Monte-Carlo Simulations of Spin-Crossover Phenomena Based on a Vibronic Ising-like Model with Realistic Parameters

Materials with spin-crossover (SCO) properties hold great potentials in information storage and therefore have received a lot of concerns in the recent decades. The hysteresis phenomena accompanying SCO is attributed to the intermolecular cooperativity whose underlying mechanism may have a vibronic origin. In this work, a new vibronic Ising-like model in which the elastic coupling between SCO centers is included by considering harmonic stretching and bending (SAB) interactions is proposed and solved by Monte Carlo simulations. The key parameters in the new model, $k_1$ and $k_2$, corresponding to the elastic constant of the stretching and bending mode, respectively, can be directly related to the macroscopic bulk and shear modulus of the material in study, which can be readily estimated either based on experimental measurements or first-principles calculations. The convergence issue in the MC simulations of the thermal hysteresis has been carefully checked, and it was found that the stable hysteresis loop can be more readily obtained when using the SAB model compared to that using the Wajnflasz-Pick model. Using realistic parameters estimated based on first-principles calculations of a specific polymeric coordination SCO compound, [Fe(pz)Pt(CN)$_4$]$\cdot$2H$_2$O, temperature-induced hysteresis and pressure effects on SCO phenomena are simulated successfully.Comment: 8 pages, 8 figure

Microstructural Characterization of Shrouded Plasma-Sprayed Titanium Coatings

Titanium and its alloys are often used for corrosion protection because they are able to offer high chemical resistance against various corrosive media. In this paper, shrouded plasma spray technology was applied to produce titanium coatings. A solid shroud with an external shrouding gas was used to plasma spray titanium powder feedstock with aim of reducing the oxide content in the as-sprayed coatings. The titanium coatings were assessed by optical microscope, scanning electron microscopy, X-ray diffraction, LECO combustion method and Vickers microhardness testing. The results showed that the presence of the shroud and the external shrouding gas led to a dense microstructure with a low porosity in the plasma-sprayed titanium coatings. The oxygen and nitrogen contents in the titanium coating were kept at a low level due to the shielding effect of the shroud attachment and the external shrouding gas. The dominant phase in the shrouded titanium coatings was mainly composed of α-Ti phase, which was very similar to the titanium feedstock powders. The shrouded plasma-sprayed titanium coatings had a Vickers microhardness of 404.2 ± 103.2 HV

Online Filter Clustering and Pruning for Efficient Convnets

Pruning filters is an effective method for accelerating deep neural networks (DNNs), but most existing approaches prune filters on a pre-trained network directly which limits in acceleration. Although each filter has its own effect in DNNs, but if two filters are the same with each other, we could prune one safely. In this paper, we add an extra cluster loss term in the loss function which can force filters in each cluster to be similar online. After training, we keep one filter in each cluster and prune others and fine-tune the pruned network to compensate for the loss. Particularly, the clusters in every layer can be defined firstly which is effective for pruning DNNs within residual blocks. Extensive experiments on CIFAR10 and CIFAR100 benchmarks demonstrate the competitive performance of our proposed filter pruning method.Comment: 5 pages, 4 figure