Multi-compartment membranes for multicellular robots
… everybody needs some body.
The typical image of a robot is one composed of motors and circuits, encased in metal. Yet the field of molecular robotics, which is being spearheaded in Japan, is beginning to change that.
Much like how complex living organisms are formed, molecular robots derive form and functionality from assembled molecules. Such robots could have important applications, such as being used to treat and diagnose diseases in vivo.
The first challenge in building a molecular robot is the same as the most basic need of any organism: the body, which holds everything together. But manufacturing complex structures, especially at the microscopic level, has proven to be an engineering nightmare, and many limitations on what is possible currently exist.
To address this problem, a research team at Tohoku University has developed a simple method for creating molecular robots from artificial, multicellular-like bodies by using molecules which can organize themselves into the desired shape.
The team, including Associate Professor Shin-ichiro Nomura and postdoctoral researcher Richard Archer from the Department of Robotics at the Graduate School of Engineering, recently reported their breakthrough in the American Chemical Society’s publication, Langmuir.
“Our work demonstrated a simple, self-assembly technique which utilizes phospholipids and synthetic surfactants coated onto a hydrophobic silicone sponge,” said Archer.
When Nomura and his colleagues introduced water into the lipid coated sponge, the hydrophilic and hydrophobic forces enabled the lipids and surfactants to assemble themselves, thereby allowing water to soak in. The sponge was then placed into oil, spontaneously forming micron sized, stabilized aqueous droplets as the water was expelled from the solid support. When pipetted on the surface of water, these droplets quickly assembled into larger planar macroscopic structures, like bricks coming together to form a wall.
“Our developed technique can easily build centimeter size structures from the assembly of micron sized compartments and is capable of being done with more than one droplet type,” adds Archer. “By using different sponges with water containing different solutes, and forming different droplet types, the droplets can combine to form heterogeneous structures. This modular approach to assembly unleashes near endless possibilities.”
The team could also turn these bodies into controllable devices with induced motion. To do so, they introduced magnetic nanoparticles into the hydrophobic walls of the multi-compartment structure. Archer says this multi-compartment approach to robot design will allow flexible modular designs with multiple functionalities and could redefine what we imagine robots to be. “Future work here will move us closer to a new generation of robots which are assembled by molecules rather than forged in steel and use functional chemicals rather than silicon chips and motors.”
Journal: Langmuir
DOI: 10.1021/acs.langmuir.2c02859
Article Title: Scalable Synthesis of Planar Macroscopic Lipid-Based Multi-Compartment Structures
Article Publication Date: 27-Mar-2023
Media Contact
Public Relations
Tohoku University
public_relations@grp.tohoku.ac.jp
All latest news from the category: Materials Sciences
Materials management deals with the research, development, manufacturing and processing of raw and industrial materials. Key aspects here are biological and medical issues, which play an increasingly important role in this field.
innovations-report offers in-depth articles related to the development and application of materials and the structure and properties of new materials.
Newest articles
Molecular gardening: New enzymes discovered for protein modification pruning
How deubiquitinases USP53 and USP54 cleave long polyubiquitin chains and how the former is linked to liver disease in children. Deubiquitinases (DUBs) are enzymes used by cells to trim protein…
Machine learning accelerates catalyst discovery
Conceptual blueprint to analyze experimental catalyst data. Machine learning (ML) models have recently become popular in the field of heterogeneous catalyst design. The inherent complexity of the interactions between catalyst…
More efficient car designs with AI
8,000 open source models for sustainable mobility. Designing new cars is expensive and time consuming. As a result, manufacturers tend to make only minor changes from one model generation to…