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Solvent-Mediated Dewetting Principles for Cell-Sized Liposome Formation
No full textReconstitution of synthetic cells holds potential to advance synthetic biology, biomanufacturing, and therapeutics. Microfluidic generation of cell-sized liposomes via double emulsion templating offers precise control over composition and formation process, yet the principles underlying solvent-mediated dewetting remain poorly understood. Using a solvent combination of hexanol and paraffin oil, we demonstrate that solvent-mediated dewetting liposome generation entails both solvent removal and the application of mechanical stimuli. Solvent removal suffices to induce the morphological transition from double emulsions to partially dewetted liposomes exhibiting low and high budding angles of the residual oil pockets. This transition is driven by relaxation of monolayer and membrane tensions, arising from the increased lipid packing density at the liposome interfaces during solvent depletion. While dewetting kinetics and intermediate stages are governed by solvent removal rate, complete dewetting is not spontaneous. Using optical tweezers, we identify tethering between the liposome and oil pocket and characterize the mechanical force required for liposome detachment. By integrating these principles, a predictive, high-throughput approach for generating biocompatible, surfactant-free liposomes is provided. These findings establish a mechanistic framework for liposome dewetting and, through similarities to lipid droplet morphogenesis, offer a protocell platform that could further the understanding of biological budding processes.</p
Cybersecurity for 5G-Enabled IoT Ecosystems:Introduction, Challenges, and Solutions
No full text5G and Internet of Things complement each other in contributing towards the advancements of various relevant regimes like healthcare, smart cities, and industrial automation. This combination also brings cybersecurity as potential challenge due to abrupt surge in network devices and components. This chapter addresses various concerns like the significant challenges in 5G-enabled IoT systems, gauging effectiveness of existing solution and the next-generation solutions for the protection of 5G-enabled IOT in future. The study evaluates advanced solutions such as AI-based anomaly detection, privacy-preserving analytics etc. Backed by simulations and real-world case studies, the findings highlight the practical potential of these approaches to enhance IoT security and resilience. The following chapter is expected to provide the significant mentoring to the different stakeholders like young researchers, key industry personals, law administrators for creating the awareness about various steps towards designing and maintaining 5G-enabled IoT ecosystems with security as well as scalability.</p
Liquid–Liquid Extraction of Acetic Acid with 2-Methyltetrahydrofuran:Experiments, Process Modeling, and Economics
No full textAcetic acid production from renewable processes such as biomass hydrolysis and electrochemical reduction of CO2 exhibits low concentrations, which make downstream separation challenging. We measured the vapor–liquid equilibria of the binary systems acetic acid + 2-methyltetrahydrofuran (2-MTHF), methyl-t-butyl ether (MTBE) + acetic acid, and the ternary liquid–liquid equilibria of the system 2-MTHF + AA + water, fitted the data to the UNIQUAC-HOC and NRTL models, designed a hybrid extraction-distillation process for acetic acid separation with 2-MTHF, and evaluated its economics and compared with that of three other commonly used solvents (i.e., ethyl acetate, MTBE, and methyl propyl ketone). The lowest and highest costs of separation were observed for MTBE and MPK, while 2-MTHF and EA showed similar performance. The cost of separation increased exponentially as the feed concentration decreased, and renewable processes should aim for at least 5 wt % acetic acid in the feed to allow economically feasible separation.</p
Evaluation of non-destructive examination requirements and challenges for small modular reactors
No full textThis study evaluates the applicability of Non-Destructive Examination (NDE) methods to the BWRX-300, i-SMR, and Rolls-Royce SMR Small Modular Reactor (SMR) designs, as well as to Generation IV concepts: GTHTR300, IMSR 400, and 4S. The assessment considers plant design, structural materials, and manufacturing technologies to identify corresponding NDE requirements for both manufacturing and in-service inspections. The findings suggest that, for near-term deployable SMRs, existing inspection methods used in the conventional large-scale nuclear power plants remain applicable. However, the introduction of new materials, novel reactor designs, advanced manufacturing techniques, and the modular design, may require adaptations or development of new NDE approaches
Unsupported CoMoS catalysts for isoeugenol hydrodeoxygenation:optimisation of synthesis parameters for catalyst performance
No full textHydrodeoxygenation of isoeugenol as a model compound for lignocellulosic biomass-derived oils has been studied in this work. A series of unsupported cobalt-doped molybdenum oxide and sulfide catalysts were prepared via hydrothermal precipitation to systematically study the effect of catalyst preparation conditions on catalyst properties and catalytic performance. The effects of the preparation temperature, excess sulfur, and pH and their combinations were studied using a design of experiments approach. The catalysts were characterized with ICP-OES, N2 physisorption, XRD, XPS and SEM-EDS and screened for bio-oil model compound isoeugenol hydrodeoxygenation under relevant process conditions of 300 °C and 30 bar in a batch reactor. Co was observed as a sulfide, while molybdenum exhibited mixtures of the oxide and sulfide, with the former favored under preparation conditions with less sulfur. The catalyst performance testing revealed a higher activity and increased deoxygenation selectivity of the sulfide catalysts compared to those of the oxide catalysts. In addition to the chemical nature, the catalyst activity in the model reaction was increased by the high pore volume and surface area, which were promoted by a low pH at the start of the synthesis. The observed tendencies provide a basis for catalyst tailoring in hydrotreatment processes for biofuel and biochemical production from lignocellulosic biomass.</p
Novel Data-Driven Discrete Neurodynamics Schemes for Redundant Manipulator Control
No full textIt is very challenging to precisely control a redundant manipulator with an unknown model during the end-effector tracking task. A data-driven approach offers a promising solution for manipulator control under such conditions. In this article, two data-driven discrete neurodynamics (DDDN) schemes are proposed for redundant manipulator tracking control. First, utilizing discrete neurodynamics (DN) principles, the DDDN-1 scheme with an adaptive Jacobian matrix is developed. Subsequently, the DDDN-2 scheme is further presented, which eliminates the need for the Jacobian matrix inversion operation. Detailed theoretical analyses verify the effectiveness of DDDN-1 and DDDN-2 schemes. Additionally, detailed comparisons with existing schemes have been provided. Finally, simulative and physical experiments conducted using the UR5 manipulator validate the theoretical analyses, demonstrating the effectiveness and superiority of DDDN-1 and DDDN-2 schemes.</p
