Faience Waste for the Production of Wall Products

Increasing the efficiency of using gypsum binders can be carried out by using not natural gypsum raw materials, but calcium sulfate-containing waste from various industries (phosphogypsum, borogypsum, citrogypsum, etc.). As the main source material in the work, we used gypsum-containing waste from a faience factory in the form of waste molds for casting dishes, souvenirs and plumbing fixtures. It has been established that the optimal binding system is formed by mixing powders of dihydrate technogenic gypsum from a coarse and fine earthenware factory with average particle diameters of 3.473 microns and 3.065 microns in a percentage ratio of 30:70, respectively. Using a computer software developed by the authors, which makes it possible to simulate the microstructure of a raw mixture taking into account the contact interaction of particles and calculate the average coordination number, models of binary packing of particles were constructed at various ratios of their diameters. Studies of the strength of composites obtained on the basis of bidisperse systems have shown the presence of an extremum in the region of mixtures containing 30% coarse powder. With optimal packing, a large number of phase contacts are formed due to the regulation of the grain composition of the bidisperse system. It was revealed that a brick based on the waste of two-water gypsum from earthenware production has 2.5–5 times better characteristics of compressive strength than traditional building wall products based on natural gypsum. At the same time, the strength immediately after molding is more than 3 times higher than that of traditional gypsum products. Even higher indicators are achieved when adding microcalcite in addition to the waste of earthenware production, in this case, the compressive strength is 3–6 times higher, and the strength immediately after molding is almost 3 times higher than that of traditional gypsum products.

Identifying the Optimal Packing and Routing to Improve Last-Mile Delivery Using Cargo Bicycles

Efficient vehicle routing is a major concern for any supply chain, especially when dealing with last-mile deliveries in highly urbanized areas. In this paper problems considering last-mile delivery in areas with the restrictions of motorized traffic are described and different types of cargo bikes are reviewed. The paper describes methods developed in order to solve a combination of problems for cargo bicycle logistics, including efficient packing, routing and load-dependent speed constraints. Proposed models apply mathematical descriptions of problems, including the Knapsack Problem, Traveling Salesman Problem and Traveling Thief Problem. Based on synthetically generated data, we study the efficiency of the proposed algorithms. Models described in this paper are implemented in Python programming language and will be further developed and used for solving the problems of electric cargo bikes’ routing under real-world conditions.

Optimal Random Packing of Spheres and Extremal Effective Conductivity

A close relation between the optimal packing of spheres in Rd and minimal energy E (effective conductivity) of composites with ideally conducting spherical inclusions is established. The location of inclusions of the optimal-design problem yields the optimal packing of inclusions. The geometrical-packing and physical-conductivity problems are stated in a periodic toroidal d-dimensional space with an arbitrarily fixed number n of nonoverlapping spheres per periodicity cell. Energy E depends on Voronoi tessellation (Delaunay graph) associated with the centers of spheres ak (k=1,2,…,n). All Delaunay graphs are divided into classes of isomorphic periodic graphs. For any fixed n, the number of such classes is finite. Energy E is estimated in the framework of structural approximations and reduced to the study of an elementary function of n variables. The minimum of E over locations of spheres is attained at the optimal packing within a fixed class of graphs. The optimal-packing location is unique within a fixed class up to translations and can be found from linear algebraic equations. Such an approach is useful for random optimal packing where an initial location of balls is randomly chosen; hence, a class of graphs is fixed and can dynamically change following prescribed packing rules. A finite algorithm for any fixed n is constructed to determine the optimal random packing of spheres in Rd.

First person – Neha Khetan

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Neha Khetan is first author on ‘Self-organized optimal packing of kinesin-5-driven microtubule asters scales with cell size’, published in JCS. Neha is a CEFIPRA postdoctoral research fellow in the lab of Chaitanya A. Athale at the Indian Institute of Science Education and Research, Pune, India, investigating the interplay of self-organization and evolutionary forces in cytoskeletal patterns and collective behaviour.

