Article
Physics, Condensed Matter
Anand Pandey, Lokendra Kumar
Summary: This research reveals the internal relationship between the processing temperature and the optoelectronic properties of MAPbI(3-x)Cl(x) perovskite films, and finds that strain in the perovskite films is eliminated at a specific processing temperature. Furthermore, the charge transport properties of the films are explored.
PHYSICA B-CONDENSED MATTER
(2022)
Article
Chemistry, Physical
Xusheng Zhao, Jun Dong, Daofu Wu, Jiaer Zhou, Julin Feng, Yanqing Yao, Cun Yun Xu, Xiude Yang, Xiaosheng Tang, Qunliang Song
Summary: A simple interface treatment strategy using DETAPMP successfully passivated the SnO2/MAPbI(3-x)Cl(x) interface, leading to improved efficiency and long-term stability of perovskite solar cells.
ACS APPLIED ENERGY MATERIALS
(2021)
Article
Materials Science, Multidisciplinary
Hsin-Chang Lin, Li-Yin Chen, Tsung-Hsien Lin
Summary: The study focuses on the utilization of mixed-lead halide precursors to improve hysteresis in room-temperature air-quenching perovskite solar cells, resulting in a low hysteresis effect index of -0.032. Smooth film morphology and low trap density contributed by the mixed-lead halide precursor were identified as key factors in overcoming hysteresis in the PSCs.
MATERIALS CHEMISTRY AND PHYSICS
(2021)
Article
Chemistry, Multidisciplinary
Sai Liu, Yu Wei Du, Chi Yan Tso, Hau Him Lee, Rui Cheng, Shien-Ping Feng, Kin Man Yu
Summary: A hydrated MAPbI(3-)(x)Cl(x) thermochromic perovskite smart window is proposed, with excellent optical performance and thermochromic effect, reversible transition between transparent and tinted states, low transition temperature and short transition time. It has the potential for wide applications in energy-efficient buildings.
ADVANCED FUNCTIONAL MATERIALS
(2021)
Article
Energy & Fuels
Mohammad Mahdi Tavakoli, Ziba Fazel, Rouhollah Tavakoli, Seckin Akin, Soumitra Satapathi, Daniel Prochowicz, Pankaj Yadav
Summary: A novel approach using metal alloying of halide-perovskite domain via ion-transfer is developed for the growth of high-quality perovskite films. This technique enables the replacement of toxic Pb metal with other metals and leads to more efficient solar cells. The approach shows potential for other alloys as well.
Article
Physics, Applied
Sidrah Younus, Faisal Mustafa, Mehmet Egilmez, Mariam Al Awadhi, Wael Abuzaid, Sami El Khatib, Serhat Alagoz, Abdul Hai Alami
Summary: FexCu100-x binary alloys are attracting attention due to their complex magnetic phase diagram and the difficulty of achieving single phases. While the physical properties of low-Cu doping in Fe-Cu alloys have been studied, the understanding of high Cu doping remains limited. In this study, different techniques including XRD, SEM, electrical transport, and magnetic measurements were used to investigate the Fe15Cu85 single-phase alloy system. The experimental results reveal a second-order phase transition and negative magnetoresistance, which can be explained by classical models.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2023)
Article
Chemistry, Physical
Likang Zhou, Junhao Fei, Wei Fang, Luqing Shao, Qianjiang Liu, Huiwen He, Meng Ma, Yanqin Shi, Si Chen, Xu Wang
Summary: Different from traditional concept, true colors that can be precisely controlled are obtained by changing the volume fraction deviation. The tunable photonic bandgap varies linearly in the visible region by controlling the volume fraction of two building blocks. The stability of photonic pigments is improved by utilizing the metastable structures of red photonic pigment.
