In Situ Nanostress Visualization Method to Reveal the Micromechanical Mechanism of Nanocomposites by Atomic Force Microscopy

Investigating the relationship between residual stress and micromechanical properties of blood vessels using atomic force microscopy

The magnitude of vascular residual stress, an inherent characteristic exclusive to the vasculature, exhibits a strong correlation with vascular compliance, tensile resistance, vascular rigidity, and vascular remodeling subsequent to vascular transplantation. Vascular residual stress can be quantified by evaluating the magnitude of the opening angle within the vascular ring. For decellularized vessels, the vascular ring's opening angle diminishes, consequently reducing residual stress. The decellularization process induces a laxity in the vascular fiber structure within decellularized vessels. To investigate the interrelation between the magnitude of residual stress and the microstructure as well as mechanical properties of elastin and collagen within blood vessels, this study employed fresh blood vessels, stress-relieved vessels, and sections of decellularized blood vessels. Structural scanning and force map experiments on the surface of the sections were conducted using atomic force microscopy (AFM). The findings revealed well-organized arrangements of elastin and collagen within fresh vessels, wherein the regularity of collagen and elastin exhibited variability as residual stress declined. Furthermore, both stress-relieved and decellularized vessel sections exhibited a reduction in the mean Young's modulus to varying extents in comparison to fresh vessels. The validity of our experimental results was further corroborated through finite element simulations. Hence, residual stress assumes a crucial role in upholding the structural stability of blood vessels, and the intricate association between residual stress and the microstructural and micromechanical properties of blood vessels holds significant implications for comprehending the impact of vascular diseases on vascular structure and advancing the development of biomimetic artificial blood vessels that replicate residual stress. RESEARCH HIGHLIGHTS: In this inquiry, we scrutinized the interconnection amid vascular residual stress and the microscale and nanoscale aspects of vascular structure and mechanical function, employing AFM. We ascertained that residual stress assumes a pivotal role in upholding vascular microstructure and mechanical attributes. The experimental outcomes were subsequently validated through finite element simulation.

How scanning probe microscopy can be supported by artificial intelligence and quantum computing?

The impact of Artificial Intelligence (AI) is rapidly expanding, revolutionizing both science and society. It is applied to practically all areas of life, science, and technology, including materials science, which continuously requires novel tools for effective materials characterization. One of the widely used techniques is scanning probe microscopy (SPM). SPM has fundamentally changed materials engineering, biology, and chemistry by providing tools for atomic-precision surface mapping. Despite its many advantages, it also has some drawbacks, such as long scanning times or the possibility of damaging soft-surface materials. In this paper, we focus on the potential for supporting SPM-based measurements, with an emphasis on the application of AI-based algorithms, especially Machine Learning-based algorithms, as well as quantum computing (QC). It has been found that AI can be helpful in automating experimental processes in routine operations, algorithmically searching for optimal sample regions, and elucidating structure-property relationships. Thus, it contributes to increasing the efficiency and accuracy of optical nanoscopy scanning probes. Moreover, the combination of AI-based algorithms and QC may have enormous potential to enhance the practical application of SPM. The limitations of the AI-QC-based approach were also discussed. Finally, we outline a research path for improving AI-QC-powered SPM. RESEARCH HIGHLIGHTS: Artificial intelligence and quantum computing as support for scanning probe microscopy. The analysis indicates a research gap in the field of scanning probe microscopy. The research aims to shed light into ai-qc-powered scanning probe microscopy.

Performance Enhancement of Silicone Rubber Using Superhydrophobic Silica Aerogel with Robust Nanonetwork Structure and Outstanding Interfacial Effect

The application of high-performance rubber nanocomposites has attracted wide attention, but its development is limited by the imbalance of interface and network effects caused by fillers. Herein, an ultrastrong polymer nanocomposite is successfully designed by introducing a superhydrophobic and mesoporous silica aerogel (HSA) as the filler to poly(methyl vinyl phenyl) siloxane (PVMQ), which increased the PVMQ elongation at break (∼690.1%) by ∼9.3 times and the strength at break (∼6.6 MPa) by ∼24.3 times. Furthermore, HSA/PVMQ with a high dynamic storage modulus (G'0) of ∼12.2 MPa and high Payne effect (ΔG') of ∼9.4 MPa is simultaneously achieved, which is equivalent to 2-3 times that of commercial fumed silica reinforced PVMQ. The superior performance is attributed to the filler-rubber interfacial interaction and the robust filler-rubber entanglement network which is observed by scanning electron microscopy. When the HSA-PVMQ entanglement network is subjected to external stress, both the HSA and bound-PVMQ chains are synergistically involved in resisting structural evolution, resulting in the maximized energy dissipation and deformation resistance through the desorption of the polymer chain and the slip/interpenetrating of the exchange hydrogen bond pairs. Hence, highly aggregated nanoporous silica aerogels may soon be widely used in the application of reinforced silicone rubber or other polymers shortly.

Simultaneous Visualization of Microscopic Conductivity and Deformation in Conductive Elastomers

Conductive elastomers are promising for a wide range of applications in many fields due to their unique mechanical and electrical properties, and an understanding of the conductive mechanisms of such materials under deformation is crucial. However, revealing the microscopic conduction mechanism of conductive elastomers is a challenge. In this study, we developed a method that combines in situ deformation nanomechanical atomic force microscopy (AFM) and conductive AFM to successfully and simultaneously characterize the microscopic deformation and microscopic electrical conductivity of nanofiller composite conductive elastomers. With this approach, we visualized the conductive network structure of carbon black and carbon nanotube composite conductive elastomers at the nanoscale, tracked their microscopic response under different compressive strains, and revealed the correlation between microscopic and macroscopic electrical properties. This technique is important for understanding the conductive mechanism of conductive elastomers and improving the design of conductive elastomers.