Traditional polymeric photocatalysts are typically constructed using aromatic building blocks to enhanceπ-conjugation.However,their inherent hydrophobicity and rigid structure lead to poor dispersibility in aqueous s...Traditional polymeric photocatalysts are typically constructed using aromatic building blocks to enhanceπ-conjugation.However,their inherent hydrophobicity and rigid structure lead to poor dispersibility in aqueous solutions,resulting in significant optical losses and exciton recombination.In this study,two series of six novel polymer photocatalysts(FLUSO,FLUSO-PEG10,FLUSO-PEG30;CPDTSO,CPDTSO-PEG10,CPDTSO-PEG30)are designed and synthesized by incorporating the hydrophilic,non-conjugated polyethylene glycol(PEG)chain,into both the main and side chains of polymers.By precisely optimizing the ratio of hydrophilic PEG segments,the water dispersibility is significantly improved while the light absorption capability of the polymer photocatalysts is well maintained.The experimental results confirm that the optimized FLUSO-PEG10 exhibits excellent photocatalytic hydrogen evolution rate,reaching up to 33.9 mmol/(g·h),which is nearly three times higher than that of fullyπ-conjugated counterparts.Water contact angles and particle size analyses reveal that incorporating non-conjugated segments into the main chains enhances the capacitance of the polymer/water interface and reduces particle aggregation,leading to improved photocatalyst dispersion and enhanced charge generation.展开更多
Pb(Zr,Ti)O_(3)-Pb(Zn_(1/3)Nb_(2/3))O_(3) (PZT-PZN) based ceramics, as important piezoelectric materials, have a wide range of applications in fields such as sensors and actuators, thus the optimization of their piezoe...Pb(Zr,Ti)O_(3)-Pb(Zn_(1/3)Nb_(2/3))O_(3) (PZT-PZN) based ceramics, as important piezoelectric materials, have a wide range of applications in fields such as sensors and actuators, thus the optimization of their piezoelectric properties has been a hot research topic. This study investigated the effects of phase boundary engineering and domain engineering on (1-x)[0.8Pb(Zr_(0.5)Ti_(0.5))O_(3)-0.2Pb(Zn_(1/3)Nb_(2/3))O_(3)]-xBi(Zn_(0.5)Ti_(0.5))O_(3) ((1-x)(0.8PZT-0.2PZN)- xBZT) ceramic to obtain excellent piezoelectric properties. The crystal phase structure and microstructure of ceramic samples were characterized. The results showed that all samples had a pure perovskite structure, and the addition of BZT gradually increased the grain size. The addition of BZT caused a phase transition in ceramic samples from the morphotropic phase boundary (MPB) towards the tetragonal phase region, which is crucial for optimizing piezoelectric properties. By adjusting content of BZT and precisely controlling position of the phase boundary, the piezoelectric performance can be optimized. Domain structure is one of the key factors affecting piezoelectric performance. By using domain engineering techniques to optimize grain size and domain size, piezoelectric properties of ceramic samples have been significantly improved. Specifically, excellent piezoelectric properties (piezoelectric constant d_(33)=320 pC/N, electromechanical coupling factor kp=0.44) were obtained simultaneously for x=0.08. Based on experimental results and theoretical analysis, influence mechanisms of phase boundary engineering and domain engineering on piezoelectric properties were explored. The study shows that addition of BZT not only promotes grain growth, but also optimizes the domain structure, enabling the polarization reversal process easier, thereby improving piezoelectric properties. These research results not only provide new ideas for the design of high-performance piezoelectric ceramics, but also lay a theoretical foundation for development of related electronic devices.展开更多
In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave pow...In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.展开更多