NANOSCALE HORIZONS
(2022)
Review
Chemistry, Multidisciplinary
Annemieke Janssen, Quynh N. Nguyen, Younan Xia
Summary: This article discusses the importance of crystal structure in engineering the properties of metal nanocrystals, with a focus on noble metals. Various strategies for fabricating colloidal metal nanocrystals in unconventional phases have been developed, highlighting mechanistic insights, experimental controls, and enhanced catalytic properties. The article concludes with perspectives on remaining issues and future opportunities.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2021)
Article
Nanoscience & Nanotechnology
Ibrahima Gueye, Yasuhiro Shirai, Dhruba B. Khadka, Okkyun Seo, Satoshi Hiroi, Masatoshi Yanagida, Kenjiro Miyano, Osami Sakata
Summary: The study reveals that the stability issues of halide perovskite solar cells are related to the chemical decomposition at different transport layer (TL) interfaces, resulting in migration and formation of different molecular fragments, which in turn affect their long-term stability.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Engineering, Electrical & Electronic
N. Sivakumar, Subhashis Saha, Ramakrishna Madaka, Narendra Bandaru, Jatindra Kumar Rath
Summary: To address the electronic degradation issue in organic-inorganic perovskite solar cells, we have conducted a study using crystalline perovskite absorber layers. Single-crystal X-ray diffraction confirmed the crystal structures of MAPbI(3).H2O and MAPbI(3). Spectroscopic studies revealed the optical band gaps of these perovskites. The investigation of solar cell devices using these crystalline perovskites is ongoing.
JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
(2023)
Article
Materials Science, Multidisciplinary
Jiabin Hao, Zeming Wang, Hongcheng Gao, Xiaoxuan Li, Bo Yang, Xu He
Summary: The article introduces the research status of one-dimensional perovskite nanowire materials in the field of photonics and photovoltaic devices, and investigates their performance and structural changes under light conditions. The study found that the prolongation of light illumination time has an impact on the device efficiency, possibly due to structural changes caused by ion migration and accumulation.
JOURNAL OF OPTOELECTRONICS AND ADVANCED MATERIALS
(2023)
Article
Materials Science, Multidisciplinary
Rui-xiang Chen, Xue-qiong Su, Jin Wang, Dong-wen Gao, Yong Pan, Yi-meng Wang, Li Wang
Summary: This study explains the mechanism behind the double peaks phenomenon in perovskite photoluminescence, identifies the specific structures and defects causing the two peaks, and provides theoretical references for experimental research on new perovskite materials.
Article
Multidisciplinary Sciences
Saradh Prasad, Mamduh J. Aljaafreh, Abeer Alshammari, Mona A. S. Almutairi, Jagannathan Madhavan, Mohamad S. AlSalhi
Summary: This study investigates the performance characteristics of a series of solar cells with different structures and material combinations. The results demonstrate that a conjugated polymer can serve as a hole transport layer, reducing the reliance on separate materials and improving device stability. Additionally, optimizing the thickness of the TiO2 mesoporous layer can enhance the permeability of the perovskite and further improve the conversion efficiency of the solar cell.
JOURNAL OF KING SAUD UNIVERSITY SCIENCE
(2022)
Article
Chemistry, Physical
Parameswaran Rajamanickam, Yi-Sheng Ou, Lun-Xin Chang, Chung-Kai Chang, Yu-Chun Chuang, Che-Min Chou, Cheng-Si Tsao, Cheng-Yu Wang
Summary: MOF or ZIF-derived carbon (MDC/ZDC) plays an important role in catalysis applications. Well-dispersed metal or oxide nanoparticles can be obtained with direct pyrolysis while retaining the porosity of MOF/ZIF. It has been found that pyrolysis parameters significantly affect the properties of MDC/ZDC. Manipulating the pyrolysis conditions can trigger interdiffusion and alloying behavior of metal ions, resulting in the formation of unstable intermetallic compounds.
JOURNAL OF ALLOYS AND COMPOUNDS
(2023)
Article
Chemistry, Multidisciplinary
Wei Qian, Weitao Qiu, Shanshan Yu, Duan Huang, Renbo Lei, Xianzhen Huang, Shuang Xiao, Xinwei Wang, Shihe Yang
Summary: The emergence of organic-inorganic hybrid perovskites has enabled the use of aerosol-liquid-solid technology for direct X-ray detectors. However, the film quality from this process is often compromised when deposited in ambient conditions with uncontrolled humidity. In this study, a solvent engineering strategy is developed to obtain high-quality perovskite thick films, minimizing the negative effect of the ambient conditions and improving the overall performance of the X-ray detectors.
Article
Radiology, Nuclear Medicine & Medical Imaging
Shuyi Yang, Yida Wang, Yuxin Shi, Guang Yang, Qinqin Yan, Jie Shen, Qingle Wang, Haoling Zhang, Shan Yang, Fei Shan, Zhiyong Zhang
Summary: A radiomics nomogram was developed based on manual segmentation of different pulmonary nodules and measurement of signal intensity, nodule size, and other parameters, successfully distinguishing between malignant and benign nodules. The nomogram performed better in both the training and test sets compared to T2-based quantitative parameters.
