Particle Size Effects of TiO2 Layers on the Solar Efficiency of Dye-Sensitized Solar Cells

Large particle sizes having a strong light scattering lead to a significantly decreased surface area and small particle sizes having large surface area lack light-scattering effect. How to combine large and small particle sizes together is an interesting work for achieving higher solar efficiency. In this work, we investigate the solar performance influence of the dye-sensitized solar cells (DSSCs) by the multiple titanium oxide (TiO2) layers with different particle sizes. It was found that the optimal TiO2 thickness depends on the particle sizes of TiO2 layers for achieving the maximum efficiency. The solar efficiency of DSSCs prepared by triple TiO2 layers with different particle sizes is higher than that by double TiO2 layers for the same TiO2 thickness. The choice of particle size in the bottom layer is more important than that in the top layer for achieving higher solar efficiency. The choice of the particle sizes in the middle layer depends on the particle sizes in the bottom and top layers. The mixing of the particle sizes in the middle layer is a good choice for achieving higher solar efficiency

Particle Size Effects of TiO 2

Large particle sizes having a strong light scattering lead to a significantly decreased surface area and small particle sizes having large surface area lack light-scattering effect. How to combine large and small particle sizes together is an interesting work for achieving higher solar efficiency. In this work, we investigate the solar performance influence of the dye-sensitized solar cells (DSSCs) by the multiple titanium oxide (TiO2) layers with different particle sizes. It was found that the optimal TiO2 thickness depends on the particle sizes of TiO2 layers for achieving the maximum efficiency. The solar efficiency of DSSCs prepared by triple TiO2 layers with different particle sizes is higher than that by double TiO2 layers for the same TiO2 thickness. The choice of particle size in the bottom layer is more important than that in the top layer for achieving higher solar efficiency. The choice of the particle sizes in the middle layer depends on the particle sizes in the bottom and top layers. The mixing of the particle sizes in the middle layer is a good choice for achieving higher solar efficiency

Assessment of density functional approximations for the hemibonded structure of water dimer radical cation

Due to the severe self-interaction errors associated with some density functional approximations, conventional density functionals often fail to dissociate the hemibonded structure of water dimer radical cation (H2O)2+ into the correct fragments: H2O and H2O+. Consequently, the binding energy of the hemibonded structure (H2O)2+ is not well-defined. For a comprehensive comparison of different functionals for this system, we propose three criteria: (i) The binding energies, (ii) the relative energies between the conformers of the water dimer radical cation, and (iii) the dissociation curves predicted by different functionals. The long-range corrected (LC) double-hybrid functional, omegaB97X-2(LP) [J.-D. Chai and M. Head-Gordon, J. Chem. Phys., 2009, 131, 174105.], is shown to perform reasonably well based on these three criteria. Reasons that LC hybrid functionals generally work better than conventional density functionals for hemibonded systems are also explained in this work.Comment: 10 pages, 5 figures, 4 table

Replication and Meta-Analysis of GWAS Identified Susceptibility Loci in Kawasaki Disease Confirm the Importance of B Lymphoid Tyrosine Kinase (BLK) in Disease Susceptibility

10.1371/journal.pone.0072037PLoS ONE88-POLN

Identification of Novel Susceptibility Loci for Kawasaki Disease in a Han Chinese Population by a Genome-Wide Association Study

Kawasaki disease (KD) is an acute systemic vasculitis syndrome that primarily affects infants and young children. Its etiology is unknown; however, epidemiological findings suggest that genetic predisposition underlies disease susceptibility. Taiwan has the third-highest incidence of KD in the world, after Japan and Korea. To investigate novel mechanisms that might predispose individuals to KD, we conducted a genome-wide association study (GWAS) in 250 KD patients and 446 controls in a Han Chinese population residing in Taiwan, and further validated our findings in an independent Han Chinese cohort of 208 cases and 366 controls. The most strongly associated single-nucleotide polymorphisms (SNPs) detected in the joint analysis corresponded to three novel loci. Among these KD-associated SNPs three were close to the COPB2 (coatomer protein complex beta-2 subunit) gene: rs1873668 (p = 9.52×10−5), rs4243399 (p = 9.93×10−5), and rs16849083 (p = 9.93×10−5). We also identified a SNP in the intronic region of the ERAP1 (endoplasmic reticulum amino peptidase 1) gene (rs149481, pbest = 4.61×10−5). Six SNPs (rs17113284, rs8005468, rs10129255, rs2007467, rs10150241, and rs12590667) clustered in an area containing immunoglobulin heavy chain variable regions genes, with pbest-values between 2.08×10−5 and 8.93×10−6, were also identified. This is the first KD GWAS performed in a Han Chinese population. The novel KD candidates we identified have been implicated in T cell receptor signaling, regulation of proinflammatory cytokines, as well as antibody-mediated immune responses. These findings may lead to a better understanding of the underlying molecular pathogenesis of KD

