Thermal energy systems (TES) are an essential part of industries that have evolved over time through the engagement of managers and researchers. The development of digital twin (DT) technology has enabled accurate prediction of their performance. The inherent limitations of complex thermal systems, such as noisy input data and occasional lack of measurement data or boundary conditions, have recently created opportunities to apply physics-based problem-solving alongside DT technology. This paper aims to systematically review the novel physics-informed neural network-digital twin (PINN-DT) methodology as a potential solution to these challenges, and to present a taxonomy for problem-solving. The outcome of this study provides valuable guidance in selecting PINN-DT technology in thermal energy system (TES) modeling. A review of the proposed loss functions demonstrates that their design is critical for achieving precise outcomes in this technology, effectively serving as the foundational core of PINN-DT. As a result, it is recommended that the construction of the loss function be fundamentally guided by two principal considerations: forecasting accuracy and compliance with physical principles, which serve as foundational pillars in the surrogate model design framework. A significant gap exists in applying this technology to industries that use discrete sampling for quality control. Implementing the PINN-DT framework could address this issue by determining optimal sampling intervals, thereby offering vital decision-making support. Moreover, the absence of exergy analysis in formulating the physical loss component of the loss function represents a significant research gap. Future studies should therefore incorporate the exergy concept into the design of the loss function.

Achieving both a low operating temperature for photovoltaic (PV) and a high heat collection temperature for photothermal (PT) conversion in full-spectrum solar energy utilization is challenging with traditional spectrum-splitting methods. Therefore, this study focuses on the full-spectrum solar utilization and proposes a novel multi-stage concentrating and spectrum-splitting coupling approach for complementary photovoltaic-thermophotovoltaic (PV-TPV) conversion. Multi-stage thermophysical models are developed based on thermodynamic analysis, Shockley-Queisser model coupling, and external quantum efficiency model coupling, incorporating cell combinations with different bandgaps and temperature coefficients, enabling performance analysis from idealized scenarios to realistic conditions. A single-stage spectrum splitting PV-TPV system is optimized as a baseline, and the impact of multi-stage spectrum coupling on system performance is investigated. Results show that low-bandgap cells with higher temperature coefficients can achieve superior performance at lower concentration ratios compared with high-bandgap cells at higher concentration ratios. Considering the practical external quantum efficiency (EQE) model, low-bandgap cells demonstrate additional advantages, achieving a maximum system efficiency of 41.82% at C₁ = 500 and C₂ = 300. The multi-stage spectrum-splitting design allows decoupling of the spectrum and concentration ratio, effectively reducing the system concentration ratio by more than 50% while maintaining high system performance. This not only facilitates device design and practical implementation but also enhances theoretical efficiency, demonstrating significant application potential. The study provides valuable insights for the development of full-spectrum PV-TPV conversion methods.

Aqueous zinc-ion batteries (AZIBs) have emerged as promising candidates for large-scale energy storage systems in the post-lithium era, owing to their inherent safety and cost-effectiveness. However, their practical implementation faces significant challenges, including chemical corrosion, uncontrolled dendrite formation, and hydrogen evolution reactions (HER). To address these limitations, an innovative “hydrophobic-zincophilic” Pd/g-C₃N₄ composite coating was developed for Zn anodes by atomic-layer-deposition (ALD). The g-C₃N₄ matrix serves as an ion flux regulator, while uniformly dispersed Pd nanoparticles function as zincophilic nucleation sites, enabling homogeneous Zn deposition. In situ optical characterization demonstrates the coating’s dual functionality: the hydrophobic component effectively minimizes water contact, while the zincophilic phase guides ordered Zn plating, jointly suppressing parasitic reactions. The modified Pd/g-C₃N₄@Zn anode achieves exceptional cycling stability (> 2500 h) and maintains a remarkable Coulombic efficiency of 99.56% over 5000 cycles at 2 A/g, representing a significant advancement in AZIB anode engineering. This work provides a generalizable interfacial design strategy for developing high-performance AZIB systems.

Li metal batteries (LMBs), owing to their high theoretical specific energy, are considered a crucial development direction for future high-energy-density battery systems. However, the high reactivity of the Li metal anode leads to extreme electrochemical and chemical instability at the interface with the electrolyte. This instability triggers detrimental effects, including Li dendrite growth, repeated cracking and reformation of the solid electrolyte interphase (SEI), and continuous irreversible consumption of both active Li and electrolyte. Therefore, designing high-performance electrolytes to precisely regulate interfacial chemistry has become one of the core strategies for advancing the practical application of LMBs. Significant progress has recently been made in stabilizing the Li metal–electrolyte interface (Li-electrolyte interface) through strategies including additives, weakly solvating electrolytes (WSEs), high-concentration/localized high-concentration electrolytes (HCEs/LHCEs), and novel molecular design. Nevertheless, these advanced strategies and their corresponding stabilization mechanisms have not yet been systematically organized. To address this gap, this review focuses on four core electrolyte design strategies and systematically summarizes their mechanisms for stabilizing the Li-electrolyte interface. Building on this foundation, it discusses the inherent limitations of individual electrolyte design strategies. It then focuses on the potential of synergistic electrolyte design to achieve a more electrochemically stable Li-electrolyte interface. Finally, it proposes future research directions requiring key focus for existing electrolyte design strategies.

