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| 1 | Single crystalline CH_3NH_3PbI_3 self-grown on FTO/TiO_2 substrate for high efficiency perovskite solar cells显示文摘Since its first report in 2009,CH_3NH_3PbI_3-based perovskite solar cells(PSCs)have emerged as one of the most exciting developments in the next generation photovoltaic(PV)technologies[1],with its PV conversion efficiency(PCE)rising spectacularly from3.81% to 22.1% in just 7 years.Such rapid advance is | Jinjin Zhao Guoli Kong Shulin Chen Qian Li Boyuan Huang Zhenghao Liu Xingyuan San Yujia Wang Chen Wang Yunce Zhen Haidan Wen Peng Gao Jiangyu Li | 2017 | Science Bulletin2017，62，17： | 12 |
| 2 | Dependence of corrosion resistance on grain boundary characteristics in a high nitrogen CrMn austenitic stainless steel显示文摘Processing schedules for grain boundary engineering involving different types of cold deformation(tension, compression, and rolling) and annealing were designed and carried out for 18Mn18Cr0.6N high nitrogen austenitic stainless steel. The grain boundary characteristic distribution was obtained and characterized by electron backscatter diffraction(EBSD) analysis. The corrosion resistance of the specimens with different grain boundary characteristic distribution was examined by using potentiodynamic polarization test. The corrosion behavior of different types of boundaries after sensitization was also studied.The fraction of low-∑ boundaries decreased with increasing strain, and it was insensitive to the type of cold deformation when the engineering strain was lower than 20%. At the strain of 30%, the largest and smallest fractions of low-∑ boundaries were achieved in cold-tensioned and rolled specimens, respectively. The fraction of low-∑ boundaries increased exponentially with the increase of grain size. The proportion of low-∑ angle grain boundaries increased with decreasing grain size. Increasing the fraction of low-∑ boundaries could improve the pitting corrosion resistance for the steels with the same grain size.After sensitization, the relative corrosion resistances of low-∑ angle grain boundaries, ∑3 boundaries, and ∑9 boundaries were 100%, 95%, and 25%, respectively, while ∑27 boundaries, other low-∑ boundaries and random high-angle grain boundaries had no resistance to corrosion. | Jianjun Qi Boyuan Huang Zhenhua Wang Hui Ding Junliang Xi Wantang Fu | 2017 | Journal of Materials Science & Technology2017，33，12： | 4 |
| 3 | Mapping intrinsic electromechanical responses at the nanoscale via sequential excitation scanning probe microscopy empowered by deep data显示文摘Ever-increasing hardware capabilities and computation powers have enabled acquisition and analysis of big scientific data at the nanoscale routine, though much of the data acquired often turn out to be redundant,noisy and/or irrelevant to the problems of interest, and it remains nontrivial to draw clear mechanistic insights from pure data analytics. In this work, we use scanning probe microscopy(SPM) as an example to demonstrate deep data methodology for nanosciences, transitioning from brute-force analytics such as data mining, correlation analysis and unsupervised classification to informed and/or targeted causative data analytics built on sound physical understanding. Three key ingredients of such deep data analytics are presented. A sequential excitation scanning probe microscopy(SE-SPM) technique is first developed to acquire high-quality, efficient and physically relevant data, which can be easily implemented on any standard atomic force microscope(AFM). Brute-force physical analysis is then carried out using a simple harmonic oscillator(SHO) model, enabling us to derive intrinsic electromechanical coupling of interest.Finally, principal component analysis(PCA) is carried out, which not only speeds up the analysis by four orders of magnitude, but also allows a clear physical interpretation of its modes in combination with SHO analysis. A rough piezoelectric material has been probed using such a strategy, enabling us to map its intrinsic electromechanical properties at the nanoscale with high fidelity, where conventional methods fail.The SE in combination with deep data methodology can be easily adapted for other SPM techniques to probe a wide range of functional phenomena at the nanoscale. | Boyuan Huang Ehsan Nasr Esfahani Jiangyu Li | 2019 | National Science Review2019，6，1： | 2 |