Assessing the vulnerability of a platform is crucial in its design.In fact,the results obtained from vulnerability analyses provide valuable information,leading to precise design choices or corrective solutions that e...Assessing the vulnerability of a platform is crucial in its design.In fact,the results obtained from vulnerability analyses provide valuable information,leading to precise design choices or corrective solutions that enhance the platform's chances of surviving different scenarios.Such scenarios can involve various types of threats that can affect the platform's survivability.Among such,blast waves impacting the platform's structure represent critical conditions that have not yet been studied in detail.That is,frameworks for vulnerability assessment that can deal with blast loading have not been presented yet.In this context,this work presents a fast-running engineering tool that can quantify the risk that a structure fails when it is subjected to blast loading from the detonation of high explosive-driven threats detonating at various distances from the structure itself.The tool has been implemented in an in-house software that calculates vulnerability to various impacting objects,and its capabilities have been shown through a simplified,yet realistic,case study.The novelty of this research lies in the development of an integrated computational environment capable of calculating the platform's vulnerability to blast waves,without the need for running expensive finite element simulations.In fact,the proposed tool is fully based on analytical models integrated with a probabilistic approach for vulnerability calculation.展开更多
With the continuous expansion of deep underground engineering and the growing demand for safety monitoring,microseismic monitoring has become a core method for early warning of rock mass fracture and engineering stabi...With the continuous expansion of deep underground engineering and the growing demand for safety monitoring,microseismic monitoring has become a core method for early warning of rock mass fracture and engineering stability assessment.To address problems in existing methods,such as low data processing efficiency and poor phase recognition accuracy under low signal-to-noise ratio(SNR)conditions in complex geological environments,this study proposes an intelligent phase picking model based on ResUNet.The model integrates the residual learning mechanism of ResNet with the multi-scale feature extraction capability of UNet,effectively mitigating the vanishing gradient problem in deep networks.It also achieves cross-layer fusion of shallow detail features and deep semantic features through skip connections in the encoder-decoder structure.Compared with traditional short-time average/long-time average(STA/LTA)algorithms and advanced neural network models such as PhaseNet and EQTransformer,ResUNet shows superior performance in picking P-and S-wave phases.The model was trained on 400000 labeled microseismic signals from the Stanford earthquake dataset(STEAD)and was successfully applied to the Shizhuyuan polymetallic mine in Hunan Province,China.The results demonstrate that ResUNet achieves high picking accuracy and robustness in complex geological conditions,offering reliable technical support for early warning of disasters such as rockburst in deep underground engineering.展开更多
Cell and Tissue Engineering provides exciting opportunities for studying development and Disease.In this talk,we will focus on cell chirality,also known as handedness and left-right(LR)asymmetry,which is an intrinsic ...Cell and Tissue Engineering provides exciting opportunities for studying development and Disease.In this talk,we will focus on cell chirality,also known as handedness and left-right(LR)asymmetry,which is an intrinsic capability of the cell telling left from right(1)The development of the vertebrate body plan with left-right asymmetry requires the emerging chiral morphogenesis at multicellular levels at specific embryonic stages.Changes in orientation of the LR axis due to genetic or environmental factors can lead to malformations and disease.However,the concept of cell chirality has never studied in detail until the recent development of novel engineering tools[2-3].We demonstrate that the cultivation of cells on micropatterned 2D surfaces and in 3D graded hydrogels reveals an intrinsic cellular LR asymmetry,which is dependent of cell phenotype and actin cytoskeleton.With these new tools,we examine the role of cell chirality on the embryonic development of cardiac LR asymmetry [4] as well as the barrier function of endothelium layers [5].We find that Protein Kinase C(PKC)activation reverses the inherent chirality from clockwise to counter clockwise in engineering systems [4-5].Interestingly,activation of PKC signaling reverses the directional bias of chick cardiac C-looping [4].Mediating endothelial cell chirality can regulate the permeability of endothelial layers[5].Overall,our results strongly suggest critical roles of cell chirality in cardiovascular development and disease.展开更多
