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Search: (WFRF:(Wei Xiaofeng)) srt2:(2015-2019) > (2016)

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  • Wang, Chuanfei, et al. (author)
  • Low Band Gap Polymer Solar Cells With Minimal Voltage Losses
  • 2016
  • In: Advanced Energy Materials. - : Wiley. - 1614-6832 .- 1614-6840. ; 6:18
  • Journal article (peer-reviewed)abstract
    • One of the factors limiting the performance of organic solar cells (OSCs) is their large energy losses (E loss) in the conversion from photons to electrons, typically believed to be around 0.6 eV and often higher than those of inorganic solar cells. In this work, a novel low band gap polymer PIDTT-TID with a optical gap of 1.49 eV is synthesized and used as the donor combined with PC71BM in solar cells. These solar cells attain a good power conversion efficiency of 6.7% with a high open-circuit voltage of 1.0 V, leading to the E loss as low as 0.49 eV. A systematic study indicates that the driving force in this donor and acceptor system is sufficient for charge generation with the low E loss. This work pushes the minimal E loss of OSCs down to 0.49 eV, approaching the values of some inorganic and hybrid solar cells. It indicates the potential for further enhancement of the performance of OSCs by improving their V oc since the E loss can be minimized.
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  • Luo, Yiqi, et al. (author)
  • Toward more realistic projections of soil carbon dynamics by Earth system models
  • 2016
  • In: Global Biogeochemical Cycles. - 0886-6236. ; 30:1, s. 40-56
  • Journal article (peer-reviewed)abstract
    • Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.
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