MAGNETIC RESONANCE IMAGING
(2022)
Article
Reproductive Biology
Tianping Wang, Haijie Wang, Yida Wang, Xuefen Liu, Lei Ling, Guofu Zhang, Guang Yang, He Zhang
Summary: This study aimed to construct and compare radiomics-clinical nomograms based on MR images for prognosis prediction in EOC. The T2WI radiomic-clinical nomogram showed a favorable prediction performance in EOC patients.
JOURNAL OF OVARIAN RESEARCH
(2022)
Article
Neurosciences
Weiwei Zhao, Yida Wang, Fangfang Zhou, Gaiying Li, Zhichao Wang, Haodong Zhong, Yang Song, Kelly M. Gillen, Yi Wang, Guang Yang, Jianqi Li
Summary: This study successfully segmented midbrain nuclei in high-resolution susceptibility maps using a convolutional neural network-based method. The automated segmentation results showed no significant differences compared to manual delineations, and the volume and magnetic susceptibility values extracted by the automated method were significantly correlated with manual tracing results.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Qiong Li, Qiu-Xia Feng, Liang Qi, Chang Liu, Jing Zhang, Guang Yang, Yu-Dong Zhang, Xi-Sheng Liu
Summary: The study demonstrates the potential of radiomics and deep transfer learning features on CECT images for predicting LVI in GC patients, which could help predict survival outcomes. The GRISK model shows promising diagnostic performance in individualized treatment decision-making.
ABDOMINAL RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jinbo Qi, Peipei Wang, Guohua Zhao, Eryuan Gao, Kai Zhao, Ankang Gao, Jie Bai, Huiting Zhang, Guang Yang, Yong Zhang, Xiaoyue Ma, Jingliang Cheng
Summary: This study explored the value of histogram analysis based on NODDI in differentiating between GBM and SBM, and compared the diagnostic performance of two ROI placements. The results showed that the multivariate logistic regression model based on NODDI histogram analysis had better performance than the optimal single parameter in distinguishing GBM from SBM, and the ROI placed on the whole tumor area exhibited better diagnostic performance.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Ke-Wen Jiang, Yang Song, Ying Hou, Rui Zhi, Jing Zhang, Mei-Ling Bao, Hai Li, Xu Yan, Wei Xi, Cheng-Xiu Zhang, Ye-Feng Yao, Guang Yang, Yu-Dong Zhang
Summary: A study developed and tested an artificial intelligence (AI) system for diagnosing clinically significant prostate cancer (CsPC) using MRI. The AI system performed comparably or better than radiologists in both internal and external tests. Factors such as Gleason score, lesion location, PI-RADS score, and lesion size significantly impacted the accuracy of the AI system.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Article
Oncology
Ruiqi Yu, Ke-wen Jiang, Jie Bao, Ying Hou, Yinqiao Yi, Dongmei Wu, Yang Song, Chun-Hong Hu, Guang Yang, Yu-Dong Zhang
Summary: In this study, an artificial intelligence (AI)-aided Prostate Imaging Reporting and Data System (PI-RADS(AI)) was developed and validated for prostate cancer (PCa) diagnosis based on MRI. UNet-Seg and 3D-Resnet models were used to detect and segment prostate lesions, achieving an automatic AI-aided diagnosis for PCa. The results showed that PI-RADS(AI) outperformed or matched the performance of over 70% of general readers in the MRI assessment of PCa, providing diagnostic benefits to clinical practice.
BRITISH JOURNAL OF CANCER
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jia-Xiang Xin, Da-Xiu Wei, Yan Ren, Jun-Long Wang, Guang Yang, Huojun Zhang, Jianqi Li, Caixia Fu, Ye-Feng Yao
Summary: Selective probing of glutamate (Glu) and glutamine (Gln) signals in human brain in vivo is important for studying their metabolisms. Glu-/Gln- targeted pulse sequences were developed to selectively probe Glu and Gln signals. These sequences successfully separated Glu and Gln signals in healthy human brains, providing an effective method for distinguishing H-1-MR signals of Glu and Gln.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Multidisciplinary Sciences
Long Cui, Yang Song, Yida Wang, Rui Wang, Dongmei Wu, Haibin Xie, Jianqi Li, Guang Yang
Summary: This study proposes a new method to detect and remove motion artifacts in magnetic resonance images. A convolutional neural network (CNN) model is trained to filter motion-corrupted images, and the unaffected phase-encoding (PE) lines are used to reconstruct the final image using compressed sensing (CS). The results show that the proposed algorithm effectively alleviates motion artifacts.