Electrocatalytic carbon dioxide(CO_(2))reduction is an important way to achieve carbon neutrality by converting CO_(2)in-to high-value-added chemicals using electric energy.Carbon-based materials are widely used in va...Electrocatalytic carbon dioxide(CO_(2))reduction is an important way to achieve carbon neutrality by converting CO_(2)in-to high-value-added chemicals using electric energy.Carbon-based materials are widely used in various electrochemical reactions,including electrocatalytic CO_(2)reduction,due to their low cost and high activity.In recent years,defect engineering has attracted wide attention by constructing asymmetric defect centers in the materials,which can optimize the physicochemical properties of the mater-ial and improve its electrocatalytic activity.This review summarizes the types,methods of formation and defect characterization tech-niques of defective carbon-based materials.The advantages of defect engineering and the advantages and disadvantages of various defect formation methods and characterization techniques are also evaluated.Finally,the challenges of using defective carbon-based materials in electrocatalytic CO_(2)reduction are investigated and opportunities for their use are discussed.It is believed that this re-view will provide suggestions and guidance for developing defective carbon-based materials for CO_(2)reduction.展开更多
Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function...Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.展开更多
Interface engineering is widely employed to enhance the performance of formamidinium lead triiodide(FAPbI_(3))perovskite solar cells.In this study,six different FAPbI_(3)/PbX(X=S,Se and Te)heterostructures are constru...Interface engineering is widely employed to enhance the performance of formamidinium lead triiodide(FAPbI_(3))perovskite solar cells.In this study,six different FAPbI_(3)/PbX(X=S,Se and Te)heterostructures are constructed,including the PbI interface and I interface perovskite.In addition,the lead vacancies(V-Pb)and iodine vacancies(V-I)are designed at the perovskite interface.The results show that the PbI interface is more stable than I interface in the heterostructures.The PbX covering layer on the surface of the FAPbI_(3) perovskite stabilizes the perovskite octahedral structure by interface interactions and charge reconstruction that are beneficial to passivate perovskite interface defects and inhibit the phase transition.It shows that the PbTe covering layer exhibits the best passivation effect for lead vacancy defects,while PbS covering layer shows the best passivation effect for iodine vacancy defects.Additionally,appropriate structural stress can strengthen the thermal stability of defective perovskite.This work reveals the FAPbI_(3)/PbX interface engineering,and offers new insights into effectively passivating defects and improving the stability of FAPbI_(3).展开更多
文摘Traditional polymeric photocatalysts are typically constructed using aromatic building blocks to enhanceπ-conjugation.However,their inherent hydrophobicity and rigid structure lead to poor dispersibility in aqueous solutions,resulting in significant optical losses and exciton recombination.In this study,two series of six novel polymer photocatalysts(FLUSO,FLUSO-PEG10,FLUSO-PEG30;CPDTSO,CPDTSO-PEG10,CPDTSO-PEG30)are designed and synthesized by incorporating the hydrophilic,non-conjugated polyethylene glycol(PEG)chain,into both the main and side chains of polymers.By precisely optimizing the ratio of hydrophilic PEG segments,the water dispersibility is significantly improved while the light absorption capability of the polymer photocatalysts is well maintained.The experimental results confirm that the optimized FLUSO-PEG10 exhibits excellent photocatalytic hydrogen evolution rate,reaching up to 33.9 mmol/(g·h),which is nearly three times higher than that of fullyπ-conjugated counterparts.Water contact angles and particle size analyses reveal that incorporating non-conjugated segments into the main chains enhances the capacitance of the polymer/water interface and reduces particle aggregation,leading to improved photocatalyst dispersion and enhanced charge generation.
