Conductive Copper Paste for Crystalline Silicon Solar Cells

In photovoltaic industries, the main technique of metallization is screen printing with silver pastes due to its simple and quick process. However, the expensive price of silver paste is one of the barriers to the production of low-cost solar cells. Therefore, the most focused target in photovoltaic research is the decreasing consumption of silver paste or substitute silver for other materials. As a proper candidate, copper has been researched by many institutes and companies since it has a similar conductivity with silver even though the price is inexpensive. To apply copper as a contact for solar cells, the plating technique has been actively researched. However, copper paste, which was mainly developed for integrated circuit applications, has been recently researched. Mostly, copper paste was developed for the low-temperature annealing process since copper tends to oxidize easily. On the other hand, firing type copper paste was also developed by coating copper particles with a barrier layer. This chapter discusses recent development of copper paste for the application of solar cells and its appropriate annealing conditions for better electrical properties. Also, the light I-V characteristics of copper paste on the solar cells in other research papers are summarized as well

Simultaneous fine mapping of closely linked epistatic quantitative trait loci using combined linkage disequilibrium and linkage with a general pedigree

Causal mutations and their intra- and inter-locus interactions play a critical role in complex trait variation. It is often not easy to detect epistatic quantitative trait loci (QTL) due to complicated population structure requirements for detecting epistatic effects in linkage analysis studies and due to main effects often being hidden by interaction effects. Mapping their positions is even harder when they are closely linked. The data structure requirement may be overcome when information on linkage disequilibrium is used. We present an approach using a mixed linear model nested in an empirical Bayesian approach, which simultaneously takes into account additive, dominance and epistatic effects due to multiple QTL. The covariance structure used in the mixed linear model is based on combined linkage disequilibrium and linkage information. In a simulation study where there are complex epistatic interactions between QTL, it is possible to simultaneously map interacting QTL into a small region using the proposed approach. The estimated variance components are accurate and less biased with the proposed approach compared with traditional models

Alzheimer’s disease (AD) knowledge in Korean Americans: identifying knowledge gaps and misconceptions and examining predictors of AD knowledge

Objectives: This study examined Alzheimer’s disease (AD) knowledge and its predictors among Korean Americans (KAs). Design: Convenience sampling was used to recruit KAs in the Greater Washington metropolitan area. A total of 268 KAs participated in the study and completed a cross-sectional survey in 2014. Using the Alzheimer’s Disease Knowledge Scale (ADKS), overall and domain knowledge was assessed. Multiple regression analyses were conducted for overall and domain knowledge with predictors including exposure to AD, social engagement, sources and frequency of health-related information, stigmatic beliefs (pity, antipathy, and social distance), English proficiency, and education. Results: KAs reported a 59% accuracy in the overall AD knowledge. At the domain level, KAs were most knowledgeable about assessment and diagnosis and least knowledgeable about caregiving. Our regression analyses showed that having a college degree or higher is associated with a greater overall AD knowledge. Three domain models of life impact, risk factors, and caregiving turned out to be significant: Having a college degree or higher is a predictor of greater knowledge in all three domains. Having more pity stigmatic beliefs is related to greater knowledge in both life impact and caregiving domains while having less pity stigmatic beliefs is associated with more risk factor knowledge; having less social distance stigmatic beliefs is associated with greater life impact knowledge; and having less antipathy stigmatic beliefs is related to better caregiving knowledge. Conclusion: Our findings revealed areas of misconceptions and knowledge gaps in KAs which need to be addressed in educational interventions. Different knowledge status across the domains demonstrates a multi-dimensional nature of AD knowledge. Multivariate findings confirmed the robust role of education in overall and domain AD knowledge. The effect of different AD stigmatic beliefs on certain AD knowledge domains suggests ways of how stigma change can be efficient for the purpose of increasing AD domain knowledge in KAs