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Rapid orbital drift of macroscopic dust particles is one of the major obstacles against planetesimal formation in protoplanetary disks. We reexamine this problem by considering porosity evolution of dust aggregates. We apply a porosity…
Seismic attenuation in granular porous media is of paramount importance in rock physics and seismology. Unlike sandstones, shales are mixtures of sand grains and clays with extremely low porosity and permeability. Swelling of clays upon…
Dynamic characterization of mechanical properties of dust aggregates has been one of the most important problems to quantitatively discuss the dust growth in protoplanetary disks. We experimentally investigate the dynamic properties of dust…
Each grid block in a 3D geological model requires a rock type that represents all physical and chemical properties of that block. The properties that classify rock types are lithology, permeability, and capillary pressure. Scientists and…
A new mode of nuclear fission has been proposed by the FOBOS collaboration, called Collinear Cluster Tri-partition (CCT), suggesting that three heavy fission fragments can be emitted perfectly collinearly in low-energy fission. It is…
Exploiting convolutional neural networks for point cloud processing is quite challenging, due to the inherent irregular distribution and discrete shape representation of point clouds. To address these problems, many handcrafted convolution…
Bit Patterned Media (BPM) for magnetic recording provide a route to densities $>1 Tb/in^2$ and circumvents many of the challenges associated with conventional granular media technology. Instead of recording a bit on an ensemble of random…
This article provides an overview of the current state of digital rock technology, with emphasis on industrial applications. We show how imaging and image analysis can be applied for rock typing and modeling of end-point saturations.…
To avoid the impact of inherent natural imperfections on experimental outcomes during testing, a recently designed genuine triaxial apparatus has enabled the replication of conditions where the three principal stresses exhibit varying…
Organic molecular crystals are ideally placed to become next-generation piezoelectric materials due to their diverse chemistries that can be used to engineer tailor-made solid-state assemblies. Using crystal engineering principles, and…
The field of complex self-assembly is moving toward the design of multi-particle structures consisting of thousands of distinct building blocks. To exploit the potential benefits of structures with such `addressable complexity,' we need to…
We propose a bit-flip descent method for optimizing binary spreading codes with large family sizes and long lengths, addressing the challenges of large-scale code design in GNSS and emerging PNT applications. The method iteratively flips…
The drilling of geothermal energy, CO2 sequestration, and wastewater injection all involve the pressurized flow of fluids through porous rock, which can cause deformation and fracture of the material. Despite the widespread use of these…
Most recent person re-identification approaches are based on the use of deep convolutional neural networks (CNNs). These networks, although effective in multiple tasks such as classification or object detection, tend to focus on the most…
Short-fiber-reinforced polymer composites are increasingly used in engineering applications and industrial products owing to their unique combination of superior mechanical properties, and relatively easy and low cost manufacturing process.…
Deep Convolutional Neural Networks (CNN) have been successfully applied to many real-life problems. However, the huge memory cost of deep CNN models poses a great challenge of deploying them on memory-constrained devices (e.g., mobile…
The mechanical behaviour of porous sandstones is generally modelled using concepts from granular mechanics, often overlooking the effect of cementation. To probe the key differences between sand and sandstone mechanics, we performed…
Due to their exceptional mechanical and chemical properties and their natural abundance, cellulose nanocrystals (CNCs) are promising building blocks of sustainable polymer composites. However, the rapid gelation of CNC dispersions has…
The objective of this work is to study the applicability of various Machine Learning algorithms for prediction of some rock properties which geoscientists usually define due to special lab analysis. We demonstrate that these special…
Circular colliders have the advantage of delivering collisions to multiple interaction points, which allow different detector designs to be studied and optimized - up to four for FCC-ee. On the one hand, the detectors must satisfy the…