| 1. |
- Cai, Xia, et al.
(författare)
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Data-driven design of high-performance MASn(x)Pb(1-x)I(3) perovskite materials by machine learning and experimental realization
- 2022
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Ingår i: Light. - : Springer Nature. - 2095-5545 .- 2047-7538. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- The photovoltaic performance of perovskite solar cell is determined by multiple interrelated factors, such as perovskite compositions, electronic properties of each transport layer and fabrication parameters, which makes it rather challenging for optimization of device performances and discovery of underlying mechanisms. Here, we propose and realize a novel machine learning approach based on forward-reverse framework to establish the relationship between key parameters and photovoltaic performance in high-profile MASn(x)Pb(1-x)I(3) perovskite materials. The proposed method establishes the asymmetrically bowing relationship between band gap and Sn composition, which is precisely verified by our experiments. Based on the analysis of structural evolution and SHAP library, the rapid-change region and low-bandgap plateau region for small and large Sn composition are explained, respectively. By establishing the models for photovoltaic parameters of working photovoltaic devices, the deviation of short-circuit current and opencircuit voltage with band gap in defective-zone and low-bandgap-plateau regions from Shockley-Queisser theory is captured by our models, and the former is due to the deep-level traps formed by crystallographic distortion and the latter is due to the enhanced susceptibility by increased Sn (4+ )content. The more difficulty for hole extraction than electron is also concluded in the models and the prediction curve of power conversion efficiency is in a good agreement with Shockley-Queisser limit. With the help of search and optimization algorithms, an optimized Sn:Pb composition ratio near 0.6 is finally obtained for high-performance perovskite solar cells, then verified by our experiments. Our constructive method could also be applicable to other material optimization and efficient device development.
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| 2. |
- Leipold, Sina, et al.
(författare)
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Lessons, narratives, and research directions for a sustainable circular economy
- 2023
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Ingår i: Journal of Industrial Ecology. - : Wiley. - 1088-1980 .- 1530-9290. ; 27:1, s. 6-18
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Tidskriftsartikel (refereegranskat)abstract
- The current enthusiasm for the circular economy (CE) offers a unique opportunity to advance the impact of research on sustainability transitions. Diverse interpretations of CE by scholars, however, produce partly opposing assessments of its potential benefits, which can hinder progress. Here, we synthesize policy-relevant lessons and research directions for a sustainable CE and identify three narratives—optimist, reformist, and skeptical—that underpin the ambiguity in CE assessments. Based on 54 key CE scholars’ insights, we identify three research needs: the articulation and discussion of ontologically distinct CE narratives; bridging of technical, managerial, socio-economic, environmental, and political CE perspectives; and critical assessment of opportunities and limits of CE science–policy interactions. Our findings offer practical guidance for scholars to engage reflexively with the rapid expansion of CE knowledge, identify and pursue high-impact research directions, and communicate more effectively with practitioners and policymakers.
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