Investigations on Thermal Conductivity of Two-Phase WC-Co-Ni Cemented Carbides through a Novel Model and Key Experiments.

Excellent thermal conductivity is beneficial for the fast heat release during service of cemented carbides. Thus, thermal conductivity is a significant property of cemented carbides, considerably affecting their service life. Still, there is a lack of systematic investigation into the thermal conductivity of two-phase WC-Co-Ni cemented carbides. To remedy this situation, we integrated experiments and models to study its thermal conductivity varying the phase composition, temperature and WC grain size. To conduct the experiments, WC-Co-Ni samples with two-phase structure were designed via the CALPHAD (Calculation of Phase Diagrams) approach and then prepared via the liquid-phase sintering process. Key thermal conductivity measurements of these prepared samples were then taken via LFA (Laser Flash Analysis). As for modeling, the thermal conductivities of (Co, Ni) binder phase and WC hard phase were firstly evaluated through our previously developed models for single-phase solid solutions. Integrating the present key measurements and models, the values of ITR (Interface Thermal Resistance) between WC hard phase and (Co, Ni) binder phase were evaluated and thus the model to calculate thermal conductivity of two-phase WC-Co-Ni was established. Meanwhile, this model was verified to be reliable through comparing the model-evaluated thermal conductivities with the experimental data. Furthermore, using this developed model, the thermal conductivity of two-phase WC-Co-Ni varying with phase-fraction, temperature and grain size of WC was predicted, which can contribute to its design for obtaining desired thermal conductivities.

Deep Neural Network-Evaluated Thermal Conductivity for Two-Phase WC-M (M = Ag, Co) Cemented Carbides.

DNN (Deep Neural Network) is one kind of method for artificial intelligence, which has been applied in various fields including the exploration of material properties. In the present work, DNN, in combination with the 10-fold cross-validation, is applied to evaluate and predict the thermal conductivities for two-phase WC-M (M = Ag, Co) cemented carbides. Multi-layer DNNs were established by learning the measured thermal conductivities for the WC-Ag and WC-Co systems. It is observed that there are local-minimum regions for the loss functions during training and testing the DNNs, and the presently utilized Adam optimizer is valid for breaking the local-minimum regions. The good agreements between the DNN-evaluated thermal conductivities and the measured ones manifest that the DNNs were well trained and tested. Moreover, another 1000 input data points were randomly generated for the established DNNs to predict the thermal conductivities for WC-Ag and WC-Co systems, respectively. Compared with the thermal conductivities predicted by the previously developed physical model, the presently established DNNs show similarly robust predicting ability. Concerning the efficiency, it is demonstrated in the present work that machine learning is promising to explore the material properties, especially in the high-dimensional parameter space, more efficiently than previous models, and thus can considerably contribute to the corresponding material design with less time consumption and costs.

Flexible Overoxidized Polypyrrole Films with Orderly Structure as High-Performance Anodes for Li- and Na-Ion Batteries.

Flexible polypyrrole (PPy) films with highly ordered structures were fabricated by a novel vapor phase polymerization (VPP) process and used as the anode material in lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs). The PPy films demonstrate excellent rate performance and cycling stability. At a charge/discharge rate of 1 C, the reversible capacities of the PPy film anode reach 284.9 and 177.4 mAh g-1 in LIBs and SIBs, respectively. Even at a charge/discharge rate of 20 C, the reversible capacity of the PPy film anode retains 54.0% and 52.9% of the capacity of 1 C in LIBs and SIBs, respectively. After 1000 electrochemical cycles at a rate of 10 C, there is no obvious capacity fading. The molecular structure and electrochemical behaviors of Li- and Na-ion doping and dedoping in the PPy films are investigated by XPS and ex situ XRD. It is believed that the PPy film electrodes in the overoxidized state can be reversibly charged and discharged through the doping and dedoping of lithium or sodium ions. Because of the self-adaptation of the doped ions, the ordered pyrrolic chain structure can realize a fast charge/discharge process. This result may substantially contribute to the progress of research into flexible polymer electrodes in various types of batteries.

A combinatorial characterization scheme for high-throughput investigations of hydrogen storage materials.

In order to increase measurement throughput, a characterization scheme has been developed that accurately measures the hydrogen storage properties of materials in quantities ranging from 10 ng to 1 g. Initial identification of promising materials is realized by rapidly screening thin-film composition spread and thickness wedge samples using normalized IR emissivity imaging. The hydrogen storage properties of promising samples are confirmed through measurements on single-composition films with high-sensitivity (resolution <0.3 µg) Sievert's-type apparatus. For selected samples, larger quantities of up to ∼100 mg may be prepared and their (de)hydrogenation and micro-structural properties probed via parallel in situ Raman spectroscopy. Final confirmation of the hydrogen storage properties is obtained on ∼1 g powder samples using a combined Raman spectroscopy/Sievert's apparatus.