Indoor photovoltaics (IPVs) are expected to power the Internet of Things ecosystem, which is attracting ever-increasing attention as part of the rapidly developing distributed communications and electronics technology. The power conversion efficiency of IPVs strongly depends on the match between typical indoor light spectra and the band gap of the light absorbing layer. Therefore, band-gap tunable materials, such as metal-halide perovskites, are specifically promising candidates for approaching the indoor illumination efficiency limit of ∼56%. However, perovskite materials with ideal band gap for indoor application generally contain high bromine (Br) contents, causing inferior open-circuit voltage (V ). By fabricating a series of wide-bandgap perovskites (Cs FA PbI Br , 0.6 ≤ x ≤ 1.6) with varying Br contents and related band gaps, it is found that, the high Br vacancy (V ) defect density is a significant reason that leading to large V deficits apart from the well-accepted halide segregation. The introduction of I-rich alkali metal small-molecule compounds is demonstrated to suppress the V and increase the V of perovskite IPVs up to 1.05 V under 1000 lux light-emitting diode illumination, one of the highest V values reported so far. More importantly, the modules are sent for independent certification and have gained a record efficiency of 36.36%.
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http://dx.doi.org/10.1002/advs.202204138 | DOI Listing |
Science
January 2025
Beijing Key Laboratory for Theory and Technology of Advanced Battery Materials, Key Laboratory of Polymer Chemistry and Physics of Ministry of Education, School of Materials Science and Engineering, Peking University, Beijing, China.
One of the primary challenges in commercializing perovskite solar cells (PSCs) is achieving both high power conversion efficiency (PCE) and sufficient stability. We integrate wafer-scale continuous monolayer MoS buffers at the top and bottom of a perovskite layer through a transfer process. These films physically block ion migration of perovskite into carrier transport layers and chemically stabilize the formamidinium lead iodide phase through strong coordination interaction.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Southern University of Science and Technology, Department of Materials Science and Engineering, NO.1088,Xueyuan Avenue,Nanshan District, 518055, Shenzhen, CHINA.
Tin dioxide (SnO2) stands as a promising material for the electron transport layer (ETL) in perovskite solar cells (PSCs) attributed to its superlative optoelectronic properties. The attainment of superior power conversion efficiency hinges critically on the preparation of high-quality SnO2 thin films. However, conventional nanoparticle SnO2 colloids often suffer from inherent issues such as numerous oxygen vacancy defects and film non-uniformity.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA.
Background: Amyloid-β (Aβ) plaques and tau pathogenesis in the brain precede cognitive decline in the progression of Alzheimer's dementia, yet the extent to which these measures can predict localized brain tissue atrophy has not been studied in a large, diverse population. Multisite studies offer robust statistical power with larger sample sizes but are confounded by variations in biomarker quantification across studies, including variations in MRI scanners, PET tracers, and CSF assays. Longitudinal data from N=1223 individuals from four independent AD studies were harmonized to assess localized brain tissue atrophy over 2 to 5 years.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
Background: Memory clinic patients are a heterogeneous population representing various aetiologies of pathological aging. It is unknown if divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease (AD) patients, are prevalent and clinically meaningful in this group of older adults.
Method: To uncover atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to structural MRI data from 813 participants (mean ± SD age = 70.
Alzheimers Dement
December 2024
Washington University School of Medicine, Saint Louis, MO, USA.
Background: While several non-invasive plasma biomarkers are rapidly developing, they still have lower accuracy than the established CSF biomarkers. This study therefore comprehensively examined 6,905 plasma proteins in over 3,000 individuals to identify novel biomarkers for predicting clinical Alzheimer's disease (AD) and monitoring disease progression.
Method: To identify and validate plasma biomarkers, we performed difference abundance analysis of 6,905 plasma proteins in a total of 3,366 cases and controls from three different datasets (Knight-ADRC discovery, Knight-ADRC replication and Stanford ADRC).
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