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• Exploring PLS in energy research, revealing applications and addressing challenges. • Tackling limitations in PLS implementation, considering confounding variables, sample sizes, and integration. • Beyond replication issues, focusing on reliability, multi-physics phenomena, and optimized designs. • Balancing thermal, fluid, and electrical factors, enhancing PLS performance across energy applications. • Innovative fabrication techniques, scaling up PLS production for efficient, cost-effective energy solutions. Lattice structures, with their exceptional characteristics such as high specific strength and stiffness, thermal insulation, and biocompatibility, find a wide range of applications including bio-medical, thermal, automobile and aerospace industry. This study explores their potential for energy research, provides an overview of Periodic lattice structure (PLS) design and fabrication, and classifies them based on their energy function. It aims to provide insights into the potential applications, advancements, challenges, and future directions related to PLS implementation in energy research. The study categorized the recent advances and challenges of using PLS in energy conversion, storage, and transport applications and examines the challenges and limitations associated with them. The challenges and limitations include problems related to study design, reproducibility, sample sizes, multi-physics phenomena, integration with other energy storage components, interdisciplinary research, manufacturing accuracy, durability, scalability, and economic feasibility. Future research directions are suggested to address these challenges and opportunities, such as evaluating PLS performance on a broader scale, developing accurate modeling techniques, investigating underlying mechanisms, utilizing multi-physics modeling tools, examining long-term performance, exploring practical applications, and exploring alternative fabrication methods. [ABSTRACT FROM AUTHOR]

Machine learning provides a probabilistic framework for metabolic pathway inference from genomic sequence information at different levels of complexity and completion. However, several challenges, including pathway features engineering, multiple mapping of enzymatic reactions, and emergent or distributed metabolism within populations or communities of cells, can limit prediction performance. In this article, we present triUMPF (triple non-negative matrix factorization [NMF] with community detection for metabolic pathway inference), which combines three stages of NMF to capture myriad relationships between enzymes and pathways within a graph network. This is followed by community detection to extract a higher-order structure based on the clustering of vertices that share similar statistical properties. We evaluated triUMPF performance by using experimental datasets manifesting diverse multi-label properties, including Tier 1 genomes from the BioCyc collection of organismal Pathway/Genome Databases and low complexity microbial communities. Resulting performance metrics equaled or exceeded other prediction methods on organismal genomes with improved precision on multi-organismal datasets. [ABSTRACT FROM AUTHOR]

The miniaturization of electronic devices has facilitated increasing interest in new applications of wireless communication. In this paper, a new miniature microstrip fed boomerang-shaped patch antenna has been proposed and designed for a wireless sensor network (WSN) application. In this design, the proposed antenna possesses a wide bandwidth by loading of a boomerang-shaped patch; with a 50 Ω microstrip feed line and a partial ground plane. A one-step staircase slot is embedded in the ground plane to enhance the impedance matching over a wide frequency range. The antenna occupies a small size of 10 × 12 mm2, or 1.2 cm2. The simulated results are verified with measured results. The measured result shows that the achievable bandwidth of 69% (8.48–17.45 GHz). The antenna possesses stable radiation patterns and acceptable gain. The proposed low profile antenna is suitable to integrate with sensors for wireless sensor network in X-band and Ku band applications. [ABSTRACT FROM AUTHOR]

Introducing ZIF-8 into the PES-cSMM membranes played a pivotal role in the development of proton-conducting pathways and an effective methanol barrier. We employed dry-wet phase inversion techniques to fabricate PES-cSMM, finding that a 3 wt% cSMM content yielded optimal results. The resulting PES-cSMM exhibits impressive performance, with a 38% higher selectivity and a 95% greater methanol barrier compared to Nafion® 117. The imidazole-N-H linker in the terminal PES-cSMM/ZIF-8 promotes proton transport through a hydrogen bond chain, while the hydrophobic backbone acts as an effective methanol filter. As a result, PES-cSMM/ZIF-8 boasts a 13-fold higher water uptake than Nafion® 117 and achieves a 99% improvement in methanol sieving performance, a highly promising breakthrough for DMFC systems. Proton conductivity for the PES-cSMM/ZIF-8 immersion membrane reaches 19.5 × 10-3 Scm-1, comparable to Nafion® 117, which is 20.4 × 10-3 Scm-1. The structural flexibility of ZIF-8 within PES-cSMM facilitates efficient proton conduction, while the ZIF-8 cage acts as a robust methanol barrier. Computational analysis revealed covalent bonding within the PES-cSMM system. We characterized the chemical interactions in PES-cSMM/ZIF-8 using topology analysis, specifically the Atom in Molecules/Non-covalent analysis (AIM/NCI) technique. [Display omitted] • PES-cSMM made via dry-wet phase inversion; ZIF-8 added in-situ by growth immersion technique. • PES-cSMM/ZIF-8 shows promise in reducing methanol crossover, with good selectivity, stability, and proton conductivity for DMFC. • Proton transport occurs through non-covalent interactions with exposed sulfonic acid groups on the cSMMs within the membrane. • Computational findings suggest ZIF-8 interacts with methanol mainly via van der Waals forces. [ABSTRACT FROM AUTHOR]