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Buried interface bridging for inverted cesium-formamidinium triiodide perovskite solar cells with long operational stability

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science China Chemistry 2025年第01期 163-173页

作者： Chenhui Zhang Chunjun Liang Fulin Sun Ting Zhu Xinghai Huang Yuzhu Guo Xinyu Guo Kunyang Ge Dan Li Fangtian You Zhiqun He Key Laboratory of Luminescence and Optical information Ministry of Education Institute of Optoelectronic TechnologyBeijing Jiaotong University Department of Physics School of Physical Science and Engineering Beijing Jiaotong University

In the field of perovskite solar cells(PSCs), the research on defects in the buried interface has been relatively limited due to its non-exposure; however, this interface significantly impacts the performance enhancement of inverted PSCs. This study employs phenylethylammonium chloride(PEACl) molecules as a buffer layer to modify the buried interface of p-i-n structured PSCs,aiming to enhance the uniformity of self-assembled monolayers(SAMs) and facilitate the uniform nucleation and growth of perovskite films on the substrate. Furthermore, the introduction of the PEACl buffer layer effectively passivates defects at the bottom of the perovskite layer and notably enhances the crystal quality of the perovskite film by mitigating residual stress,thereby reducing nonradiative recombination loss. Following these optimizations, the MA-free PSCs treated with PEACl achieve a power conversion efficiency(PCE) of 24.11%, with significant improvements in storage, thermal stability, and operational stability. Particularly noteworthy is the device's performance in an unencapsulated state, whereas after 1,500 hours of continuous light operation stability testing, it retains 97% of its original efficiency. This study not only enriches the systematic understanding of the characteristics of the buried interface in PSCs but also contributes significantly to advancing the commercial production of perovskite photovoltaic technology.

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Morphology engineering of ZnO micro/nanostructures under mild conditions for optoelectronic application

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 498-503页

作者： Liang Chu Haoyu Shen Hudie Wei Hongyu Chen Guoqiang Ma Wensheng Yan institute of Carbon Neutrality and New Energy&school of Electronics and information Hangzhou Dianzi UniversityHangzhou 310018China school of Applied Physics and Materials Wuyi UniversityJiangmen 529020China

Zinc oxide(ZnO)serves as a crucial functional semiconductor with a wide direct bandgap of approximately 3.37 *** reaction is commonly used in the synthesis of ZnO micro/nanostructures,given its low cost,simplicity,and easy ***,ZnO morphology engineering has become desirable through the alteration of minor conditions in the reaction process,particularly at room *** this work,ZnO micro/nanostructures were synthesized in a solution by varying the amounts of the ammonia added at low temperatures(including room temperature).The formation of Zn^(2+)complexes by ammonia in the precursor regulated the reaction rate of the morphology engineering of ZnO,which resulted in various structures,such as nanoparticles,nanosheets,microflowers,and single ***,the obtained ZnO was used in the optoelectronic application of ultraviolet detectors.

关键词： morphology engineering low temperature ZnO nanosheets microflowers ultraviolet detector

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in Engineering & sciences 2025年第1期142卷 299-327页

作者： A.Robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia school of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho school of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the school of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Diffuse Interstellar Bandsλ6379,λ6614,andλ6660 in the LAMOST-MRS Spectra

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Research in Astronomy and Astrophysics 2022年第8期22卷 85-102页

作者： Ke-Fei Wu A-Li Luo Jian-Jun Chen Wen Hou Yong-Heng Zhao CAS Key Laboratory of Optical Astronomy National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China school of Astronomy and Space science University of Chinese Academy of SciencesBeijing 100049China school of information management&institute for astronomical science Dezhou UniversityDezhou 253023China

Diffuse interstellar bands(DIBs)have always been a mysterious existence in astronomical *** this work,we provide more DIB samples to slightly uncover this *** the LAMOST medium-resolution survey(MRS)spectra,we detected three DIBsλ6379,λ6614,andλ6660,obviously superimposed on the spectra of11,003 *** spectra cover spectral types from O to K,which can provide a large number of candidates for further research on *** sample shows a clear positive correlation between the strength of DIBs and extinction,which agrees with the result in the *** addition,there exist two peaks in each of the velocity distribution of these three DIBs,and the velocity differences between two peaks of each pair are *** reason for the two velocity components is due to the Galactic rotation.

