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Stretchable electronics have drawn intensive research attention over the past decade due to their potential impact in various applications, including displays, soft robots, wearable electronics, digital healthcare, and many other areas Considering that intrinsically stretchable technology is relatively new, the predominant approach to realizing current stretchable applications leverages the structure of stretchable interconnects. Therefore, one of the primary challenges in stretchable electronics is designing an optimal stretchable interconnect structure, such as mechanically compliant electrodes, capable of significant stretching without compromising electrical functionality. Numerous techniques for designing stretchable interconnects, including wavy, serpentine, and kirigami structures, have been developed to maximize the stretchability of stretchable electrodes.

Despite achieving high stretchability in structural designs, accurately measuring the strain distribution in real-time during dynamic stretching remains challenging.


To address the current technical limitations in comprehensively understanding the full mechanism of strain behavior and the geometrical effects of serpentine structures without physically breaking the structure, we carefully investigated strain-induced color changes reflecting the complex strain distribution of serpentine-shaped CLCEs. To achieve optimal serpentine CLCEs, specially tailored high-modulus and shape-designed serpentine CLCEs were investigated, incorporating controlled non-uniform strain distribution for serpentine structures. By examining the aspect shape factor in the mechano-optical color changes of the CLCEs, it was visually and quantitatively confirmed that if the CLCE samples were aligned parallel to the direction of stretching, the strain increased, whereas if they were aligned perpendicular to the direction of stretching, the strain decreased. In addition to structural design factors, a sequential study of the modulus effect on the mechano-optical visualization of the serpentine structure revealed that a serpentine CLCE with a high modulus exhibited results that are consistent with conventional serpentine stretching behavior, with the associated structural color changes and photonic wavelength shifts. In a further study on the shape design parameters (angle, width, and length) of serpentine CLCE with a high modulus, the critical factors that determine the complex and varied stretchable serpentine properties were investigated. It was found that the angle (α) shape factor is the most crucial serpentine design parameter that ensures stretchability, whereas the width wordpress is the parameter that diminishes stretchability. Furthermore, to assess the structural color changes and photonic wavelength shifts according to practical stretching mechanisms, a 2 × 2 arrayed multi-interconnected serpentine CLCE structure under multiaxial (uniaxial and biaxial) stretching conditions was investigated. It was confirmed that elongation parallel to the direction of mechanical stretching could induce serpentine stretching characteristics in the arrayed CLCE devices. These experimental results of structural color changes and photonic wavelength shifts, which enhance the reliability of many studies through comparison with strain distributions, are also supported by the FEM. Considering that stretchable CLCEs also enable molecular arrangement changes, and based on the findings of this study, it was confirmed that serpentine CLCEs can optimize serpentine design through optical visualization methods.

Researchers have developed an innovative therapeutic platform by mimicking the intricate structures of viruses using artificial intelligence (AI). Their pioneering research was published in Nature on December 18.

Viruses are uniquely designed to encapsulate genetic material within spherical shells, enabling them to replicate and invade host cells, often causing disease. Inspired by these complex structures, researchers have been exploring artificial proteins modeled after viruses.

These “nanocages” mimic viral behavior, effectively delivering therapeutic genes to target cells. However, existing nanocages face significant challenges: their small size restricts the amount of genetic material they can carry, and their simple designs fall short of replicating the multifunctionality of natural viral proteins.

Are we on the path to becoming one with machines? 🤖✨ In this video, we dive deep into the concept of The Singularity—the point where humanity and artificial intelligence merge into one seamless entity. From advanced neural interfaces to AI-driven biological enhancements, we’ll explore the technologies paving the way for this future transformation.

Ever wondered what happens when AI becomes smarter than humans? As we approach the three “scary” stages of AI—AGI (Artificial General Intelligence), ASI (Artificial Superintelligence), and the ultimate stage, Singularity—the line between groundbreaking innovation and existential danger grows thinner.

In this video, we’ll explore these stages, the potential for AI to surpass human intelligence, and the profound consequences of machines thinking, evolving, and controlling their own destiny. Are we truly prepared for the rise of AI?

Chapters:

Intro 00:00 — 0:43

NCI researchers have developed an artificial intelligence (AI) tool that uses data from individual cells inside tumors to predict whether a person’s cancer will respond to a specific drug. These findings, published today in Nature Cancer, suggest that such single-cell RNA sequencing data could one day be used to help doctors more precisely match cancer patients with drugs that will be effective for their cancer.


An AI tool called PERCEPTION developed by NCI researchers could one day be used to help more precisely match patients with effective cancer drugs.