This study reports the systematic design of two-dimensional reduced graphene oxide (rGO) integrated with onedimensional TiO2 nanorod arrays (TNR) on fluorine-doped tin oxide substrates. The architecture was engineered through controlled layer-by-layer deposition across varying spin-coating cycles (2, 5, 10, and 15) to enhance photoelectrochemical (PEC) performance. The rGO nanosheets were synthesized via the exfoliation and reduction of graphite oxide, while TNR were grown via a hydrothermal method. The progressive incorporation of rGO nanosheets into the TNR framework was comprehensively examined through morphological, crystallographic, optical, and surface-chemical analyses. The resulting rGO/TNR heterostructures exhibited significantly enhanced visible-light absorption and pronounced bandgap narrowing, attributable to the conductive carbon network and strengthened electronic coupling at the TiO2-rGO interface. Among the series of synthesized heterostructures, the rGO/TNR-5 architecture delivered the most substantial enhancement in PEC activity, achieving a 3.55-fold increase in photocurrent density (0.71 mA cm-2), a 4.33-fold improvement in applied-bias photon-to-current efficiency (0.143% at 0.92 V vs. reversible hydrogen electrode), and a 2.7-fold rise in incident photon-to-current efficiency at 365 nm relative to pristine TNR. Electrochemical impedance spectroscopy revealed a substantial decrease in charge-transfer resistance from 13,378 to 5950 Omega (approximate to 55.5% reduction), demonstrating enhanced interfacial carrier transport. The optimized heterostructure also exhibited excellent operational stability, retaining 98.3% of its photocurrent density over 3600 s. These findings highlight the synergistic role of rGO nanosheets in regulating charge separation and transport within TiO2-based architectures. The findings also demonstrate that tuning the number of rGO deposition cycles offers a simple approach to enhance the charge transfer and PEC response of TiO2 nanorod photoanodes.
Thermal adaptation and mitigation measures have been actively undertaken owing to warming climates, focusing on human-centered designs. Because clothing affects human energy balance namely thermal comfort, a suitable choice of clothing can be thermal adaptation. Similar to typical urban mitigations, two passive cooling techniques, which are ventilation and solar reflection were applied to a conventional garment. Accordingly, four types of garments (non-reflective loose-fitting, non-reflective tight-fitting, solar-reflective loose-fitting, and solar-reflective tight-fitting) were prepared and investigated by participants in terms of physical thermal load and subjective perceptions. Field measurements during walking were conducted in summer outdoors. Overall human thermal loads for clothed participants were smaller than undressed condition, indicating wearing clothing fundamentally acts as a buffer against environments suggesting comfort. Because the main heat-gain mechanism outdoors is irradiation, significant difference was observed in radiative heat gain between reflective loose and non-reflective loose, as well as reflective tight and non-reflective tight wearers. Despite the main cooling mechanism is convective heat loss, no significant difference in convective heat loss between loose and tight fitting garments were observed. Observed relationships among thermal sensation, thermal comfort, and human thermal load further suggest the validity of the experiments. Ideally, garments with both reflective and ventilation can improve thermal exposure significantly compared with the conventional garment. Our small scheme for heat adaptation in summer outdoor was confirmed in human energy balance; however, it did not work satisfactorily in perceptions, and thus more effective measures accompanying with detailed understanding of clothing effects are expected even under varying climate conditions.