Article
Oncology
Ziyu Le, Dongmei Wu, Xuming Chen, Lei Wang, Yi Xu, Guoqi Zhao, Chengxiu Zhang, Ying Chen, Ye Hu, Shengyu Yao, Tingfeng Chen, Jiangping Ren, Guang Yang, Yong Liu
Summary: The study aims to establish a predictive model for acute severe hematologic toxicity (HT) during radiotherapy in patients with cervical or endometrial cancer. It investigates the integration of clinical features and computed tomography (CT) radiomics features of the pelvic bone marrow (BM) to define a more precise model. The model combines clinical and radiomics features and achieves a higher area under the receiver operating characteristic curve (AUC) compared to models based on clinical or radiomics features alone. Further investigation is warranted to explore the value of pelvic BM radiomics in chemoradiotherapy-induced HT.
RADIOTHERAPY AND ONCOLOGY
(2023)
Article
Neurosciences
Yida Wang, Naying He, Chunyan Zhang, Youmin Zhang, Chenglong Wang, Pei Huang, Zhijia Jin, Yan Li, Zenghui Cheng, Yu Liu, Xinhui Wang, Chen Chen, Jingliang Cheng, Fangtao Liu, Ewart Mark Haacke, Shengdi Chen, Guang Yang, Fuhua Yan
Summary: A DL-based pipeline for automatic PD diagnosis is proposed, which uses QSM and T1W images to segment deep gray matter nuclei and distinguish PD from HC. The model achieved high accuracy in segmenting brain nuclei and showed promising performance in PD diagnosis with high AUC values on both internal and external testing cohorts.
HUMAN BRAIN MAPPING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Haijie Wang, Yida Wang, He Zhang, Xuan Yin, Chenglong Wang, Yuanyuan Lu, Yang Song, Hao Zhu, Guang Yang
Summary: The purpose of this study was to develop a deep learning tool for antenatal diagnosis of prenatal placenta accreta spectrum (PAS) using T2-weighted MR images. By extracting the utero-placental boundary region image, the DL model achieved an AUC of 0.860 and 0.897 in the internal test and external test cohorts, respectively, significantly outperforming three radiologists (internal test AUC, 0.737-0.770). This fully automatic DL pipeline can improve the accuracy of PAS diagnosis using MRI for radiologists.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jing Zhang, Chenao Zhan, Chenxiu Zhang, Yang Song, Xu Yan, Yihao Guo, Tao Ai, Guang Yang
Summary: The purpose of this study was to develop an automatic computer-aided diagnosis (CAD) pipeline based on multiparametric magnetic resonance imaging (mpMRI) and investigate the role of different imaging features in the classification of breast cancer. The study included 222 histopathology-confirmed breast lesions and trained a neural network-based lesion segmentation model to extract radiomics features from DWI, T2WI, and DCE parametric maps. Models based on sequence combinations achieved higher diagnostic accuracy compared to BI-RADS scores, and the joint model combining radiomics and BI-RADS scores achieved the highest accuracy.
Article
Chemistry, Inorganic & Nuclear
Mingxi Jiang, Yajuan Zhang, Zihao Yang, Haibo Li, Jinliang Li, Jiabao Li, Ting Lu, Chenglong Wang, Guang Yang, Likun Pan
Summary: Metal ion doping is an effective method to improve the electrochemical performance of metal oxide anode materials for lithium-ion batteries. Machine learning models were built to predict the charging and discharging performance of doped oxide anode materials before synthesis, saving time and resources. The study found a correlation between the electronegativity of the dopant element and the capacity performance of the material.
INORGANIC CHEMISTRY FRONTIERS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Ruiqi Yu, Wei Liu, Yang Song, Jing Zhang, Xiao-hang Liu, Liangping Zhou, Guang Yang
Summary: Radiomics models can be used to differentiate low and high ISUP grades of CCRCC by analyzing CT image features. The model using NCP and CMP features achieved the highest performance on the independent testing cohort.
CHINESE JOURNAL OF ACADEMIC RADIOLOGY
(2022)