基金National Natural Science Foundation of China (52202139, 52072178)。
文摘Pb(Zr,Ti)O_(3)-Pb(Zn_(1/3)Nb_(2/3))O_(3) (PZT-PZN) based ceramics, as important piezoelectric materials, have a wide range of applications in fields such as sensors and actuators, thus the optimization of their piezoelectric properties has been a hot research topic. This study investigated the effects of phase boundary engineering and domain engineering on (1-x)[0.8Pb(Zr_(0.5)Ti_(0.5))O_(3)-0.2Pb(Zn_(1/3)Nb_(2/3))O_(3)]-xBi(Zn_(0.5)Ti_(0.5))O_(3) ((1-x)(0.8PZT-0.2PZN)- xBZT) ceramic to obtain excellent piezoelectric properties. The crystal phase structure and microstructure of ceramic samples were characterized. The results showed that all samples had a pure perovskite structure, and the addition of BZT gradually increased the grain size. The addition of BZT caused a phase transition in ceramic samples from the morphotropic phase boundary (MPB) towards the tetragonal phase region, which is crucial for optimizing piezoelectric properties. By adjusting content of BZT and precisely controlling position of the phase boundary, the piezoelectric performance can be optimized. Domain structure is one of the key factors affecting piezoelectric performance. By using domain engineering techniques to optimize grain size and domain size, piezoelectric properties of ceramic samples have been significantly improved. Specifically, excellent piezoelectric properties (piezoelectric constant d_(33)=320 pC/N, electromechanical coupling factor kp=0.44) were obtained simultaneously for x=0.08. Based on experimental results and theoretical analysis, influence mechanisms of phase boundary engineering and domain engineering on piezoelectric properties were explored. The study shows that addition of BZT not only promotes grain growth, but also optimizes the domain structure, enabling the polarization reversal process easier, thereby improving piezoelectric properties. These research results not only provide new ideas for the design of high-performance piezoelectric ceramics, but also lay a theoretical foundation for development of related electronic devices.
文摘In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.
文摘Assessing the vulnerability of a platform is crucial in its design.In fact,the results obtained from vulnerability analyses provide valuable information,leading to precise design choices or corrective solutions that enhance the platform's chances of surviving different scenarios.Such scenarios can involve various types of threats that can affect the platform's survivability.Among such,blast waves impacting the platform's structure represent critical conditions that have not yet been studied in detail.That is,frameworks for vulnerability assessment that can deal with blast loading have not been presented yet.In this context,this work presents a fast-running engineering tool that can quantify the risk that a structure fails when it is subjected to blast loading from the detonation of high explosive-driven threats detonating at various distances from the structure itself.The tool has been implemented in an in-house software that calculates vulnerability to various impacting objects,and its capabilities have been shown through a simplified,yet realistic,case study.The novelty of this research lies in the development of an integrated computational environment capable of calculating the platform's vulnerability to blast waves,without the need for running expensive finite element simulations.In fact,the proposed tool is fully based on analytical models integrated with a probabilistic approach for vulnerability calculation.
基金Project(2022YFC2905100)supported by the National Key Research and Development Program of ChinaProject(52174098)supported by the National Natural Science Foundation of China。
文摘With the continuous expansion of deep underground engineering and the growing demand for safety monitoring,microseismic monitoring has become a core method for early warning of rock mass fracture and engineering stability assessment.To address problems in existing methods,such as low data processing efficiency and poor phase recognition accuracy under low signal-to-noise ratio(SNR)conditions in complex geological environments,this study proposes an intelligent phase picking model based on ResUNet.The model integrates the residual learning mechanism of ResNet with the multi-scale feature extraction capability of UNet,effectively mitigating the vanishing gradient problem in deep networks.It also achieves cross-layer fusion of shallow detail features and deep semantic features through skip connections in the encoder-decoder structure.Compared with traditional short-time average/long-time average(STA/LTA)algorithms and advanced neural network models such as PhaseNet and EQTransformer,ResUNet shows superior performance in picking P-and S-wave phases.The model was trained on 400000 labeled microseismic signals from the Stanford earthquake dataset(STEAD)and was successfully applied to the Shizhuyuan polymetallic mine in Hunan Province,China.The results demonstrate that ResUNet achieves high picking accuracy and robustness in complex geological conditions,offering reliable technical support for early warning of disasters such as rockburst in deep underground engineering.
基金supported by the National Institutes of Health ( OD / NICHD DP2HD083961)National Science Foundation ( CAREER CMMI-1254656)+2 种基金American Heart Association ( 13SDG17230047)March of Dimes ( MOD 5-FY14-111)Leo Q. Wan is a Pew Scholar in Biomedical Sciences ( PEW 00026185) ,supported by the Pew Charitable Trusts
文摘Cell and Tissue Engineering provides exciting opportunities for studying development and Disease.In this talk,we will focus on cell chirality,also known as handedness and left-right(LR)asymmetry,which is an intrinsic capability of the cell telling left from right(1)The development of the vertebrate body plan with left-right asymmetry requires the emerging chiral morphogenesis at multicellular levels at specific embryonic stages.Changes in orientation of the LR axis due to genetic or environmental factors can lead to malformations and disease.However,the concept of cell chirality has never studied in detail until the recent development of novel engineering tools[2-3].We demonstrate that the cultivation of cells on micropatterned 2D surfaces and in 3D graded hydrogels reveals an intrinsic cellular LR asymmetry,which is dependent of cell phenotype and actin cytoskeleton.With these new tools,we examine the role of cell chirality on the embryonic development of cardiac LR asymmetry [4] as well as the barrier function of endothelium layers [5].We find that Protein Kinase C(PKC)activation reverses the inherent chirality from clockwise to counter clockwise in engineering systems [4-5].Interestingly,activation of PKC signaling reverses the directional bias of chick cardiac C-looping [4].Mediating endothelial cell chirality can regulate the permeability of endothelial layers[5].Overall,our results strongly suggest critical roles of cell chirality in cardiovascular development and disease.
文摘Electrocatalytic carbon dioxide(CO_(2))reduction is an important way to achieve carbon neutrality by converting CO_(2)in-to high-value-added chemicals using electric energy.Carbon-based materials are widely used in various electrochemical reactions,including electrocatalytic CO_(2)reduction,due to their low cost and high activity.In recent years,defect engineering has attracted wide attention by constructing asymmetric defect centers in the materials,which can optimize the physicochemical properties of the mater-ial and improve its electrocatalytic activity.This review summarizes the types,methods of formation and defect characterization tech-niques of defective carbon-based materials.The advantages of defect engineering and the advantages and disadvantages of various defect formation methods and characterization techniques are also evaluated.Finally,the challenges of using defective carbon-based materials in electrocatalytic CO_(2)reduction are investigated and opportunities for their use are discussed.It is believed that this re-view will provide suggestions and guidance for developing defective carbon-based materials for CO_(2)reduction.
文摘Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.
基金Projects(51673214,62004225)supported by the National Natural Science Foundation of ChinaProject(2022YFB3803300)supported by the National Key Research and Development Program of ChinaProject(2024ZZTS0776)supported by the Key Innovation Project of Graduate of Central South University,China。
文摘Interface engineering is widely employed to enhance the performance of formamidinium lead triiodide(FAPbI_(3))perovskite solar cells.In this study,six different FAPbI_(3)/PbX(X=S,Se and Te)heterostructures are constructed,including the PbI interface and I interface perovskite.In addition,the lead vacancies(V-Pb)and iodine vacancies(V-I)are designed at the perovskite interface.The results show that the PbI interface is more stable than I interface in the heterostructures.The PbX covering layer on the surface of the FAPbI_(3) perovskite stabilizes the perovskite octahedral structure by interface interactions and charge reconstruction that are beneficial to passivate perovskite interface defects and inhibit the phase transition.It shows that the PbTe covering layer exhibits the best passivation effect for lead vacancy defects,while PbS covering layer shows the best passivation effect for iodine vacancy defects.Additionally,appropriate structural stress can strengthen the thermal stability of defective perovskite.This work reveals the FAPbI_(3)/PbX interface engineering,and offers new insights into effectively passivating defects and improving the stability of FAPbI_(3).
