Conventional asphalt concrete has a limited lifespan due to cracking, deformation, and environmental degradation, driving the development of fiber-reinforced asphalt concrete (FRAC). However, key gaps remain in current data-driven FRAC studies due to small and homogeneous datasets, “black-box” machine learning models, and trade-offs between mechanical-sustainable performance, failing to provide a transparent understanding of features governing FRAC behaviors. This paper proposes a framework integrating explainable artificial intelligence and life cycle assessment (LCA) to advance mechanical and sustainable design of FRAC. A dataset of 2490 laboratory samples covers 15 input features and 3 mechanical outputs. Eight machine learning models, along with a voting ensemble strategy, were optimized using Genetic algorithm for hyperparameter tuning. The optimized voting ensemble achieved an average prediction performance of R² = 0.87, RMSE = 1.09, MAPE = 11.96%, and MAE = 0.60 across the three mechanical targets, indicating robust and reliable predictive capability. SHapley Additive exPlanations (SHAP) analysis and linear non-gaussian acyclic causal inference quantified global/local feature impacts and pairwise interactions. LCA evaluated economic and environmental impacts and derived strength-normalized sustainability metrics. Finally, an interactive graphic user interface platform was developed for predictions, SHAP interpretations, and LCA outcomes. This data-driven approach establishes a paradigm for intelligent FRAC design, harmonizing mechanical performance with sustainability.

Cutting-edge photonic devices frequently rely on microparticle components to focus and manipulate light. Conventional methods used to produce these microparticle components frequently offer limited control of their structural properties or require low-throughput nanofabrication of more complex structures. Here, we employ a synthetic biology approach to produce environmentally friendly, living microlenses with tunable structural properties. We engineered Escherichia coli bacteria to display the silica biomineralization enzyme silicatein from aquatic sea sponges. Our silicatein-expressing bacteria can self-assemble a shell of polysilicate "bioglass" around themselves. Remarkably, the polysilicate-encapsulated bacteria can focus light into intense nanojets that are nearly an order of magnitude brighter than unmodified bacteria. Polysilicate-encapsulated bacteria are metabolically active for up to 4 mo, potentially allowing them to sense and respond to stimuli over time. Our data demonstrate that synthetic biology offers a pathway for producing inexpensive and durable photonic components that exhibit unique optical properties.

Energy routers present a viable option for harvesting renewable energy sources (RESs) and ensure dependable electricity provision in industrial microgrids. This paper presents a multi-functional, grid-forming energy router (GFMER), accompanied by a hierarchical proactive control approach. The lower-layer controller handles the coordination strategies among photovoltaic (PV) systems, battery energy storage units (BESU), and DC/AC converters. In this layer, an optimized multi-objective droop control mechanism is presented to proactively regulate AC grid-side voltage imbalances and deviations. Meanwhile, the upper-layer control is deployed to maintain the DC bus voltage, and a novel power allocation module has been designed to enhance the dynamic transient support for grids. The effectiveness and practical value of this proposed methodology have been validated through MATLAB/Simulink and hardware-in-the-loop (HIL) experiments.

In this research, the effects of natural seawater (SW) on the properties of alkali-activated slag/fly ash (AASF) are studied. AASF prepared with deionized water is set as the reference mixture. The results showed that the use of natural SW resulted in a prolonged setting time and lower heat release, but no obvious impact on the flowability of AASF specimens. The long-term compressive strength became higher when SW was used, whereas the corresponding flexural strength and fractural toughness turned lower. The use of SW induced the formation of new products that were not identified in the reference mixture, such as Cl–hydrocalumite and gypsum. In addition, it is evidenced that the dissolution of fly ash (FA) particles was significantly delayed with the incorporation of SW. All these results were related to the various ions introduced by the natural SW and their interactions with the alkaline activator as well as the precipitation of salts on slag and FA surfaces or in the matrix.