| 4 | Polar or nonpolar?That is not the question for perovskite solar cells显示文摘Perovskite solar cells(PSC)are promising next generation photovoltaic technologies,and there is considerable interest in the role of possible polarization of organic-inorganic halide perovskites(OIHPs)in photovoltaic conversion.The polarity of OIHPs is still hotly debated,however.In this review,we examine recent literature on the polarity of OIHPs from both theoretical and experimental points of view,and argue that they can be both polar and nonpolar,depending on composition,processing and environment.Implications of OIHP polarity to photovoltaic conversion are also discussed,and new insights gained through research efforts.In the future,integration of a local scanning probe with global macroscopic measurements in situ will provide invaluable microscopic insight into the intriguing macroscopic phenomena,while synchrotron diffractions and scanning transmission electron microscopy on more stable samples may ultimately settle the debate. | Boyuan Huang Zhenghao Liu Changwei Wu Yuan Zhang Jinjin Zhao Xiao Wang Jiangyu Li | 2021 | National Science Review2021，8，8： | 1 |
| 5 | Data Driven Uncertainty Evaluation for Complex Engineered System Design显示文摘Complex engineered systems are often difficult to analyze and design due to the tangled interdependencies among their subsystems and components. Conventional design methods often need exact modeling or accurate structure decomposition, which limits their practical application. The rapid expansion of data makes utilizing data to guide and improve system design indispensable in practical engineering. In this paper, a data driven uncertainty evaluation approach is proposed to support the design of complex engineered systems. The core of the approach is a data-mining based uncertainty evaluation method that predicts the uncertainty level of a specific system design by means of analyzing association relations along different system attributes and synthesizing the information entropy of the covered attribute areas, and a quantitative measure of system uncertainty can be obtained accordingly. Monte Carlo simulation is introduced to get the uncertainty extrema, and the possible data distributions under different situations is discussed in detail.The uncertainty values can be normalized using the simulation results and the values can be used to evaluate different system designs. A prototype system is established, and two case studies have been carried out. The case of an inverted pendulum system validates the effectiveness of the proposed method, and the case of an oil sump design shows the practicability when two or more design plans need to be compared. This research can be used to evaluate the uncertainty of complex engineered systems completely relying on data, and is ideally suited for plan selection and performance analysis in system design. | LIU Boyuan HUANG Shuangxi FAN Wenhui XIAO Tianyuan James HUMANN LAI Yuyang JIN Yan | 2016 | Chinese Journal of Mechanical Engineering2016，29，5： | 1 |
| 6 | Data augmentation in microscopic images for material data mining显示文摘Recent progress in material data mining has been driven by high-capacity models trained on large datasets.However,collecting experimental data(real data)has been extremely costly owing to the amount of human effort and expertise required.Here,we develop a novel transfer learning strategy to address problems of small or insufficient data.This strategy realizes the fusion of real and simulated data and the augmentation of training data in a data mining procedure.For a specific task of grain instance image segmentation,this strategy aims to generate synthetic data by fusing the images obtained from simulating the physical mechanism of grain formation and the“image style”information in real images.The results show that the model trained with the acquired synthetic data and only 35%of the real data can already achieve competitive segmentation performance of a model trained on all of the real data.Because the time required to perform grain simulation and to generate synthetic data are almost negligible as compared to the effort for obtaining real data,our proposed strategy is able to exploit the strong prediction power of deep learning without significantly increasing the experimental burden of training data preparation. | Boyuan Ma Xiaoyan Wei Chuni Liu Xiaojuan Ban Haiyou Huang Hao Wang Weihua Xue Stephen Wu Mingfei Gao Qing Shen Michele Mukeshimana Adnan Omer Abuassba Haokai Shen Yanjing Su | 2020 | npj Computational Materials2020，，1： | 1 |
