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Adhesion interaction of epoxy resin with the basal surfaces of h-BN and graphite is investigated with the first-principles density functional theory calculations in conjunction with the dispersion correction. The h-BN/epoxy and graphite/epoxy interfaces play an important role in producing nanocomposite materials with excellent thermal dissipation properties. The epoxy resin structure is simulated by using four kinds of fragmentary models. Their structures are optimized on the h-BN and graphite surfaces after an annealing simulation. The distance between the epoxy fragment and the surface is about 3 Å. At the interface between h-BN and epoxy resin, no H-bonding formation is observed, though one could expect that the active functional groups of epoxy resin, such as hydroxyl (−OH) group, would be involved in a hydrogen-bonding interaction with nitrogen atoms of the h-BN surface. The adhesion energies for the two interfaces are calculated, showing that these two interfaces are characterized by almost the same strength of adhesion interaction. To obtain the adhesion force–separation curve for the two interfaces, the potential energy surface associated with the detachment of the epoxy fragment from the surface is calculated with the help of the nudged elastic band method and then the adhesion force is obtained by using either the Morse-potential approximation or the Hellmann–Feynman force calculation. The results from both methods agree with each other. The maximum adhesion force for the h-BN/epoxy interface is as high as that for the graphite/epoxy interface. To better understand this result, a force-decomposition analysis is carried out, and it has been disclosed that the adhesion forces working at both interfaces mainly come from the dispersion force. The trend of increase in the C 6 parameters used for the dispersion correction for the atoms included in the h-BN or graphite surface is in the order: N < C < B, which reasonably explains why the strengths of the dispersion forces operating at the two interfaces are similar. Also, the electron localization function analysis can explain why the h-BN surface cannot form an H bond with the hydroxyl group in epoxy resin.

Application of high electric field is effective for the alignment of carbon nanotube (CNT) in a nanocomposite film. The conventionally used single pair of parallel plate electrodes is not applicable to large-sized nanocomposite fabrication due to limited output voltage of the high-voltage source. We have proposed an array of parallel wire electrodes to address this issue. The composite material was spread over a thin dielectric layer placed on the wire electrodes. The high electric field region can be extended over a wider area just by increasing the number of electrode pairs. Discrete electric field distribution bordered by the wire electrodes was avoided by linearly oscillated motion of the composite film. A CNT/epoxy resin composite film with a size of 15 cm × 15 cm was successfully fabricated.

&HCO/k = 200K [I]. Using O O H -H C O = (00s + O H C 0 ) / 2 and EOH-HCO = E~~~) "~one obtains a collision frequency of ZLJ = 1.9. l O l 4 cm3/mols. Thus, reaction (2) proceeds at a rate very near to its maximum theoretical value. Chemical Kinetics / Complex Compounds / Neutralization / Reaction tiolumeReaction volumes at infinite dilution (Avo) were obtained at 25°C using a Carlsberg dilatometer for 19 reactions of the type MAZ + OH-+ MBz-' + H 2 0 , where M = Pt(IV), Rh(II1) and Co(II1); A = H 2 0 , NH, and C20,H; B = OH, NH2_and C 2 0 4 ; and z = charge on complex which was varied between 4 + and 2 -by selecting appropriate non-participating ligands. The values of A Vo strongly depend on z and range from 35.5 * 0.4 for Pt(NH,);f+ to 2.4 + 0.3 cm3 mol--' for Co(CN),OH;-. The results are consistent with the fundamental theories concerning electrostriction effects,andAvocanbeexpressedasAVo = (14.5 ? 0.8) -(2.5 * 0.2) Az2cm3 mol-' where Az2 = (z-1)2 -2'. In addition it was found that

Novel metal-organic frameworks containing lanthanide double-layer-based secondary building units (KGF-3) were synthesized by using machine learning (ML). Isolating pure KGF-3 was challenging, and the synthesis was not reproducible because impurity phases were frequently obtained under the same synthetic conditions. Thus, dominant factors for the synthesis of KGF-3 were identified, and its synthetic conditions were optimized by using two ML techniques. Cluster analysis was used to classify the obtained powder X-ray diffractometry patterns of the products and thus automatically determine whether the experiments were successful. Decision-tree analysis was used to visualize the experimental results, after extracting factors that mainly affected the synthetic reproducibility. Water-adsorption isotherms revealed that KGF-3 possesses unique hydrophilic pores. Impedance measurements demonstrated good proton conductivities (σ = 5.2 × 10 À 4 S cm À 1 for KGF-3(Y)) at a high temperature (363 K) and relative humidity of 95 % RH.