Accelerating Hair Rendering by Learning High-Order Scattered Radiance

Efficiently and accurately rendering hair accounting for multiple scattering is a challenging open problem. Path tracing in hair takes long to converge while other techniques are either too approximate while still being computationally expensive or make assumptions about the scene. We present a technique to infer the higher order scattering in hair in constant time within the path tracing framework, while achieving better computational efficiency. Our method makes no assumptions about the scene and provides control over the renderer's bias & speedup. We achieve this by training a small multilayer perceptron (MLP) to learn the higher-order radiance online, while rendering progresses. We describe how to robustly train this network and thoroughly analyze our resulting renderer's characteristics. We evaluate our method on various hairstyles and lighting conditions. We also compare our method against a recent learning based & a traditional real-time hair rendering method and demonstrate better quantitative & qualitative results. Our method achieves a significant improvement in speed with respect to path tracing, achieving a run-time reduction of 40%-70% while only introducing a small amount of bias.     

γ-irradiation hardness investigations of (PANI)1−x(Bi2Te3)x composites for thermistor applications

The (PANI)_1−x(Bi₂Te₃)_x composites were successfully synthesized. These composites have a simple physical combination of intrinsic conducting polymer and nanocrystal topological insulator materials which are promising new materials for unusual applications. The influence of γ-irradiation (100 kGy doses) on the performance of the (PANI)_1−x(Bi₂Te₃)_x composites was described by atypical techniques to assess the radiation hardness of the samples. X-ray diffraction and Raman spectroscopy measurements show the semi-crystalline phases, the other structural parameters, and the phonon modes. The compositional analysis and the morphological properties were investigated by energy-dispersive X-ray, while transmission electron microscopy imaging confirmed the morphology of the dopants of Bi₂Te₃ nanoparticles into the polyaniline (PANI) matrix, which shows the accumulation of the particles. Thermogravimetric analysis figured out the degradation behavior of the compositions. The representative electron spin resonance (ESR) signal exhibits a narrow single-line ESR spectrum for PANI/Bi₂Te₃ nanoparticle concentrations. (PANI)_1−x(Bi₂Te₃)_x illustrates unexpected ferromagnetic behavior that confirms the magnetic performance of the samples without introducing any magnetic dopants. The obtained materials showed promising performance for using such hybrid materials as a positive temperature coefficient thermistor.