Molecular solar thermal fuels (MOSTs) based on azobenzene derivatives have become one of the research hotspots for solar thermal conversion and storage due to their excellent cycling stability, resistance to photodegradation, and the capability to precisely adjust their absorption wavelengths, and other merits. Here, a novel MOST with connecting two azobenzene molecules by a short linkage (bis-AZO) has been proposed; the photoisomerization regulation and energy storage performance are studied experimentally in detail. The photoisomerization rate of the resultant MOST could be controlled by diverse irradiation intensities. The energy density for bis-AZO was 275.03 J g⁻¹ at 100% isomerization degree, with excellent thermal and photochemical cycling stability. The macroscale heat release of bis-AZO loaded on fabric reached a temperature increase of about 4.3 °C. This research offers a new design strategy for increasing the energy density in azobenzene-based molecular solar thermal fuels.

Reliable state estimation is critical for the safe operation of second-life battery systems but is severely hindered by significant parameter heterogeneity arising from diverse historical aging conditions. Traditional static models struggle to adapt to such variability, while online identification methods are prone to divergence under dynamic loads. To overcome these challenges, this paper proposes a Dual-Anchor Adaptive Fusion Framework for robust State of Charge (SOC) estimation and State of Health (SOH) soft-sensing. Specifically, to establish a reliable physical baseline, an automated Dynamic Relaxation Interval Selection (DRIS) strategy is introduced. By minimizing the fitting Root Mean Square Error (RMSE), DRIS systematically extracts high-fidelity parameters to construct two “anchor models” that rigorously define the boundaries of the aging space. Subsequently, a residual-driven Bayesian fusion mechanism is developed to seamlessly interpolate between these anchors based on real-time voltage feedback, enabling the model to adapt to uncalibrated target batteries. Concurrently, a novel “SOH Soft-Sensing” capability is unlocked by interpreting the adaptive fusion weights as real-time health indicators. Experimental results demonstrate that the proposed framework achieves robust SOC estimation with an RMSE of 0.42%, significantly outperforming the standard Adaptive Extended Kalman Filter (A-EKF, RMSE 1.53%), which exhibits parameter drift under dynamic loading. Moreover, the a posteriori voltage tracking residual is compressed to ~0.085 mV, effectively approaching the hardware’s ADC quantization limit. Furthermore, SOH is inferred with a relative error of 0.84% without additional capacity tests. This work establishes a robust methodological foundation for calibration-free state estimation in heterogeneous retired battery packs.

Organic phase change materials (OPCMs) show immense application potential in solar energy storages owing to high energy storage capacity and latent heat efficiency. However, it is difficult to achieve prolonged energy storage due to the sensitivity of phase change to environmental temperature, and adding other substances will lead to a decrease in total energy density. Herein, azobenzene organic phase change composite (C₁₄Azo-MA) was designed and prepared by doping myristic acid (MA) with an azobenzene derivative (C₁₄Azo) featuring a carbon chain identical to that of the MA matrix. C₁₄Azo-MA was systematically characterized by UV–Visible absorption spectroscopy and differential scanning calorimetry. The results showed that the C₁₄Azo-MA retains the same isomerization properties as the C₁₄Azo dopant. C₁₄Azo-MA, due to its molecular photoisomerization and enhanced intermolecular interactions, establishes a new energy barrier and forms supercooling within C₁₄Azo-MA, thereby allowing the storage of thermal energy below the crystallization temperature of MA. Notably, the C₁₄Azo-MA exhibits a high energy density of 225.08 J g⁻¹, surpassing that of pure MA by 14.42%. This work holds significant potential for solar energy storage applications.