A Case Study on Optimization of Biomass Flow During Single-Screw Extrusion Cooking Using Genetic Algorithm (GA) and Response Surface Method (RSM)

In the present study, response surface method (RSM) and genetic algorithm (GA) were used to study the effects of process variables like screw speed, rpm (x ₁), L/D ratio (x ₂), barrel temperature (°C; x ₃), and feed mix moisture content (%; x ₄), on flow rate of biomass during single-screw extrusion cooking. A second-order regression equation was developed for flow rate in terms of the process variables. The significance of the process variables based on Pareto chart indicated that screw speed and feed mix moisture content had the most influence followed by L/D ratio and barrel temperature on the flow rate. RSM analysis indicated that a screw speed?>?80 rpm, L/D ratio?>?12, barrel temperature?>?80 °C, and feed mix moisture content?>?20% resulted in maximum flow rate. Increase in screw speed and L/D ratio increased the drag flow and also the path of traverse of the feed mix inside the extruder resulting in more shear. The presence of lipids of about 35% in the biomass feed mix might have induced a lubrication effect and has significantly influenced the flow rate. The second-order regression equations were further used as the objective function for optimization using genetic algorithm. A population of 100 and iterations of 100 have successfully led to convergence the optimum. The maximum and minimum flow rates obtained using GA were 13.19?×?10^?7 m³/s (x ₁?=?139.08 rpm, x ₂?=?15.90, x ₃?=?99.56 °C, and x ₄?=?59.72%) and 0.53?×?10^?7 m³/s (x ₁?=?59.65 rpm, x ₂?=?11.93, x ₃?=?68.98 °C, and x ₄?=?20.04%).     

Quality characteristics of biscuits prepared from finger millet seed coat based composite flour

Finger millet seed coat is an edible material and contains good proportion of dietary fibre, minerals and phytochemicals. The seed coat matter (SCM) forms a by-product of millet milling, malting and decortication industries and can be utilised as composite flour in biscuit preparation. The SCM from native, malted and hydrothermally treated millet contained 9.5–12% protein, 2.6–3.7% fat and 40–48% dietary fibre, besides 3–5% polyphenols and 700–860 mg/100 g of calcium. The biscuits prepared using the composite flour were of crisp texture and exhibited breaking strength of 1480–1690 g compared to control biscuits (1560 g). The biscuits were of mild grey colour (ΔE = 40–50) and exhibited higher protein, dietary fibre and calcium contents. The sensory evaluation of the biscuits indicated that 10% of SCM from native and hydrothermally processed millet and 20% from malted millet could be used in composite biscuit flour.     

Computer Simulations and Network-Based Profiling of Binding and Allosteric Interactions of SARS-CoV-2 Spike Variant Complexes and the Host Receptor: Dissecting the Mechanistic Effects of the Delta and Omicron Mutations

In this study, we combine all-atom MD simulations and comprehensive mutational scanning of S-RBD complexes with the angiotensin-converting enzyme 2 (ACE2) host receptor in the native form as well as the S-RBD Delta and Omicron variants to (a) examine the differences in the dynamic signatures of the S-RBD complexes and (b) identify the critical binding hotspots and sensitivity of the mutational positions. We also examined the differences in allosteric interactions and communications in the S-RBD complexes for the Delta and Omicron variants. Through the perturbation-based scanning of the allosteric propensities of the SARS-CoV-2 S-RBD residues and dynamics-based network centrality and community analyses, we characterize the global mediating centers in the complexes and the nature of local stabilizing communities. We show that a constellation of mutational sites (G496S, Q498R, N501Y and Y505H) correspond to key binding energy hotspots and also contribute decisively to the key interfacial communities that mediate allosteric communications between S-RBD and ACE2. These Omicron mutations are responsible for both favorable local binding interactions and long-range allosteric interactions, providing key functional centers that mediate the high transmissibility of the virus. At the same time, our results show that other mutational sites could provide a “flexible shield” surrounding the stable community network, thereby allowing the Omicron virus to modulate immune evasion at different epitopes, while protecting the integrity of binding and allosteric interactions in the RBD–ACE2 complexes. This study suggests that the SARS-CoV-2 S protein may exploit the plasticity of the RBD to generate escape mutants, while engaging a small group of functional hotspots to mediate efficient local binding interactions and long-range allosteric communications with ACE2.     

The effect of magnetic and optic field in water electrolysis

Hydrogen production via water electrolysis was studied under the effect of magnetic and optical field. A diode solid state laser at blue, green and red were utilized as optical field source. Magnetic bar was employed as external magnetic field. The green laser has shown a greatest effect in hydrogen production due to its non-absorbance properties in the water. Thus its intensity of electrical field is high enough to dissociation of hydronium and hydroxide ions during orientation toward polarization of water. The potential to break the autoprotolysis and generate the auto-ionization is the mechanism of optical field to reveal the hydrogen production in water electrolysis. The magnetic field effect is more dominant to enhance the hydrogen production. The diamagnetic property of water has repelled the present of magnetic in water. Consequently the water splitting occurs due to the repulsive force induced by the external magnetic field. The magnetic distributed more homogenous in the water to involve more density of water molecule. As a result hydrogen production due to magnetic field is higher in comparison to optical field. However the combination both fields have generated superior effect whereby the hydrogen yields nine times higher in comparison to conventional water electrolysis.     

