AIMC Topic: Elastic Modulus

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Vital signal sensing and manipulation of a microscale organ with a multifunctional soft gripper.

Science robotics
Soft grippers that incorporate functional materials are important in the development of mechanically compliant and multifunctional interfaces for both sensing and stimulating soft objects and organisms. In particular, the capability for firm and deli...

Left-Handed or Right-Handed? Determinants of the Chirality of Helically Deformable Soft Actuators.

Soft robotics
Helical curling and spiral structure are very common in nature, which inspire researchers to create various forms of helical configurations and actuators. The helically deformable actuators perform asymmetric deformations and show different chirality...

Paper-Based Robotics with Stackable Pneumatic Actuators.

Soft robotics
This work presents a unique approach to the design, fabrication, and characterization of paper-based origami robotic systems consisting of stackable pneumatic actuators. These paper-based actuators (PBAs) use materials with high elastic modulus-to-ma...

A Novel Biomimetic Compliant Structural Skin Based on Composite Materials for Biorobotics Applications.

Soft robotics
Biorobotics is increasingly attracting engineers worldwide, due to the high impact this field can have on the society. Biorobotics aims at imitating or taking inspiration from mechanisms and strategies evolved by animals, including their locomotion a...

Adaptive Self-Sealing Suction-Based Soft Robotic Gripper.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
While suction cups prevail as common gripping tools for a wide range of real-world parts and surfaces, they often fail to seal the contact interface when engaging with irregular shapes and textured surfaces. In this work, the authors propose a suctio...

A New Tactile Transfer Cell Using Magnetorheological Materials for Robot-Assisted Minimally Invasive Surgery.

Sensors (Basel, Switzerland)
This paper proposes a new type of tactile transfer cell which can be effectively applied to robot-assisted minimally invasive surgery (RMIS). The proposed tactile device is manufactured from two smart materials, a magnetorheological fluid (MRF) and a...

An insight into predictive parameters of tablet capping by machine learning and multivariate tools.

International journal of pharmaceutics
Capping is the frequently observed mechanical defect in tablets arising from the sub-optimal selection of the formulation composition and their robustness of response toward process parameters. Hence, overcoming capping propensity based on the unders...

Data-smart machine learning methods for predicting composition-dependent Young's modulus of pharmaceutical compacts.

International journal of pharmaceutics
The ability to predict mechanical properties of compacted powder blends of Active Pharmaceutical Ingredients (API) and excipients solely from component properties can reduce the amount of 'trial-and-error' involved in formulation design. Machine Lear...

Cryostructuring of Polymeric Systems : Application of Deep Neural Networks for the Classification of Structural Features Peculiar to Macroporous Poly(vinyl alcohol) Cryogels Prepared without and with the Additives of Chaotropes or Kosmotropes.

Molecules (Basel, Switzerland)
Macroporous poly(vinyl alcohol) cryogels (PVACGs) are physical gels formed via cryogenic processing of polymer solutions. The properties of PVACGs depend on many factors: the characteristics and concentration of PVA, the absence or presence of foreig...

Machine learning-based design strategy for 3D printable bioink: elastic modulus and yield stress determine printability.

Biofabrication
Although three-dimensional (3D) bioprinting technology is rapidly developing, the design strategies for biocompatible 3D-printable bioinks remain a challenge. In this study, we developed a machine learning-based method to design 3D-printable bioink u...