The study on graphene oxide (GO) grows rapidly in recent years. We find that graphene oxide could act as the passivation material in photovoltaic applications. Graphene oxide has been applied on Si two-different-metal solar cells. The suitable introduction of graphene oxide could result in obvious enhancement on the efficiency. The simple chemical process to deposit graphene oxide makes low thermal budget, large-area deposition, and fast production of surface passivation possible. The different procedures to incorporate graphene oxide in Si two-different-metal solar cells are compared, and 21% enhancement on the efficiency is possible with a suitable deposition method.

For photovoltaic applications, microcrystalline silicon has a lot of advantages, such as the ability to absorb the near-infrared part of the solar spectrum. However, there are many dangling bonds at the grain boundary in microcrystalline Si. These dangling bonds would lead to the recombination of photo-generated carriers and decrease the conversion efficiency. Therefore, we included the grain boundary in the numerical study in order to simulate a microcrystalline Si solar cell accurately, designing new three-terminal microcrystalline Si solar cells. The 3-μm-thick three-terminal cell achieved a conversion efficiency of 10.8%, while the efficiency of a typical two-terminal cell is 9.7%. The three-terminal structure increased the JSC but decreased the VOC, and such phenomena are discussed. High-efficiency and low-cost Si-based thin film solar cells can now be designed based on the information provided in this paper.

Background: The earlier detection of dementia is needed as cases increase yearly in the aging populations of Taiwan and the world. In recent years, the global internet usage rate has gradually increased among older people. To expand dementia screening and provide timely medical intervention, a simple self-administrated assessment tool to assist in easily screening for dementia is needed. Objective: The two-part goal of this pilot study was, first, to develop a Game-Based Cognitive Assessment (GBCA) tool, and then, to evaluate its validity at early screening for patients with cognitive impairment. Method: The researchers recruited 67 patients with neurocognitive disorders (NCDs) and 57 healthy controls (HCs). Each participant underwent the GBCA and other clinical cognitive assessments (CDR, CASI, and MMSE), and filled out a questionnaire evaluating their experience of using the GBCA. Statistical analyses were used to measure the validity of the GBCA at screening for degenerative dementia. Results: The average GBCA scores of the HC and NCD groups were 87 (SD = 7.9) and 52 (SD = 21.7), respectively. The GBCA correlated well with the CASI (r 2 = 0.90, p <  0.001) and with the MMSE (r2 = 0.92, p <  0.001), indicating concurrent validity. The GBCA cut-off of 75/76 corresponded to measurements of sensitivity, specificity, and area under curve of 85.1%, 91.5%, and 0.978, respectively. The positive predictive value was 91.9%, and the negative predictive value was 84.4%. The results of the user-experience questionnaire for the HC and NCD groups were good and acceptable, respectively. Conclusion: The GBCA is an effective and acceptable tool for screening for degenerative dementia.