Natural fibers and zinc hydroxystannate 3D microspheres based composite paper sheets for modern bendable energy storage application

For modern high-tech flexible energy storage devices, it becomes important to synthesize micro-/nanostructures as per the required shape and morphology with superior physical and electro-active characteristics. This work shares the fabrication and characterization of ZnSn(OH)₆ (Zinc hydroxystannate [ZHS]) prepared by facile microwave-assisted technique and furthermore converted into flexible sheets by employing lignocelluloses (LC) known as natural fibers, collected from Carica papaya leaf petiole as a substrate to provide the flexible matrix. X-ray diffraction measurements confirm the successful crystalline structure of ZHS. Scanning electron microscopy and transmission electron microscopy showed the solid spherical structure of ZHS microspheres. Fourier transform infrared spectrometry and Raman spectroscopy confirmed the composite formation of ZHS and LC-based composite sheets (ZHS/LC sheets). Electrochemical measurements that is, cyclic voltammetry (CV), Galvanostatic charge/discharge, and electrochemical impedance (EIS) spectroscopy revealed the electroactive behavior of ZHS/LC paper sheets as working electrode for energy storage applications. CV measurements revealed the specific capacitance of 100 F/g and EIS measurements confirmed the decrease in the resistance of LC fiber after the growth of ZHS microspheres. Presented flexible ZHS based paper sheets will be highly feasible for the modern bendable/flexible/disposable energy storage applications.     

Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

Forecasting on success or failure of software has become an interesting and, in fact, an essential task in the software development industry. In order to explore the latest data on successes and failures, this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework? What human factors contribute to success or failure of a software? What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work? In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors, misinterpretation, and miscommunication of requirements and decision-making processes play their roles in software success forecasting. We discussed a potential relationship between forecasting of software success or failure and the development processes. We noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study, and they were more likely to rate software success forecasting linking to the development processes. Our analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success rate. The results of this empirical study also validated that requirements’ misinterpretation and miscommunication were the main causes behind software systems’ failure. It has been seen that reliable, relevant, and trustworthy sources of information help in decision-making to predict software systems’ success in the software industry. This empirical study highlights a need for other software practitioners to avoid such bias while working on software projects. Future investigation can be performed to identify the other human factors that may impact software systems’ success.     

Sol-Gel-Derived Ordered Mesoporous High Entropy Spinel Ferrites and Assessment of Their Photoelectrochemical and Electrocatalytic Water Splitting Performance

The novel material class of high entropy oxides with their unique and unexpected physicochemical properties is a candidate for energy applications. Herein, it is reported for the first time about the physico- and (photo-) electrochemical properties of ordered mesoporous (CoNiCuZnMg)Fe₂O₄ thin films synthesized by a soft-templating and dip-coating approach. The A-site high entropy ferrites (HEF) are composed of periodically ordered mesopores building a highly accessible inorganic nanoarchitecture with large specific surface areas. The mesoporous spinel HEF thin films are found to be phase-pure and crack-free on the meso- and macroscale. The formation of the spinel structure hosting six distinct cations is verified by X-ray-based characterization techniques. Photoelectron spectroscopy gives insight into the chemical state of the implemented transition metals supporting the structural characterization data. Applied as photoanode for photoelectrochemical water splitting, the HEFs are photostable over several hours but show only low photoconductivity owing to fast surface recombination, as evidenced by intensity-modulated photocurrent spectroscopy. When applied as oxygen evolution reaction electrocatalyst, the HEF thin films possess overpotentials of 420 mV at 10 mA cm⁻² in 1 m KOH. The results imply that the increase of the compositional disorder enhances the electronic transport properties, which are beneficial for both energy applications.     

A reinforcement learning approach for transaction scheduling in a shuttle-based storage and retrieval system

With recent Industry 4.0 developments, companies tend to automate their industries. Warehousing companies also take part in this trend. A shuttle-based storage and retrieval system (SBS/RS) is an automated storage and retrieval system technology experiencing recent drastic market growth. This technology is mostly utilized in large distribution centers processing mini-loads. With the recent increase in e-commerce practices, fast delivery requirements with low volume orders have increased. SBS/RS provides ultrahigh-speed load handling due to having an excess amount of shuttles in the system. However, not only the physical design of an automated warehousing technology but also the design of operational system policies would help with fast handling targets. In this work, in an effort to increase the performance of an SBS/RS, we apply a machine learning (ML) (i.e., Q-learning) approach on a newly proposed tier-to-tier SBS/RS design, redesigned from a traditional tier-captive SBS/RS. The novelty of this paper is twofold: First, we propose a novel SBS/RS design where shuttles can travel between tiers in the system; second, due to the complexity of operation of shuttles in that newly proposed design, we implement an ML-based algorithm for transaction selection in that system. The ML-based solution is compared with traditional scheduling approaches: first-in-first-out and shortest process time (i.e., travel) scheduling rules. The results indicate that in most cases, the Q-learning approach performs better than the two static scheduling approaches.     