Breaking the Upper Bound of Siloxane Uptake: Metal-Organic Frameworks as an Adsorbent Platform

Biogas, regarded as a promising renewable energy source, still needs to be upgraded. This calls for the removal of the most prominent contaminants, among others the octamethylcyclotetrasiloxane (D4) molecule. Herein, high throughput computational screening in tandem with synthesis and adsorption testing revealed the hydrophobic Zr-MOF PCN-777 as an optimal D4 adsorbent with record gravimetric (1.8 g/g) and volumetric (0.49 g/cm3) uptakes, alongside with a reversible and fast adsorption/desorption process, good cyclability and easy regeneration. This MOF was demonstrated to encompass an ideal combination of mesoporous cages and chemical functionality to enable an optimal packing of the siloxane molecules and their efficient removal while maintaining the process highly reversible thanks to moderately high host/guest interactions. This work highlights the efficacy of an integrated workflow for accelerating adsorbent selection for a desired application, spanning the entire pipeline from method validation to computational screening, synthesis and adsorption testing towards the identification of the optimal adsorbents.<br>

Breaking the Upper Bound of Siloxane Uptake: Metal-Organic Frameworks as an Adsorbent Platform

Biogas, regarded as a promising renewable energy source, still needs to be upgraded. This calls for the removal of the most prominent contaminants, among others the octamethylcyclotetrasiloxane (D4) molecule. Herein, high throughput computational screening in tandem with synthesis and adsorption testing revealed the hydrophobic Zr-MOF PCN-777 as an optimal D4 adsorbent with record gravimetric (1.8 g/g) and volumetric (0.49 g/cm3) uptakes, alongside with a reversible and fast adsorption/desorption process, good cyclability and easy regeneration. This MOF was demonstrated to encompass an ideal combination of mesoporous cages and chemical functionality to enable an optimal packing of the siloxane molecules and their efficient removal while maintaining the process highly reversible thanks to moderately high host/guest interactions. This work highlights the efficacy of an integrated workflow for accelerating adsorbent selection for a desired application, spanning the entire pipeline from method validation to computational screening, synthesis and adsorption testing towards the identification of the optimal adsorbents.<br>

Optimal packing in 2D and 3D granular systems: Density, connectivity, and force distributions

In this work, we explore the influence of the grain size distribution (GSD) on density, connectivity and internal forces distributions, for both 2D and 3D granular packings built mechanically. For power law GSDs, we show that there is an exponent for which density and connectivity are optimized, and this exponent is close to those that characterize other well known GSDs such as the Fuller and Thompson distribution and the Appollonian packing. In addition, we studied the distributions of normal forces, finding that these can be well described by a power-law tail, specially for the GSDs with large size span. These results highlight the role of the GSD on internal structure and suggest important consequences on macroscopic properties.

PENENTUAN PERSEDIAAN OPTIMAL PACKING MATERIAL MENGGUNAKAN METODE FIS MAMDANI PADA PERUSAHAAN TEKSTIL DI JAWA TENGAH

Pengelolaan persediaan merupakan bagian penting dalam perusahaan yang mendukung berlangsungnya proses produksi. Namun dalam pengelolaan persediaan barang, masih ditemukan beberapa persediaan barang yang jumlahnya berlebihan dan ada yang kekurangan. Perlu adanya analisis jumlah pengadaan barang yang dapat menyebabkan jumlah persediaan barang menjadi optimal. Apabila dapat ditentukan jumlah pengadaan barang optimal, maka jumlah persediaan barang juga akan optimal karena jumlah persediaan barang adalah jumlah stok awal barang ditambah jumlah pengadaan barang. Penelitian ini menerapkan Metode FIS (Fuzzy Inference System) Mamdani untuk menentukan jumlah pengadaan barang yang optimal berdasarkan jumlah stok awal barang dan jumlah permintaan barang. Disusun model FIS Mamdani dengan menentukan Himpunan Fuzzy sebagai variabel linguistik pembentuk aturan dalam model persediaan agar dapat menghasilkan jumlah persediaan barang optimal dan memenuhi batas yang diberikan oleh perusahaan. Hasil penelitian pada 4 jenis barang yang dipilih menunjukkan bahwa jumlah pengadaan barang berdasarkan model persediaan FIS Mamdani lebih baik dibandingkan dengan pengadaan real di perusahaan tekstil Jawa Tengah.