| 7 | Author Correction:Data augmentation in microscopic images for material data mining显示文摘The original version of this article omitted the following from the Acknowledgements:“This work was supported by Beijing Top Discipline for Artificial Intelligent Science and Engineering,University of Science and Technology Beijing”.This has now been corrected in both the PDF and HTML versions of the article. | Boyuan Ma Xiaoyan Wei Chuni Liu Xiaojuan Ban Haiyou Huang Hao Wang Weihua Xue Stephen Wu Mingfei Gao Qing Shen Michele Mukeshimana Adnan Omer Abuassba Haokai Shen Yanjing Su | 2020 | npj Computational Materials2020，，1： | 0 |
| 8 | Achieving oxidation protection effect for strips hot rolling via Al_(2)O_(3) nanofluid lubrication显示文摘It was discovered the application of Al_(2)O_(3) nanofluid as lubricant for steel hot rolling could synchronously achieve oxidation protection of strips surface.The underlying mechanism was investigated through hot rolling tests and molecular dynamics (MD) simulations.The employment of Al_(2)O_(3) nanoparticles contributed to significant enhancement in the lubrication performance of lubricant.The rolled strip exhibited the best surface topography that the roughness reached lowest with the sparsest surface defects.Besides,the oxide scale generated on steel surface was also thinner,and the ratio of Fe_(2)O_(3) among various iron oxides became lower.It was revealed the above oxidation protection effect of Al_(2)O_(3) nanofluid was attributed to the deposition of nanoparticles on metal surface during hot rolling.A protective layer in the thickness of about 193 nm was formed to prevent the direct contact between steel matrix and atmosphere,which was mainly composed of Al_(2)O_(3) and sintered organic molecules.MD simulations confirmed the diffusion of O_(2) and H_(2)O could be blocked by the Al_(2)O_(3) layer through physical absorption and penetration barrier effect. | Jianlin Sun Boyuan Huang Jiaqi He Erchao Meng Qianhao Chang | 2023 | International Journal of Minerals,Metallurgy and Materials2023，30，5： | 0 |
| 9 | Fano resonance-enhanced Si/MoS_(2) photodetector显示文摘In this work,a Si∕MoS_(2) heterojunction photodetector enhanced by hot electron injection through Fano resonance is developed.By preparing Au oligomers using capillary-assisted particle assembly(CAPA)on the silicon substrate with a nanohole array and covering few-layer MoS_(2) with Au electrodes on top of the oligomer structures,the Fano resonance couples with a Si∕MoS_(2) heterojunction.With on-resonance excitation,Fano resonance generated many hot electrons on the surface of oligomers,and the hot electrons were injected into MoS_(2),providing an increased current in the photodetector under a bias voltage.The photodetectors exhibited a broadband photoresponse ranging from 450 to 1064 nm,and a large responsivity up to 52 A/W at a wavelength of 785 nm under a bias voltage of 3 V.The demonstrated Fano resonance-enhanced Si∕MoS_(2) heterojunction photodetector provides a strategy to improve the photoresponsivity of two-dimensional materials-based photodetectors for optoelectronic applications in the field of visible and near-infrared detection. | TIANXUN GONG BOYUAN YAN TAIPING ZHANG WEN HUANG YUHAO HE XIAOYU XU SONG SUN XIAOSHENG ZHANG | 2023 | Photonics Research2023，11，12： | 0 |
| 10 | 3D printing of functional bioengineered constructs for neural regeneration: a review显示文摘Three-dimensional(3D)printing technology has opened a new paradigm to controllably and reproducibly fabricate bioengineered neural constructs for potential applications in repairing injured nervous tissues or producing in vitro nervous tissue models.However,the complexity of nervous tissues poses great challenges to 3D-printed bioengineered analogues,which should possess diverse architectural/chemical/electrical functionalities to resemble the native growth microenvironments for functional neural regeneration.In this work,we provide a state-of-the-art review of the latest development