The interfacial stress between silicon bottom cell and perovskite top cell remains a critical challenge for flexible perovskite/silicon tandem solar cells, leading to interfacial delamination and device degradation. In this work, the effect of the thickness and pyramid size on mechanical properties of silicon wafers are investigated, demonstrating that thinner wafers and smaller pyramids significantly enhance the flexural strength of thin silicon wafers by mitigating stress concentration effects. Based on these findings, a synergistic optimization strategy is proposed that employs precise wet-etching control to fabricate small-sized, high-density, uniform pyramids on 55 μm silicon wafers for efficient and flexible perovskite/silicon tandem solar cells. By optimizing the texturing duration, this approach simultaneously enhances the minority carrier lifetime (τ) and achieves an excellent implied open-circuit voltage (iVoc). Furthermore, the uniform submicron-scale pyramid structure promotes high-quality perovskite film formation and improves interfacial contact properties. As a proof of concept, monolithic flexible perovskite/silicon tandem devices fabricated on such uniformly textured pyramids delivered a power conversion efficiency (PCE) of 30.04%. These devices promise for low-cost, lightweight and flexible photovoltaic applications.

Zinc-ion batteries (ZIBs) represent a promising class of post-lithium energy storage systems. However, their practical deployment is impeded by critical interfacial instabilities, such as uncontrolled growth of zinc dendrites, adverse parasitic interfacial reactions, and cathode material dissolution. Atomic layer deposition (ALD), renowned for its atomic-scale precision and exceptional conformality, offers a pivotal strategy to mitigate these challenges. This review provides a comprehensive analysis of ALD applications in ZIBs, with a central focus on a critical paradigm shift: from the use of simple passive physical barriers toward multifunctional coatings capable of actively regulating interfacial chemistry and ion transport. It elucidates the mechanisms through which ALD-derived coatings (e.g., Al₂O₃, ZnO, Fe₂O₃) regulate Zn²⁺ flux, suppress hydrogen evolution reactions (HERs), and induce preferential zinc deposition along specific crystallographic orientations (e.g., the Zn (002) plane) to inhibit dendrite formation. Furthermore, it covers ALD strategies for enhancing cathode structural stability against dissolution and collapse, as well as for functionalizing separators to achieve selective ion transport. Finally, it presents critical perspectives on overcoming the cost-scalability trade-off and deepening the mechanistic understanding of structure-property relationships, aiming to guide the rational design of durable and high-performance ZIBs. This paradigm shift represents a fundamental transition in interface design philosophy for high-performance ZIBs.

The Fe–N–C single-atom catalyst represents a promising candidate for promoting the oxygen reduction reaction (ORR), which is crucial for fuel cell applications; yet, identifying optimal modification strategies to enhance its activity and stability remains challenging. Herein, the modulation of Fe–N–C catalysts via in-plane heteroatom doping and axial coordination is systematically investigated using integrated density functional theory (DFT) and machine learning (ML) approaches. The analysis reveals that axial ligands have a more profound influence on ORR performance than in-plane dopants, primarily by modulating the Fe d_z2 orbital and weakening *OH adsorption. Through interpretable descriptors extracted from ML models, the key electronic and geometric properties governing catalyst behavior are identified, and several novel dual-modified candidates with enhanced activity relative to pristine Fe–N–C are subsequently predicted and validated by DFT calculations. This work provides a unified mechanistic and data-driven framework for accelerating the design of high-performance Fe–N–C ORR electrocatalysts.

Biomass-derived materials are emerging as powerful enablers for sustainable solid-state batteries (SSBs), offering structurally tunable, chemically versatile, and environmentally benign alternatives to conventional battery components. This review critically examines recent advances in the use of bio-derived carbons, polymers, and composites across key SSBs elements, including electrodes, solid electrolytes, binders, and separators. Biomass-derived carbons produced via pyrolysis, hydrothermal carbonization, and molten-salt methods provide hierarchical porosity and controllable graphitization, enabling efficient ion transport, catalytic activity, and mechanical buffering in electrode architectures. Biopolymers such as cellulose, lignin, and chitosan serve as functional matrices for solid polymer and gel electrolytes, enhancing ionic conductivity, interfacial stability, and mechanical integrity, while their intrinsic microstructures can also template low-tortuosity inorganic ceramic electrolytes. In addition, bio-based binders, separators, and electrolyte additives help address critical challenges, including dendrite growth, polysulfide shuttling, and interfacial degradation. Remaining barriers, such as feedstock variability, impurity control, multifunctional performance trade-offs, and scalable processing, are discussed alongside emerging opportunities enabled by artificial intelligence-assisted materials design. By synthesizing fundamental design principles and recent progress, this review highlights how biomass-derived materials can accelerate the development of high-performance, safe, and truly sustainable next-generation SSBs.