Reconstruction of 3D Porous Geometry for Coupled FEM-CFD Simulation

Porous materials can be found in numerous areas of life (e. g., applied science, material science), however, the simulation of the fluid flow and transport phenomena through porous media is a significant challenge nowadays. Numerical simulations can help to analyze and understand physical processes and different phenomena in the porous structure, as well as to determine certain parameters that are difficult or impossible to measure directly or can only be determined by expensive and time-consuming experiments. The basic condition for the numerical simulations is the 3D geometric model of the porous material sample, which is the input parameter of the simulation. For this reason, geometry reconstruction is highly critical for pore-scale analysis. This paper introduces a complex process for the preparation of the microstructure's geometry in connection with a coupled FEM-CFD two-way fluid-structure interaction simulation. Micro-CT has been successfully applied to reconstruct both the fluid and solid phases of the used porous material.

Creation of a collection of blood samples of patients with multiple myeloma

Aim. To create a collection of samples of blood components of patients with multiple myeloma for potential fundamental and applied biomedical research.Material and methods. The material was collected according to the developed algorithm, including the collection of clinical information, biological material, sample preparation, quality control and storage in the biobank of the National Medical Research Center of Oncology.Results. As of August 2021, the cryostorage of the National Medical Research Center of Oncology biobank contains a collection of 175 samples of blood serum, plasma and mononuclear cell fraction of patients with multiple myeloma. Samples were obtained from 32 patients of both sexes, the mean age of which was 59,5±1,65 years. To create an electronic catalog, personal, clinical and laboratory data about patients were collected, after which each sample was assigned its own unique identification number. Written informed consent was obtained from all patients for the storage of their biomaterial in a biobank with possible subsequent use for scientific purposes. Freezing of the obtained samples was carried out in accordance with low-temperature storage protocol. The electronic catalog contains a wide range of systematized clinical and laboratory information on samples.Conclusion. The collection of multiple myeloma samples is a unique resource for potential research on its pathophysiology, the development of diagnostic biomarkers, and the search for targeted agents.

Pore-scale investigation of dynamic effects on the moisture retention curve during spontaneous imbibition

The moisture retention curve of porous materials is often assumed to be independent of the process dynamics, i.e., of the drying/wetting rate. Experimental outcomes and pore-scale simulations put this assumption into question though. It has been shown that dynamic effects can significantly affect the moisture retention curve, which presents different behaviours, depending on whether it is determined at transient or steady-state conditions. The cause of this phenomenon is addressed as “dynamic effects” in the literature. While dynamic effects of the drainage process have been widely studied, the data concerning spontaneous imbibition are still quite limited. We attempt at reducing this lack of knowledge by modelling spontaneous imbibition in an artificial material sample represented by a pore network model. In our model, the liquid flow is described via the Hagen-Poiseuille equation, while a percolation algorithm controls the dynamics of liquid-gas interfaces through the network junctions. A dynamic contact angle between liquid water and pore surface is considered, depending on the velocity of the meniscus. Dynamic states are determined by linking the local capillary pressure to the local moisture content in the artificial material sample subject to spontaneous imbibition. Our investigation demonstrates that dynamic effects due to contact angle variations may have a major impact on the imbibition process.

Shape-programmable liquid crystal elastomer structures with arbitrary three-dimensional director fields and geometries

Liquid crystal elastomers exhibit large reversible strain and programmable shape transformations, enabling various applications in soft robotics, dynamic optics, and programmable origami and kirigami. The morphing modes of these materials depend on both their geometries and director fields. In two dimensions, a pixel-by-pixel design has been accomplished to attain more flexibility over the spatial resolution of the liquid crystal response. Here we generalize this idea in two steps. First, we create independent, cubic light-responsive voxels, each with a predefined director field orientation. Second, these voxels are in turn assembled to form lines, grids, or skeletal structures that would be rather difficult to obtain from an initially connected material sample. In this way, the orientation of the director fields can be made to vary at voxel resolution to allow for programmable optically- or thermally-triggered anisotropic or heterogeneous material responses and morphology changes in three dimensions that would be impossible or hard to implement otherwise.