of 3D printing for bioengineered neural constructs.Various 3D printing techniques for neural tissue-engineered scaffolds or living cell-laden constructs are summarized and compared in terms of their unique advantages.We highlight the advanced strategies by integrating topographical,biochemical and electroactive cues inside 3D-printed neural constructs to replicate in vivo-like microenvironment for functional neural regeneration.The typical applications of 3D-printed bioengineered constructs for in vivo repair of injured nervous tissues,bio-electronics interfacing with native nervous system,neural-on-chips as well as brain-like tissue models are demonstrated.The challenges and future outlook associated with 3D printing for functional neural constructs in various categories are discussed. | Hui Zhu Cong Yao Boyuan Wei Chenyu Xu Xinxin Huang Yan Liu Jiankang He Jianning Zhang Dichen Li | 2023 | International Journal of Extreme Manufacturing2023，5，4： | 0 |
| 11 | Self-powered forest ambient monitoring microsystem based on wind energy hybrid nanogenerators显示文摘In response to the call for zero-carbon energy supply for Internet of Things(IoTs)applications and to get rid of the dependence of traditional distributed IoTs devices on batteries,the invention of nanogenerators that can convert wind energy in the surrounding environment into electrical energy have received widespread attention.Herein,a wind energy hybrid harvester(WH-EH)combining a soft-friction and positive-directional triboelectric nanogenerator(SP-TENG)and a hierarchical rotating electromagnetic nanogenerator(HR-EMG)is reported to construct a self-powered forest environment monitoring microsystem.With the design of thin inner wall beams and comb-shaped electrodes,the SP-TENG is able to change the output into positivedirectional,which can be stored directly in the energy storage device,breaking the limitation of the alternating positive and negative output of conventional TENGs.In addition,the HR-EMG embeds coils in the cup lid to make the most of the available space in the external package.In the WH-EH,a layered structure,including the HR-EMG and SP-TENG is adopted to jointly utilize wind energy for both higher output and higher utilization.In order to effectively implement wireless monitoring of the forest environment,the WH-EH is further utilized to develop a self-powered forest environment monitoring microsystem by powering the IoTs sensor nodes,realizing ambient temperature and humidity sampling and wireless transmission,so as to achieve the purpose of preventing forest fires.It is believed that the development of the WH-EH and the self-powered forest environment monitoring microsystem provides diverse options for the practicalization of self-powered IoTs systems and the energy supply problem of IoTs sensor networks. | LI BoYuan QIU Yu HUANG Peng TANG WenJie ZHANG XiaoSheng | 2022 | Science China(Technological Sciences)2022，65，10： | 0 |
| 12 | Highly spectra-stable pure blue perovskite light-emitting diodes based on copper and potassium co-doped quantum dots显示文摘Halide perovskite light emitting diodes(LEDs)have gained great progress in recent years.However,mixed-halide perovskites for blue LEDs usually suffer from electroluminescence(EL)spectra shift at a high applied voltage or current density,limiting their efficiency.In this work,we report a strategy of using single-layer perovskite quantum dots(QDs)film to tackle the electroluminescence spectra shift in pure-blue perovskite LEDs and improve the LED efficiency by co-doping copper and potassium in the mixed-halide perovskite QDs.As a result,we obtained pure-blue halide perovskite QD-LEDs with stable EL spectra centred at 469 nm even at a current density of 1,617 mA·cm^(−2).The optimal device presents a maximum external quantum efficiency(EQE)of 2.0%.The average maximum EQE and luminance of the LEDs are 1.49%and 393 cd·m^(−2),increasing 62%and 66%compared with the control LEDs.Our study provides an effective strategy for achieving spectra-stable and highly efficient pure-blue perovskite LEDs. | Fang Chen Wenjie Ming Yongfei Li Yun Gao Lea Pasquale Kexin Yao Boyuan Huang Qiuting Cai Guochao Lu Jizhong Song Mirko Prato Xingliang Dai Haiping He Zhizhen Ye | 2023 | Nano Research2023，16，5： | 0 |
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