Abstract:Molecularly imprinted polymer brush layers and gel layers with both a lectin (ConA) and an antibody-IgG as biomolecular ligands for a target protein were formed on surface plasmon resonance (SPR) sensor chips via surface-initiated atom transfer radical polymerization (SI-ATRP) without and with a crosslinker, respectively. While the IgG-imprinted brush layers chip had almost the same affinity constant for target IgG as the nonimprinted brush layer chip, the affinity constant of the IgG-imprinted gel layer chip was approximately twice than that of the nonimprinted gel layer chip. These indicate that chemical crosslinks are very important factor to create distinct molecular recognition sites by molecular imprinting. Thus, biomolecular imprinting that uses biomolecular ligands and crosslinkers enables us to design polymer layer chips with distinct molecular recognition sites with a strong affinity for a target biomolecule. The molecularly imprinted gel layers chips with lectin and antibody ligands are promising candidates for fabricating SPR sensor systems to monitor target biomolecules such as proteins.
Carbon materials are widely used as anode on Li-ion battery (LIB). In particular, the effect of electrical conductivity (EC) on the anode is related to capacity and retention, which are important factors for LIB performance. However, the relationship between carbon properties and battery performance is still unclear. This uncertainty is due to the sp3 and sp2 bond states, the diversity of carbon like amorphous structures, and impurities.
In this study, we investigate the structure-EC relationship from over 50 carbon samples. The carbon used was graphite, carbon nanotube (CNT), carbon black (CB), hetero atom doped carbon, and the ones synthesized by solution plasma. The carbon materials are evaluated by X-ray diffraction (XRD), Raman spectroscopy, Thermogravimetric analysis (TGA), Energy-dispersive X-ray spectroscopy (EDX), and four-point probe (FPP) measurement. The characterized values were extracted from the results and analyzed by Cluster analysis (CA) with JMP software. CA was used to classify how carbons are related to each other.
The clusters were divided into 3 big groups according to the presence of 002 peak and the degree of defects. Some clusters have been shown high conductivity when they have high crystallinity. It was also found that the heteroatomic effect was higher than the crystallinity in the part showing low EC range. However overall correlation with EC is still unclear. This is because XRD and Raman can only provide information of symmetric or periodic structures rather than the effect of disorder or amorphous parts, sizes and shapes are not considered. Thus, analysis of shapes and sizes such as SEM and BET, and additional measurements related to amorphous structures may be helpful to clarifying the correlation.
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