Clinical Efficacy and Post-Treatment Seromarkers Associated with the Risk of Hepatocellular Carcinoma among Chronic Hepatitis C Patients

This follow-up study enrolled chronic hepatitis C patients to evaluate the treatment efficacy and to identify post-treatment seromarkers associated with risk of hepatocellular carcinoma (HCC) among patients with a sustained virological response (SVR) or nonsustained virological response (NSVR). A total of 4639 patients who received pegylated interferon and ribavirin during 2004–2013 were followed until December 2014. HCC was confirmed through health examinations and data linkage with a national database. A total of 233 HCC cases were reported after 26,163 person-years of follow-up, indicating an incidence of 8.9 per 1000 person-years: 6.9 for SVR and 21.6 for NSVR per 1000 person-years. The associated risk of HCC in patients with SVR was 0.37 (0.22–0.63) for those without cirrhosis and 0.54 (0.31–0.92) for those with cirrhosis compared with their respective counterparts with NSVR. Among patients with SVR, advanced age, male gender, cirrhosis, decreased platelet count, and increased aspartate aminotransferase and α-fetoprotein levels were associated with HCC (p < 0.001). The treatment of chronic hepatitis C patients before they developed cirrhosis showed a higher efficacy than did the treatment of those who had already developed cirrhosis. Patients with SVR may still have a risk of HCC and need to be regularly monitored

Simulation of Nonpolar p-GaN/i-N/n-GaN Solar Cells

It is well known that nitride-based devices suffer the polarization effects. A promising way to overcome the polarization effects is growth in a direction perpendicular to the c-axis (nonpolar direction). Nonpolar devices do not suffer polarization charge, and then they have a chance to achieve the high solar efficiency. The understanding of the solar performance of non-polar InGaN-based solar cells will be interesting. For a pin non-polar solar cell with GaN p- and n-cladding layers, the conduction band offset (or barrier height, ) between an intrinsic layer and n-GaN layer is an important issue correlating to the efficiency and fill factor. The efficiency and fill factor will be seriously degraded due to sufficiently high barrier height. To reduce a high barrier height, some graded layers with an energy bandgap between the energy bandgap of n-GaN and InxGa1−xN intrinsic layer can be inserted to the interface of n-GaN and InxGa1-xN layers. From simulation, it indicates that the insertion of graded layer is an effective method to lower energy barrier when there exists a high energy band offset in non-polar nitride devices

A Surface Acoustic Wave Sensor with a Microfluidic Channel for Detecting C-Reactive Protein

A surface acoustic wave (SAW) sensor with a microfluidic channel was studied to detect C-reactive protein (CRP). A piezoelectric lithium niobate substrate was used to examine the frequency response of the microfluidic SAW sensor. The amplitude (insertion loss) changes in the microfluidic SAW sensor were measured from the interaction of CRP/anti-CRP owing to mass variation. The fabricated microfluidic SAW sensor exhibited a detection limit of 4 ng/mL CRP concentration. A wide CRP concentration range (10 ng/mL to 0.1 mg/mL) can be detected by this sensor, which is higher than the existing CRP detection methods. A good linear relationship between the amplitude peak shift and CRP concentrations from 10 ng/mL to 0.1 mg/mL was obtained. The amplitude peak shifts in the sensor can be useful for estimating CRP concentration. This can be used as a biosensor to diagnose the risk of cardiovascular disease

Raman Spectroscopy Analysis for Optical Diagnosis of Oral Cancer Detection

Raman spectroscopy (RS) is widely used as a non-invasive technique in screening for the diagnosis of oral cancer. The potential of this optical technique for several biomedical applications has been proved. This work studies the efficacy of RS in detecting oral cancer using sub-site-wise differentiation. A total of 80 samples (44 tumor and 36 normal) were cryopreserved from three different sub-sites: The tongue, the buccal mucosa, and the gingiva of the oral mucosa during surgery. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to classify the samples and the classifications were validated by leave-one-out-cross-validation (LOOCV) and k-fold cross-validation methods. The normal and tumor tissues were differentiated under the PCA-LDA model with an accuracy of 81.25% (sensitivity: 77.27%, specificity: 86.11%). The PCA-QDA classifier model differentiated these tissues with an accuracy of 87.5% (sensitivity: 90.90%, specificity: 83.33%). The PCA-QDA classifier model outperformed the PCA-LDA-based classifier. The model studies revealed that protein, amino acid, and beta-carotene variations are the main biomolecular difference markers for detecting oral cancer