Huntington’s disease (HD) is caused by a CAG trinucleotide repeat expansion in the first exon of the huntingtin (HTT) gene coding for the huntingtin (HTT) protein. The misfolding and consequential aggregation of CAG-expanded mutant HTT (mHTT) underpin HD pathology. Our interest in the life cycle of HTT led us to consider the development of high-affinity small-molecule binders of HTT oligomerized/amyloid-containing species that could serve as either cellular and in vivo imaging tools or potential therapeutic agents. We recently reported the development of PET tracers CHDI-180 and CHDI-626 as suitable for imaging mHTT aggregates, and here we present an in-depth pharmacological investigation of their binding characteristics. We have implemented an array of in vitro and ex vivo radiometric binding assays using recombinant HTT, brain homogenate-derived HTT aggregates, and brain sections from mouse HD models and humans post-mortem to investigate binding affinities and selectivity against other pathological proteins from indications such as Alzheimer’s disease and spinocerebellar ataxia 1. Radioligand binding assays and autoradiography studies using brain homogenates and tissue sections from HD mouse models showed that CHDI-180 and CHDI-626 specifically bind mHTT aggregates that accumulate with age and disease progression. Finally, we characterized CHDI-180 and CHDI-626 regarding their off-target selectivity and binding affinity to beta amyloid plaques in brain sections and homogenates from Alzheimer’s disease patients.

The fiber woven reinforced flexible composite film has been widely concerned in the fields of adjacent space aerostats, high air balls, etc. due to its excellent properties such as high strength, good toughness, light weight and good foldability. However, the temperature difference which is too large between day and night around the high-altitude environment causes the flexible composite film to undergo stress fatigue damage with the alternating change of the bearing pressure, which induces to form the damage microcrack and cause the air leakage damage of the flexible composite film, consequently, the damage seriously affects the normal service life of the aerostat and the airbag. Here, a typical Vectran fiber reinforced plain woven flexible composite film was taken as an example. The uniaxial warp stress fatigue damage evolution model of fiber reinforced plain weave flexible composites was constructed by using flexible film mechanics theory and progressive damage accumulation principle. And the uniaxial stress fatigue damage test and the SEM test of the damage mode were performed to identify the parameters of the uniaxial stress fatigue damage evolution model. It was found that the uniaxial warp-induced stress fatigue damage of flexible fiber reinforced plain woven composites was closely related to the properties, structure and stress state of the main load-bearing fiber bundles, and the damage mode was mainly represented by fiber bundle control, which synchronously induced the damage evolution of internal matrix and functional film layer. The fatigue test data of warp uniaxial fatigue damage under different fatigue loads showed good double logarithmic linear variation law, which could provide theoretical references for the structure optimization design and service life analysis of the fatigue damage mechanism.

Shape memory alloys (SMAs) show exceptional potential in actuator design due to their shape memory effect and superelasticity, yet their thermoelectric hysteresis challenges accurate modeling. This study proposes a hybrid framework integrating long short-term memory (LSTM) networks with physical kinematics to predict SMA actuator responses. Unlike conventional approaches, our method decouples material behavior prediction from actuator geometry: A single-layer LSTM network processes voltage-time sequences to predict SMA wire’s temperature and resistance dynamics, while a physics-based model computes angular displacement through phase transformation and constitutive equations. Trained on 10 experimental conditions (1–2 °C/s heating rates) and tested on 3 unseen cases (0.8 °C/s), the model achieves a mean absolute error of < 5% in angular displacement prediction, with root mean square errors of 2.5 × 10⁻⁵ for temperature/resistance outputs. The modular architecture eliminates neural network retraining during structural iterations—only ordinary differential equation parameters require adjustment. This approach advances rapid actuator optimization, demonstrating faster computational efficiency compared to full-physics models. Our findings establish a computationally sustainable paradigm for smart material-based actuation systems, extensible to piezoelectric and magnetostrictive materials through constitutive parameter substitution.

Shape memory polymers (SMPs) are a class of smart materials that exhibit remarkable shape memory effects, making them highly suitable for applications in aerospace, biomedical engineering, robotics, and textiles. Understanding their deformation mechanisms and developing accurate constitutive models to predict their thermomechanical behavior are crucial for advancing their practical applications. In this study, we propose a simplified three-dimensional viscoelastic constitutive model based on the Standard Linear Viscoelastic (SLV) framework to describe the shape memory behavior of SMPs under small strain conditions, which are typical in engineering applications such as torsion and bending. The model is implemented using a user-defined material subroutine (UMAT) in the finite element analysis software ABAQUS, enabling numerical simulations of SMPs’ shape memory behavior under uniaxial tension, torsion, and bending deformations. The simulation results demonstrate excellent agreement with experimental data, validating the model’s ability to accurately predict SMPs’ mechanical behavior. The proposed model is characterized by its simplicity, ease of parameter acquisition, and straightforward numerical implementation, offering valuable theoretical guidance for the design and application of SMP-based smart structures.

To address the issue of electronic equipment failure inside the instrument compartment due to aerodynamic heating during high-speed flight. Combining the heat transfer characteristics of phase change materials, a new instrument compartment structure was proposed as the research subject based on phase change materials. While studying the heat transfer characteristics of this structure, one-dimensional phase change heat transfer theoretical model was constructed based on the Lightfoot integral equation method, and the corresponding analytical solution was obtained. To explore the temperature change law of the instrument compartment structure and verify the rationality of the theoretical model, the new thermal experiment was carried out for the instrument compartment structure. Compared with the aluminum alloy instrument compartment structure, the experimental results show that the instrument compartment structure design based on phase change materials could effectively reduce the temperature of the structure itself, and the experimental data are in good agreement with the theoretical calculation results, which verified the rationality of the theoretical model and provided a scientific basis for the practical application of phase change materials in instrument compartment structures.