Consider that there are $k\le n$ agents in a simple, connected, and undirected graph $G=(V,E)$ with $n$ nodes and $m$ edges. The goal of the dispersion problem is to move these $k$ agents to mutually distinct nodes. Agents can communicate only when they are at the same node, and no other communication means, such as whiteboards, are available. We assume that the agents operate synchronously. We consider two scenarios: when all agents are initially located at a single node (rooted setting) and when they are initially distributed over one or more nodes (general setting). Kshemkalyani and Sharma presented a dispersion algorithm for the general setting, which uses $O(m_k)$ time and $\log(k + \Delta)$ bits of memory per agent [OPODIS 2021], where $m_k$ is the maximum number of edges in any induced subgraph of $G$ with $k$ nodes, and $\Delta$ is the maximum degree of $G$. This algorithm is currently the fastest in the literature, as no $o(m_k)$-time algorithm has been discovered, even for the rooted setting. In this paper, we present significantly faster algorithms for both the rooted and the general settings. First, we present an algorithm for the rooted setting that solves the dispersion problem in $O(k\log \min(k,\Delta))=O(k\log k)$ time using $O(\log (k+\Delta))$ bits of memory per agent. Next, we propose an algorithm for the general setting that achieves dispersion in $O(k \log k \cdot \log \min(k,\Delta))=O(k \log^2 k)$ time using $O(\log (k+\Delta))$ bits. Finally, for the rooted setting, we give a time-optimal (i.e.,~$O(k)$-time) algorithm with $O(\Delta+\log k)$ bits of space per agent. All algorithms presented in this paper work only in the synchronous setting, while several algorithms in the literature, including the one given by Kshemkalyani and Sharma at OPODIS 2021, work in the asynchronous setting.
Microalgae present a unique, dual-purpose platform for addressing two of the most urgent global challenges: sustainable energy and nutritional security. With rapid growth, high lipid content, and minimal land and water requirements, microalgae offer a scalable and sustainable source for both biodiesel and omega-3. This review is the first to provide a comprehensive analysis of the entire microalgae production chain, from cultivation to downstream conversion, focused specifically on biodiesel and omega-3 pathways. A structured literature review was conducted across Elsevier, Wiley, and Springer (2016-2024), using predefined inclusion/exclusion criteria. Risk of bias was assessed based on study design, data transparency, and measurement methods. Key findings reveal that raceway ponds and photobioreactors offer the best trade-off between scalability and productivity. Supercritical CO2 and microwave-assisted extraction techniques outperform conventional solvent methods in enhancing both biodiesel yield and omega-3 quality. Stress-induced nutrient limitation strategies (e.g., nitrogen depletion) consistently boosted lipid accumulation without genetic modification. Integrating cultivation with municipal or industrial wastewater reduced operational costs while contributing to carbon mitigation and nutrient recycling. Despite economic and scale-up barriers, such as high photobioreactor capital costs and light penetration inefficiencies, recent innovations including hybrid cultivation systems, adaptive evolution, and co-product valorization demonstrate strong potential to overcome these limitations. The simultaneous production of biodiesel and omega-3 from a single microalgae biomass stream also aligns directly with multiple Sustainable Development Goals (SDGs). The insights herein offer a decision-support foundation for advancing these dual-value lipid streams from microalgae toward scalable, policy-aligned, and market-responsive implementation in the global bioeconomy.
Heteroatom co-doping of graphene-based materials has become an effective and powerful approach to develop advanced two-dimensional (2D) layered electrodes by engineering the electronic structure, defect chemistry, and surface functionality for electrochemical energy storage and conversion. Compared with single-atom doping, codoping enables synergistic modulation of charge redistribution, adsorption energetics, and ion transport behavior through complementary electronic and structural effects. Co-doping enables enhanced ion adsorption, charge transfer, and catalytic activity by introducing specific electronic and structural modifications that increase electrical conductivity, generate numerous active sites, and improve surface wettability. This review article systematically outlines the advantages of co-doped 2D graphene-based materials, and summarizes the synthesis techniques for nitrogen-sulfur (N,S), boron-nitrogen (B,N), nitrogen-phosphorus (N,P), and nitrogen-fluorine (N, F) co-doped 2D graphene-based materials, covering high-temperature annealing, thermal heating, hydrothermal, solvothermal, and liquid-phase methods for dual-heteroatom insertion in the carbon skeleton of these materials. The effectiveness of co-doped 2D graphene-based composite electrodes has been demonstrated in supercapacitors, batteries, fuel cells, solar cells, and water-splitting applications, highlighting the significance of synergistic heteroatom interactions for improving electrochemical performance. In addition to comparisons between single-doped and co-doped 2D graphene-based materials, analytical insights into electron/ion transport, adsorption energy optimization, and structural stability are discussed. The article provides an outlook for further research, highlighting potential uses and new developments in co-doped graphene-based 2D materials for energy applications. Important issues like scalable synthesis, reproducibility, and long-term cycling stability are also addressed, with suggestions for the systematic design of next-generation graphene-based materials and devices.
