scholarly journals Photovoltaic lithium-ion battery fabricated by molecular precursor method

2016 ◽  
Vol 09 (03) ◽  
pp. 1650046 ◽  
Author(s):  
Hiroki Nagai ◽  
Tatsuya Suzuki ◽  
Yoshihisa Takahashi ◽  
Mitsunobu Sato

A novel thin-film lithium-ion battery (LIB) which can be charged by the light irradiation was fabricated by molecular precursor method. The unprecedented, translucent thin-film LIB, fabricated on a fluorine-doped tin oxide pre-coated glass substrate, was attained by using the active materials, titania for anode and LiCoO2 for cathode, respectively. The averaged potential at 2.04[Formula: see text]V was observed by applying a constant current of 0.2[Formula: see text]mA. Then, that at 1.82[Formula: see text]V was detected after 60[Formula: see text]s during the sequential self-discharge process. The charging voltage of the assembled battery was 1.38[Formula: see text]V with irradiation of 1-sun, the self-discharge voltage was 1.37[Formula: see text]V. Based on the calibration curve of the charging voltages over constant currents ranging from 0–1.0[Formula: see text]mA, the detected value can be theoretically reduced to the charging operation by applying a constant current of approximately 60[Formula: see text][Formula: see text]A. The charge and discharge of this device was stable voltage at least 30 cycles. The two-in-one device can simultaneously generate and store electricity from solar light, the renewable energy source, and may be applied in smart windows for distributed power system according to on-site demand.

2011 ◽  
Vol 196 (3) ◽  
pp. 1474-1477 ◽  
Author(s):  
Juchuan Li ◽  
Fuqian Yang ◽  
Jia Ye ◽  
Yang-Tse Cheng

Nanoscale ◽  
2014 ◽  
Vol 6 (17) ◽  
pp. 10243-10254 ◽  
Author(s):  
Uttam Kumar Sen ◽  
Priya Johari ◽  
Sohini Basu ◽  
Chandrani Nayak ◽  
Sagar Mitra

Experimental evidence and theoretical correlation of the formation of elemental sulphur during the discharge process of MoS2, a high rate lithium ion battery anode.


2015 ◽  
Vol 178 ◽  
pp. 476-483 ◽  
Author(s):  
Jianjiang He ◽  
Chuanjian Zhang ◽  
Huiping Du ◽  
Shengliang Zhang ◽  
Pu Hu ◽  
...  

2014 ◽  
Vol 246 ◽  
pp. 149-159 ◽  
Author(s):  
Siladitya Pal ◽  
Sameer S. Damle ◽  
Siddharth H. Patel ◽  
Moni K. Datta ◽  
Prashant N. Kumta ◽  
...  

2021 ◽  
Vol 12 (4) ◽  
pp. 228
Author(s):  
Jianfeng Jiang ◽  
Shaishai Zhao ◽  
Chaolong Zhang

The state-of-health (SOH) estimation is of extreme importance for the performance maximization and upgrading of lithium-ion battery. This paper is concerned with neural-network-enabled battery SOH indication and estimation. The insight that motivates this work is that the chi-square of battery voltages of each constant current-constant voltage phrase and mean temperature could reflect the battery capacity loss effectively. An ensemble algorithm composed of extreme learning machine (ELM) and long short-term memory (LSTM) neural network is utilized to capture the underlying correspondence between the SOH, mean temperature and chi-square of battery voltages. NASA battery data and battery pack data are used to demonstrate the estimation procedures and performance of the proposed approach. The results show that the proposed approach can estimate the battery SOH accurately. Meanwhile, comparative experiments are designed to compare the proposed approach with the separate used method, and the proposed approach shows better estimation performance in the comparisons.


2020 ◽  
Vol 118 ◽  
pp. 106790
Author(s):  
Hisao Kiuchi ◽  
Kazuhiro Hikima ◽  
Keisuke Shimizu ◽  
Ryoji Kanno ◽  
Fukunaga Toshiharu ◽  
...  

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