Internet of Samples: Progress report

Material samples form an important portion of the data infrastructure for many disciplines. Here, a material sample is a physical object, representative of some physical thing, on which observations can be made. Material samples may be collected for one project initially, but can also be valuable resources for other studies in other disciplines. Collecting and curating material samples can be a costly process. Integrating institutionally managed sample collections, along with those sitting in individual offices or labs, is necessary to faciliate large-scale evidence-based scientific research. Many have recognized the problems and are working to make data related to material samples FAIR: findable, accessible, interoperable, and reusable. The Internet of Samples (i.e., iSamples) is one of these projects. iSamples was funded by the United States National Science Foundation in 2020 with the following aims: enable previously impossible connections between diverse and disparate sample-based observations; support existing research programs and facilities that collect and manage diverse sample types; facilitate new interdisciplinary collaborations; and provide an efficient solution for FAIR samples, avoiding duplicate efforts in different domains (Davies et al. 2021) enable previously impossible connections between diverse and disparate sample-based observations; support existing research programs and facilities that collect and manage diverse sample types; facilitate new interdisciplinary collaborations; and provide an efficient solution for FAIR samples, avoiding duplicate efforts in different domains (Davies et al. 2021) The initial sample collections that will make up the internet of samples include those from the System for Earth Sample Registration (SESAR), Open Context, the Genomic Observatories Meta-Database (GEOME), and Smithsonian Institution Museum of Natural History (NMNH), representing the disciplines of geoscience, archaeology/anthropology, and biology. To achieve these aims, the proposed iSamples infrastructure (Fig. 1) has two key components: iSamples in a Box (iSB) and iSamples Central (iSC). The iSC component will be a permanent Internet service that preserves, indexes, and provides access to sample metadata aggregated from iSBs. It will also ensure that persistent identifiers and sample descriptions assigned and used by individual iSBs are synchronized with the records in iSC and with identifier authorities like International Geo Sample Number (IGSN) or Archival Resource Key (ARK). The iSBs create and maintain identifiers and metadata for their respective collection of samples. While providing access to the samples held locally, an iSB also allows iSC to harvest its metadata records. The metadata modeling strategy adopted by the iSamples project is a metadata profile-based approach, where core metadata fields that are applicable to all samples, form the core metadata schema for iSamples. Each individual participating collectionis free to include additional metadata in their records, which will also be harvested by iSC and are discoverable through the iSC user interface or APIs (Application Programming Interfaces), just like the core. In-depth analysis of metadata profiles used by participating collections, including Darwin Core, has resulted in an iSamples core schema currently being tested and refined through use. See the current version of the iSamples core schema. A number of properties require a controlled vocabulary. Controlled vocabularies used by existing records are kept, while new vocabularies are also being developed to support high-level grouping with consistent semantics across collection types. Examples include vocabularies for Context Category, Material Category, and Specimen Type (Table 1). These vocabularies were also developed in a bottom-up manner, based on the terms used in the existing collections. For each vocabulary, a decision tree graph was created to illustrate relations among the terms, and a card sorting exercise was conducted within the project team to collect feedback. Domain experts are invited to take part in this exercise here, here, and here. These terms will be used as upper-level terms to the existing category terms used in the participating collections and hence create connections among individual participating collections. iSample project members are also active in the TDWG Material Sample Task Group and the global consultation on Digital Extended Specimens. Many members of the iSamples project also lead or participate in a sister research coordination network (RCN), Sampling Nature. The goal of this RCN is to develop and refine metadata standards and controlled vocabularies for the iSamples and other projects focusing on material samples. We cordially invite you to participate in the Sampling Nature RCN and help shape the future standards for material samples. Contact Sarah Ramdeen ([email protected]) to engage with the RCN.

Learning Medical Materials From Radiography Images

Deep learning models have been shown to be effective for material analysis, a subfield of computer vision, on natural images. In medicine, deep learning systems have been shown to more accurately analyze radiography images than algorithmic approaches and even experts. However, one major roadblock to applying deep learning-based material analysis on radiography images is a lack of material annotations accompanying image sets. To solve this, we first introduce an automated procedure to augment annotated radiography images into a set of material samples. Next, using a novel Siamese neural network that compares material sample pairs, called D-CNN, we demonstrate how to learn a perceptual distance metric between material categories. This system replicates the actions of human annotators by discovering attributes that encode traits that distinguish materials in radiography images. Finally, we update and apply MAC-CNN, a material recognition neural network, to demonstrate this system on a dataset of knee X-rays and brain MRIs with tumors. Experiments show that this system has strong predictive power on these radiography images, achieving 92.8% accuracy at predicting the material present in a local region of an image. Our system also draws interesting parallels between human perception of natural materials and materials in radiography images.

Influence of the ore reduction method on the percolation leaching efficiency

This paper covers gold leaching from sulfide ores. The data on the silicate, mineral, and grain-size composition are presented for the ore studied. Agitation leaching studies were completed for the combined sample and direct cyanidation dynamics indicators are established for the material sample. For all material with the grain size class of 95 % passing –0.074 mm, the required agitation leaching duration is 9–10 hours; with the material sizes up to 2 mm, the leaching duration shall be at least 22 hours. In order to study the efficiency of using roller presses as an alternative to fine crushing, two percolation leaching tests were conducted for the ore size of –5 mm. The material for the first test was prepared by crushing in a standard jaw crusher and the material for the second test was prepared by crushing in a laboratory press with complex monolayer reduction. It has been found that ore reduction using high-pressure crushers, as compared to standard crushing equipment, allows increasing gold recovery during subsequent leaching by 13.52 %. At the same time, the consumption of sodium cyanide increases by 0.26 kg/t of ore.

Optimization of RHDV type 1 and 2 inactivation modes

The purpose of these studies was to optimize RHDV type 1 and 2 (RHDV1 and RHDV2) inactivation modes to use the obtained antigens in inactivated vaccines and diagnosticums. The inactivating effect of aminoethylethylenimine and β-propiolactone was studied in different concentrations in correlation with the exposure time and temperature. The correlation between the inactivating effect of the compound used and the accepted test conditions (concentration, temperature, and exposure time) was studied on a group of rabbits, each of which was injected intramuscularly with 1 cm3 of the inactivated material sample. At the end of the maximum exposure interval, a control sample of the viral material, kept under the same conditions without any inactivant added was similarly tested. Lethality was considered to evaluate the damaging action in the test and control groups: L = m/n, where m is the number of dead animals; n is the total number of rabbits in the group for testing of the inactivated material sample. The postmortem diagnosis was confirmed by testing the rabbit liver tissue homogenate for relative antigens using ELISA. It was found that aminoethylethylenimine and β-propiolactone did not have the same effect on the studied variants of the virus. In order to preserve at maximum the antigenic structures of the virus, the following inactivation modes were considered to be optimal: for RHDV1-aminoethylethylenimine at a concentration of 0.3% at 37 °C, exposure time – 72 hours, or β-propiolactone at a concentration of 0.1–0.3% at 25–37 °С, exposure time – 24–48 hours; for RHDV2 – aminoethylethylenimine at a concentration of 1% at 37 °C, exposure time – 72 hours, or β-propiolactone at a concentration 0.3% at 25 °С, exposure time – 24 hours.