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Abstract Green energy generation is an indispensable task to concurrently resolve fossil fuel depletion and environmental issues to align with the global goals of achieving carbon neutrality. Photocatalysis, a process that transforms solar energy into clean fuels through a photocatalyst, represents a felicitous direction toward sustainability. Eco‐rich metal‐free graphitic carbon nitride (g‐C3N4) is profiled as an attractive photocatalyst due to its fascinating properties, including excellent chemical and thermal stability, moderate band gap, visible light‐active nature, and ease of fabrication. Nonetheless, the shortcomings of g‐C3N4 include fast charge recombination and limited surface‐active sites, which adversely affect photocatalytic reactions. Among the modification strategies, point‐to‐face contact engineering of 2D g‐C3N4 with 0D nanomaterials represents an innovative and promising synergy owing to several intriguing attributes such as the high specific surface area, short effective charge‐transfer pathways, and quantum confinement effects. This review introduces recent advances achieved in experimental and computational studies on the interfacial design of 0D nanostructures on 2D g‐C3N4 in the construction of point‐to‐face heterojunction interfaces. Notably, 0D materials such as metals, metal oxides, metal sulfides, metal selenides, metal phosphides, and nonmetals on g‐C3N4 with different charge‐transfer mechanisms are systematically discussed along with controllable synthesis strategies. The applications of 0D/2D g‐C3N4‐based photocatalysts are focused on solar‐to‐energy conversion via the hydrogen evolution reaction, the CO2 reduction reaction, and the N2 reduction reaction to evaluate the photocatalyst activity and elucidate reaction pathways. Finally, future perspectives for developing high‐efficiency 0D/2D photocatalysts are proposed to explore potential emerging carbon nitride allotropes, large‐scale production, machine learning integration, and multidisciplinary advances for technological breakthroughs.

IntroductionThe population is heterogeneous with varying levels of healthcare needs. Clustering individuals into health segments with more homogeneous healthcare needs allows for better understanding and monitoring of health profiles in the population, which can support data-driven resource allocation.MethodsUsing the developed criteria, data from several of Singapore's national administrative datasets were used to classify individuals into the various health segments. Cross-sectional analysis of healthcare utilization charges was conducted. Validation was done for the framework's prognostic ability of clinically relevant outcomes measured in the following year.ResultsThe framework is comprised of twelve segments classed within four broad groups. The segments comprising individuals with cancer, with transitional care needs, and in the last year of their lives had the highest mean per resident healthcare charges. The segments comprising adults and seniors with complex chronic conditions and with transitional care needs had the highest percentage of individuals historically diagnosed with obesity. The framework was able to distinguish varying tiers of healthcare utilization charges and relative risk of death in the following year.DiscussionThe framework was developed using a hybrid approach, with expert input and comprehensive national data that extended beyond the usual hospital patient population. The framework can be directly applied for use in program or policy design, evaluation, and cost-effectiveness analyses.ConclusionThe HealthSCOPES framework was developed to segment the entire population in Singapore with similar healthcare needs.