao),and 21572018(C.Li))the National High-Level Hospital Clinical Research Funding(2023-NHLHCRF-YXHZ-ZRMS-02)the Joint Project of BRCBC(Biomedical Translational Engineering Research Center of BUCT-CJFH)(XK2020-06).
文摘4-Bromo-3-methylphenol(BMP)is an important chemical intermediate with wide applications in the fields of medicine and pesticides.The synthesis of BMP from m-cresol via bromination is easy to carry out on an industrial scale.However,due to the formation of regioisomeric impurities during bromination and the low melting point of BMP,the separation process is prone to the formation of oily substances,resulting in low yield and purity.In this work,a new cocrystallization engineering approach was proposed to separate and purify BMP.Through design of experiments,the cocrystallization process of BMP and triethylenediamine(DABCO)was optimized using a minimum-run resolution IV screening design combined with response surface methodology.In addition,the obtained 2BMP-DABCO powder was characterized by thermal analysis,powder X-ray diffraction,infrared spectroscopy,and scanning electron microscopy.Single crystals of 2BMP-DABCO were grown from acetone by slow evaporation,and detailed structural information was obtained through single-crystal X-ray diffraction.The self-assembly mechanism was further clarified by density functional theory calculations.This study provides a simple,robust,and scalable method for the production of BMP and offers a reference for the separation and purification of phenolic substances.
基金the National Natural Science Foundation of China (52076076, 52006065)Fundamental Research Funds for Central Universities (2025JC003)Beijing Municipal Natural Science Foundation (3242022)
文摘In the realm of large-scale power system energy storage,sodium-based batteries represent a cost-effective post-lithium energy storage technology,making inorganic solid-state sodium batteries(ISSSB)a critical branch of this development.Inorganic solid-state electrolytes(ISSEs)are the core components of sodium batteries;however,they face significant challenges such as insufficient ionic conductivity,interfacial instability,and dendrite growth,all of which severely hinder practical application.This review critically assesses experimental protocols and theoretical frameworks related to mainstream ISSEs and systematizes optimization strategies aimed at overcoming these challenges.Leveraging integrated insights from both experimental and computational studies,the review first categorizes and summarizes the primary types of ISSEs,namely oxide-,sulfide-,and halide-based electrolytes.It then details interfacial optimization strategies focused on addressing three core interfacial issues:ion transport barriers resulting from mechanical incompatibility,side reactions stemming from electrochemical mismatch,and dendrite formation.Finally,the review advocates prioritizing in-depth research that integrates experimental and theoretical approaches to establish a closed-loop methodology encompassing predictive design,multiscale investigation,mechanistic exploration,and high-throughput automated experimentation,with feedback-driven refinement.This work serves as a comprehensive reference and systematic roadmap for future research on solid-state electrolytes(SSEs).
基金supported by the research fund of Hanyang University(HY-202500000001616).
文摘Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers:Basic,Conversion&Stability(efficiency and volatility across actions),and Advanced Interactions&Activity(crossbehavior synergies and intensity).Using real Taobao(Alibaba’s primary e-commerce platform)logs(57,976 records for 10,203 users;25 November–03 December 2017),we conducted a hierarchical,layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution.Across logistic regression(LR),decision tree,random forest,XGBoost,and CatBoost models with stratified 5-fold cross-validation,the performance improvedmonotonically fromBasic to Conversion&Stability to Advanced features.With LR,F1 increased from 0.613(Basic)to 0.962(Advanced);boosted models achieved high discrimination(0.995 AUC Score)and an F1 score up to 0.983.Calibration and precision–recall analyses indicated strong ranking quality and acknowledged potential dataset and period biases given the short(9-day)window.By making feature contributions measurable and reproducible,the framework complements model-centric advances and offers a transparent blueprint for production-grade behavioralmodeling.The code and processed artifacts are publicly available,and future work will extend the validation to longer,seasonal datasets and hybrid approaches that combine automated feature learning with domain-driven design.
基金financially supported by the National Nature Science Foundation of China (62504130)National Key Research and Development Program of China (2018YFB0704100)+3 种基金the Key university laboratory of highly efficient utilization of solar energy and sustainable development of Guangdong (Y01256331)the Technology Development Project of Henan Province (252102240047)the Pico Center at SUSTech CRF which receives support from the Presidential FundDevelopment and Reform Commission of Shenzhen Municipality
文摘Two-step-processed(TSP)inverted p-i-n perovskite solar cells(PSCs)have demonstrated significant promise in tandem applications.However,the power conversion efficiency(PCE)of TSP p-i-n PSCs rarely exceeds 24%.Here,we demonstrate that TSP perovskite films exhibit a vertically gradient distribution of residual PbI_(2)clusters,which form Schottky heterojunctions with the perovskite,leading to substantial interfacial energy-level mismatches within NiO_(x)-based TSP p-i-n PSCs.These limitations were effectively addressed via a vertical interfacial engineering enabled by dual-interface modification incorporating tin trifluoromethanesulfonate(Sn(OTF)_(2))and 4-Fluorophenylethylamine chloride(F-PEA)at the NiO_(x)/perovskite and perovskite/C60 interfaces,respectively.The functional Sn(OTF)_(2)not only enhances the conductivity of NiO_(x)films but also suppresses ion migration,while inducing the formation of a Pb-Sn mixed perovskite interlayer that precisely regulates the energy level at the NiO_(x)/perovskite interface.Complementally,F-PEA post-treatment effectively converts surface residual PbI_(2)clusters into a 2D perovskite capping layer,which simultaneously passivates surface defects and enhances energy-level alignment at the perovskite/C60 interface.Consequently,the optimized NiO_(x)-based TSP p-i-n PSCs achieve a notable PCE of 25.6%with superior operational stability.This study elucidates the underlying mechanisms limiting the efficiency of TSP p-i-n PSCs,while establishing design principles for these devices targeting 26%efficiency.