Passivated Emitter and Rear Totally Diffused: PERT Solar Cell-An Overview

Silicon - An overview of the Passivated Emitter and Rear Totally Diffused (PERT) solar cell is presented, which is a member of Passivated Emitter and Rear Contact (PERC) family. Due to its...     

Geotechnical properties of problematic expansive subgrade stabilized with guar gum biopolymer

Clean Technologies and Environmental Policy - This article presents a comprehensive study on the geotechnical behavior of problematic expansive subgrade stabilized by guar gum (GG) biopolymer. In...     

Elimination of solidification shrinkage defects in the casting of aluminum alloy

Journal of Mechanical Science and Technology - In this study, the analysis is carried out to optimize in-gate position and size of riser for casting mold. The baseline size of riser for the casting...     

Cactus-Shaped Frequency Reconfigurable Antenna for Sub 10 GHz Wireless Applications

This paper presents, a novel cactus shaped frequency reconfigurable antenna for sub 10 GHz wireless applications. PIN diode is utilized as an electrical switch to achieve reconfigurability, enabling operation in four different frequency ranges. In the switch ON state mode, the antenna supports 2177–3431 and 6301–8467 MHz ranges. Alternatively, the antenna resonates within 2329–3431 and 4951–6718 MHz while in the OFF state mode. Radiation efficiency values, ranging from 68% to 84%, and gain values, ranging from 1.6 to 4 dB, in the operating frequency bands. the proposed antenna satisfy the practical requirements and expectations. The overall planner dimensions of the proposed antenna model is 40 × 21 mm². Moreover, the measurement results from the prototype support the simulation results. Based on the frequency ranges supported by the antenna, it can be used for multiple wireless standards and services, including Worldwide interoperability and Microwave Access (WiMAX), Wireless Fidelity (Wi-Fi), Bluetooth, Long Term Evolution (LTE) and satellite communications. This increases its applicability for use in mobile terminals.     

Versatile Magnetic Mesoporous Carbon Derived Nano-Adsorbent for Synchronized Toxic Metal Removal and Bacterial Disinfection from Water Matrices

Contamination of water resources by toxic metals and opportunistic pathogens remains a serious challenge. The development of nano-adsorbents with desired features to tackle this problem is a continuously evolving field. Here, magnetic mesoporous carbon nanospheres grafted by antimicrobial polyhexamethylene biguanidine (PHMB) are reported. Detailed mechanistic investigations reveal that the electrostatic stabilizer modified magnetic nanocore interfaced mesoporous shell can be programmatically regulated to tune the size and related morphological properties. The core–shell nano-adsorbent shows tailorable shell thickness (≈20–55 nm), high surface area (363.47 m² g⁻¹), pore volume (0.426 cm³ g⁻¹), radially gradient pores (11.26 nm), and abundant biguanidine functionality. Importantly, the nano-adsorbent has high adsorption capacity for toxic thallium (Tl(I) ions (≈559 mg g⁻¹), excellent disinfection against Staphylococcus aureus and Escherichia coli (>99.99% at 2 and 2.5 µg mL⁻¹), ultrafast disinfection kinetics rate (>99.99% within ≈4 min), and remarkable regeneration capability when exposed to polluted water matrices. The Tl(I) removal is attributed to surface complexation and physical adsorption owing to open ended mesopores, while disinfection relies on contact of terminal biguanidines with phospholipid head groups of membrane. The significance of this work lies in bringing up effective synchronic water purification technology to combat pathogenic microorganisms and toxic metal.     

Phthalonitrile-glass fabric composites

Phthalonitrile polymers, under development at the Naval Research Laboratory, offer promise as high temperature, high performance composite matrix materials. A fully cured resin shows outstanding thermal stability with no evidence of a glass transition temperature or T_g up to 450°C, good mechanical properties, and is easily processed into void-free components. Phthalonitrile/glass fabric composite panels have been successfully fabricated by conventional consolidation of prepregged glass and by a more recently developed simplified process, resin infusion molding. Both processes can be used to produce panels with comparable mechanical properties. More important, flammability performance of these composites, evaluated in terms of specific optical density, combustion gases, heat release, and ignitability, excels over other state-of-the-art polymer/glass composites. This finding is significant given that overcoming flammability obstacles has been the main limiting factor for use of composites in marine applications.