关键词： ISM:molecules methods:data analysis (ISM:)dust extinction

ICA-Net: improving class activation for weakly supervised semantic segmentation via joint contrastive and simulation learning

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Optoelectronics Letters 2025年第3期 188-192页

作者： YE Zhuang LIU Ruyu SUN Bo school of information Engineering Chengdu Aviation Vocational and Technical College school of Computer science and Engineering Hangzhou Normal University Quanzhou institute of Equipment Manufacturing Haixi Institutes Chinese Academy of Sciences

In the field of optoelectronics, certain types of data may be difficult to accurately annotate, such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges. Weakly supervised learning can provide a more reliable approach in these situations. Current popular approaches mainly adopt the classification-based class activation maps (CAM) as initial pseudo labels to solve the task.

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The HⅠGas Fraction Scaling Relation of the Green Pea Galaxies

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Research in Astronomy and Astrophysics 2023年第6期23卷 56-64页

作者：刘思琦罗阿理张伟张彦霞孔啸赵永恒 CAS Key Laboratory of Optical Astronomy National Astronomical ObservatoriesBeijing 100101China University of Chinese Academy of sciences Beijing 100049China College of Computer and information management&institute for astronomical science Dezhou UniversityDezhou 253023China

Green Pea galaxies are compact galaxies with high star formation ***,limited samples of Green Pea galaxies have H I 21 cm *** the H I gas fraction(fH I≡MH I/M_(★))of Green Pea galaxies follows the existing scaling relations between the fH Iand NUV-r color or linear combinations of color and other physical quantities needs *** archival data of H I 21 cm observations,we investigate the scaling relation of the NUV-r color with the MH I/M_(★)of 38 Green Pea galaxies,including 17 detections and 21 *** H I to stellar mass ratios(fH I)of Green Pea galaxies deviate from the polynomial form,where a higher H I gas fraction is predicted given the current NUV-r color,even with the emission lines *** blue sources(NUV-r<1)from the comparison sample(ALFALFA-SDSS)follow a similar *** H I gas fraction scaling relations with linear combination forms of-0.34(N UV-r)-0.64 log(μ_(★,z))+5.9 and-0.77 log_(μ_(★)),i+0.26logS FRM_(★)+8.53,better predict the H I gas fraction of the Green Pea *** order to obtain accurate linear combined forms,higher-resolution photometry from space-based telescopes is needed.

关键词： galaxies:general galaxies:dwarf galaxies:formation

The Significance of Thermally Pulsing Asymptotic Giant Branch Stars in Post-starburst Galaxies

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Research in Astronomy and Astrophysics 2023年第1期23卷 184-201页

作者： Siqi Liu A-Li Luo CAS Key Laboratory of Optical Astronomy National Astronomical ObservatoriesBeijing 100101China University of Chinese Academy of sciences Beijing 100049China College of Computer and information management&institute for astronomical science Dezhou UniversityDezhou 253023China

We measure the significance of thermally pulsing asymptotic giant branch(TP-AGB)stars via the spectral energy distributions(SEDs)of a sample of post-starburst(PSB)galaxies at z=*** ground-and space-based photometry from the 3D-HST catalog,as well as associated near-infrared(NIR)Hubble Space Telescope(HST)slitless grism spectroscopy,we evaluate the importance of TP-AGB stars in the SEDs of 177 PSB galaxies by fitting simple stellar populations with different levels of TP-AGB *** grism spectra,despite their low resolution of R~100,enable the detection of molecular features specific to TP-AGB stars and thus improve constraints on their contribution.A majority(~70%)of galaxies in the PSB sample show features indicative of TPAGB stars,while the remainder does not and they are well fit by Bruzual&Charlot TP-AGB light *** spectra of sources classified to be the best fit by TP-AGB heavy/mild models reveal strong detections of NIR molecular features associated with TP-AGB ***,we observe a tentative trend with redshift where more TP-AGB heavy galaxies are observed in the higher redshift PSB galaxy ***,neglecting the contribution of TP-AGB stars can yield an over-prediction of stellar masses measured in the K-band ranging from 0.13-0.23 dex.

关键词： stars AGB and post-AGB-galaxies stellar content-galaxies peculiar

A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

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Computer Modeling in Engineering & sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen Bo Yang Siyu Lu Wenfeng Zheng Department of Computer science and Engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea school of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia school of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation