| 1. |
- Sun, Huiliang, et al.
(författare)
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A monothiophene unit incorporating both fluoro and ester substitution enabling high-performance donor polymers for non-fullerene solar cells with 16.4% efficiency
- 2019
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Ingår i: Energy & Environmental Science. - : ROYAL SOC CHEMISTRY. - 1754-5692 .- 1754-5706. ; 12:11, s. 3328-3337
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Tidskriftsartikel (refereegranskat)abstract
- Thiophene and its derivatives have been extensively used in organic electronics, particularly in the field of polymer solar cells (PSCs). Significant research efforts have been dedicated to modifying thiophene-based units by attaching electron-donating or withdrawing groups to tune the energy levels of conjugated materials. Herein, we report the design and synthesis of a novel thiophene derivative, FE-T, featuring a monothiophene functionalized with both an electron-withdrawing fluorine atom (F) and an ester group (E). The FE-T unit possesses distinctive advantages of both F and E groups, the synergistic effects of which enable significant downshifting of the energy levels and enhanced aggregation/crystallinity of the resulting organic materials. Shown in this work are a series of polymers obtained by incorporating the FE-T unit into a PM6 polymer to fine-tune the energetics and morphology of this high-performance PSC material. The optimal polymer in the series shows a downshifted HOMO and an improved morphology, leading to a high PCE of 16.4% with a small energy loss (0.53 eV) enabled by the reduced non-radiative energy loss (0.23 eV), which are among the best values reported for non-fullerene PSCs to date. This work shows that the FE-T unit is a promising building block to construct donor polymers for high-performance organic photovoltaic cells.
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| 2. |
- Tang, Xiaopeng, et al.
(författare)
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A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging
- 2019
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Ingår i: Energy Conversion and Management. - : Elsevier BV. - 0196-8904. ; 180, s. 162-170
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Tidskriftsartikel (refereegranskat)abstract
- Temperature and cell aging are two major factors that influence the reliability and safety of Li-ion batteries. A general battery model considering both temperature and degradation is often difficult to develop, given the fact that there are many different types of cells with different shapes and/or internal chemical components. In response, a migration-based framework is proposed in this paper for battery modeling, in which the effects of temperature and aging are treated as uncertainties. An accurate model for a fresh cell is established first and then migrated to the degraded batteries through a Bayes Monte Carlo method. Experiments are carried out on both LiFePO4 batteries and Li(Ni1/3Co1/3Mn1/3) O2 batteries under various ambient temperatures and aging levels. The results indicate that the typical voltage prediction error can be limited within ±20 mV, for the cases of temperature change up to 40 °C, and capacity degradation up to 20%. The proposed method paves ways to an effective battery management and energy control for electric vehicles or micro grid applications.
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