Concurrent optimisation of a computer vision system’s multiple responses

A number of recent research works have focused on how to improve the performance of production systems. This paper examines the system based on a simulation model with two manufacturing cells under a re-entrant environment. With the model a set of experiments has been carried out to study how the factors influence the system performance. Different release times and lot sizes have been compared, and scheduling heuristics for both bottleneck and non-bottleneck have been discussed to capture the essence of the production system. We used ANOVA to analyze the experimental results and achieved the conclusions that: interval releasing is better than beginning releasing; lot size can improve one of the performance indicators, but deteriorate the other under interval releasing; NC policy can obtain both good due-date performance and high throughput.     

Prediction of back break in blasting using random decision trees

Back break is an unsolicited phenomenon caused due to rock condition, blast geometry, explosive and initiation system in mines. It does not help in creating a smooth high wall and free face for next blasting due to cracks, overhang and under-hang. It can cause rockfall during drilling due to the cracks present in the in situ rock mass at the perimeter. Due to improper free face created from the previous blast and the presence of loose strata in the face increases the overall cost of production. Therefore, predicting and subsequently optimising back break shall reduce their problems to some extent. In this paper, an attempt is made to predict back break using the random forest method. The variables used for the study was such as burden to spacing ratio, stemming to hole-depth ratio, p-wave velocity and the density of explosive. For the random forest model, R² 0.9791 and RMSE 0.87899 and for linear regression was R² was 0.824 and root mean square error (RMSE) 0.72, respectively. From the field trials, it was evident that the use of low-density emulsion can help in reducing the back break and optimise the overall cost of the blasting process. The same results were validated using Random forest method wherein the model R² was 0.9791 and RMSE was 0.8799.

     

Hydrogen-iodide decomposition over PdCeO2 nanocatalyst for hydrogen production in sulfur-iodine thermochemical cycle

A highly active and stable catalyst for hydrogen-iodide decomposition reaction in sulfur-iodine (SI) cycle has been prepared in the form of PdCeO₂ nanocatalyst by sol-gel method with different calcination temperatures (300 °C, 500 °C, and 700 °C). XRD and TEM confirmed a size around 6–8 nm for PdCeO₂ particles calcined at 300 °C. Raman study revealed large number oxygen vacancies in PdCeO₂-300 when compared to PdCeO₂-500 and PdCeO₂-700. With increase in calcination temperature, the average particle size increased whereas the specific surface area and number of oxygen vacancies decreased. Hydrogen-iodide catalytic-decomposition was carried out in the temperature range of 400°C–550 °C in a quartz-tube, vertical, fixed-bed reactor with 55 wt % aqueous hydrogen-iodide feed over PdCeO₂ catalyst using nitrogen as a carrier gas. PdCeO₂-300 showed hydrogen-iodide conversion of 23.3%, which is close to the theoretical equilibrium conversion of 24%, at 550 °C. It also showed a reasonable stability with a time-on-stream of 5 h.     

Dysprosium doped copper oxide (Cu1-xDyxO) nanoparticles enabled bifunctional electrode for overall water splitting

The production of hydrogen, a favourable alternative to an unsustainable fossil fuel remains as a significant hurdle with the pertaining challenge in the design of proficient, highly productive and sustainable electrocatalyst for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, the dysprosium (Dy) doped copper oxide (Cu_1-xDy_xO) nanoparticles were synthesized via solution combustion technique and utilized as a non-noble metal based bi-functional electrocatalyst for overall water splitting. Due to the improved surface to volume ratio and conductivity, the optimized Cu_1-xDy_xO (x = 0.01, 0.02) electrocatalysts exhibited impressive HER and OER performance respectively in 1 M KOH delivering a current density of 10 mAcm^?2 at a potential of ?0.18 V vs RHE for HER and 1.53 V vs RHE for OER. Moreover, the Dy doped CuO electrocatalyst used as a bi-functional catalyst for overall water splitting achieved a potential of 1.56 V at a current density 10 mAcm^?2 and relatively high current density of 66 mAcm^?2 at a peak potential of 2 V. A long term stability of 24 h was achieved for a cell voltage of 2.2 V at a constant current density of 30 mAcm^?2 with only 10% of the initial current loss. This showcases the accumulative opportunity of dysprosium as a dopant in CuO nanoparticles for fabricating a highly effective and low-cost bi-functional electrocatalyst for overall water splitting.     

Hydrogen generation under sunlight by self ordered TiO2 nanotube arrays

Highly ordered TiO₂ nanotube arrays generate a considerable interest for hydrogen generation by an electrochemical photocell, since ordered architecture of nanotube arrays provides a unidirectional electric channel for electron's transport. Here, we report the hydrogen generation by highly ordered TiO₂ nanotube arrays under actual sunlight in KOH electrolyte. The two-electrode electrochemical cell included an adjustable anode compartment capable of tracing the trajectory of the sun and a set of alkaline batteries connected with a rheostat for application of external bias. The results showed that the photocurrent responses of nanotube arrays match well with the intensity of solar irradiance on a clear summer day. Addition of ethylene glycol into KOH electrolyte as a hole scavenger enhanced the rate of hydrogen generation. A maximum photocurrent density of 31 mA/cm² was observed at 13:30 h, by focusing the sunlight with an intensity of 113 mW/cm² on the surface of the TiO₂ nanotube arrays in 1 M KOH electrolyte with 10 vol% ethylene glycol under an applied bias of 0.5 V. The observed hydrogen generation rate was 4.4 mL/h cm² under the focalized solar irradiance with an intensity between 104 mW/cm² and 115 mW/cm² from 10:00 to 14:20 h.