Platinum (Pt) persists as an exceptionally prevalent catalyst material in the proton exchange membrane fuel cells (PEMFCs), especially for cathodic oxygen reduction kinetics. However, the high cost and limited supply of Pt are driving interest in bio-based catalyst systems. In this review, three families of such catalysts, which include enzymes, metalloporphyrins, and biomass-derived carbon, are evaluated for their performance under PEMFC-relevant conditions. Rather than evaluating these as potential alternatives, this review focuses on their four-electron route driving capabilities, impurity sensitivity, and stability. Contemporary reports indicate that laccase-based systems, Fe/Co porphyrinic carbons, and microbial-templated Pd and Pt catalysts can attain activity levels comparable to Pt/C when immobilization and electronic coupling are effectively regulated. The primary concerns lie in durability and poisoning, with sulfur species and CO being detrimental to various biological templates. Furthermore, challenges persist regarding scalability and reproducibility because, unlike the conventional heterogeneous catalysts used in PEMFCs, bio-catalysts are contingent upon parameters including ligand chemistry, protein structural arrangement, and microbial growth. This makes the production process and maintenance of batch uniformity laborious. Although recent advancements have mitigated performance limitations, mechanistic understanding, operational longevity, and manufacturing scalability remain critical considerations. Overcoming these challenges will establish biocatalysts as a viable alternative to traditional precious-metal catalysts in PEMFCs.
Multi-walled carbon nanotubes (MWCNTs) enable efficient photothermal coatings for thermal management applications due to their broadband near-infrared absorption and high thermal conductivity. This study optimizes MWCNT-polymer formulations using random forest machine learning (ML) to maximize photothermal conversion efficiency (η), targeting inputs like MWCNT concentration (1–10 mass% ), polymer type (polystyrene, polyethylene, and polyurethane), and coating thickness (100–500 nm) prepared via dip, spray, or spin coating on glass substrates. A dataset of 500 + experimental points (features: composition, processing parameters; target: η and steady-state temperature rise) underwent preprocessing (normalization and categorical encoding) and fivefold cross-validation. The random forest model achieved R2 = 0.93 (validation), outperforming baselines by predicting optimal formulations (e.g., 5 mass% MWCNT in polyurethane yielding η = 85
The widespread adoption of lithium-ion batteries (LIBs) in electric vehicles, portable electronics, and renewable energy systems has intensified the demand for effective thermal management strategies to ensure safety, performance, and longevity. Among emerging solutions, phase change materials (PCMs) have attracted significant interest for their passive thermal regulation capabilities, particularly their high latent heat and isothermal behavior. However, the research landscape is fragmented, with varied materials, configurations, and integration strategies explored across the literature. This review aims to provide a comprehensive synthesis of recent advances in PCM-based battery thermal management systems (BTMS), highlighting their thermal performance, structural innovations, and hybrid configurations with active cooling methods. Drawing on experimental, numerical, and theoretical studies, the review identifies key design parameters affecting efficiency, including PCM composition, nano-enhancements, encapsulation techniques, and system architecture. The review examines emerging research trends such as the use of machine learning for BTMS optimization, development of multifunctional PCMs with flame-retardant and structural properties, and cost-benefit analyses supporting commercial viability. Despite notable progress, challenges remain in material stability, scalability, and integration complexity. This review concludes by outlining future research directions, including the standardization of performance metrics, exploration of bio-based PCMs, and adaptive control strategies.
As climate change, rapid urbanization, and rising global demand continue to strain freshwater resources, the pursuit of sustainable and decentralized desalination solutions has become increasingly urgent. Solar‐powered water purification, particularly via passive systems, offers an environmentally sound and energy‐efficient pathway to address this challenge. Among the different solar still configurations, spherical designs (SPSS) stand out as a noteworthy advancement, based on their unique geometry that ensures uniform solar energy absorption, improved thermal efficiency, and a compact form suitable for off‐grid and remote applications.This review delivers an in‐depth and up‐to‐date examination of advancements in SPSS technology, focusing on recent integrations such as wick‐based evaporation systems, nanoparticle‐infused phase change materials (PCMs), reflective surfaces, internal baffles, and rotational mechanisms. Collectively, these improvements have led to significant enhancements in distillate output, with some designs achieving performance increases of up to 259% relative to traditional setups. By critically examining experimental research, modeling approaches, and techno‐economic evaluations, this review outlines the current landscape, identifies key limitations, and explores emerging strategies to enhance efficient and cost‐effective SPSS systems.The analysis underscores the role of SPSS as a promising and scalable method for generating clean water, particularly suited to sun‐rich regions facing resource constraints.
Dual-specificity phosphatases (DUSPs) require two conserved motifs, the HCX₅R nucleophilic loop and a WPD/FPD-type general-acid loop, to support cysteine-dependent dephosphorylation. Although annotated as a DUSP, the catalytic competence of DUSP15 has remained ambiguous, with only weak activity reported against artificial substrates and paradoxical roles in sustaining ERK and Jak1-STAT3 signalling. Here, sequence analysis, crystallographic inspection, structural modelling, evolutionary profiling, interaction-network inference, and molecular dynamics (MD) simulations are integrated to reassess the functional properties of DUSP15. Motif analysis identifies two defining deviations: a phenylalanine immediately following the catalytic cysteine within a divergent HCFAGISR loop, and complete absence of a WPD/FPD-type general-acid loop. Structural examination of a DUSP15 crystal fragment, together with AlphaFold predictions, shows that the inserted phenylalanine projects into and sterically occludes the active-site cleft, in contrast to the open catalytic pocket of the active phosphatase DUSP7. Comparative analysis of 11 mammalian orthologs reveals absolute conservation of both anomalies, indicating long-standing selective maintenance of a catalytically divergent architecture. 100-ns all-atom MD simulations reveal a globally stable and compact fold with a conformationally rigid, tightly packed, and selectively dehydrated catalytic motif, lacking the flexibility and solvent accessibility typically required for productive cysteine-based catalysis. Comparative MD simulations performed under identical conditions further distinguish DUSP15 from the catalytically competent phosphatase DUSP7. Interaction-network analysis places DUSP15 within phosphatase-, transcriptional-, and metabolism-associated modules, consistent with scaffold-like regulatory roles. Together, these convergent structural, evolutionary, and dynamical features support a model in which DUSP15 functions predominantly as a non-catalytic adaptor, providing a mechanistic framework for its non-canonical regulation of ERK and Jak1-STAT3 signalling and its tumour-selective expression in chromophobe renal cell carcinoma.
