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Abstract Adaptive and bioinspired droplet-based materials are built using the droplet interface bilayer (DIB) technique, assembling networks of lipid membranes through adhered microdroplets. The properties of these lipid membranes are linked to the properties of the droplets forming the interface. Consequently, rearranging the relative positions of the droplets within the network will also alter the properties of the lipid membranes formed between them, modifying the transmembrane exchanges between neighboring compartments. In this work, we achieved this through the use of magnetic fluids or ferrofluids selectively dispersed within the droplet-phase of DIB structures. First, the ferrofluid DIB properties are optimized for reconfiguration using a coupled experimental-computational approach, exploring the ideal parameters for droplet manipulation through magnetic fields. Next, these findings are applied towards larger, magnetically-heterogeneous collections of DIBs to investigate magnetically-driven reconfiguration events. Activating electromagnets bordering the DIB networks generates rearrangement events by separating and reforming the interfacial membranes bordering the dispersed magnetic compartments. These findings enable the production of dynamic droplet networks capable of modifying their underlying membranous architecture through magnetic forces.
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Neuron‐Inspired Biomolecular Memcapacitors Formed Using Droplet Interface Bilayer Networks
Abstract Brain‐inspired (or neuromorphic) computing circumvents costly bottlenecks in conventional Von Neumann architectures by collocating memory and processing. This is accomplished through dynamic material architectures, strengthening or weakening internal conduction pathways similar to synaptic connections within the brain. A new class of neuromorphic materials approximates synaptic interfaces using lipid membranes assembled via the droplet interface bilayer (DIB) technique. These DIB membranes have been studied as novel memristors or memcapacitors owing to the soft, reconfigurable nature of both the lipid membrane geometry and the embedded ion‐conducting channels. In this work, a biomolecular approach to neuromorphic materials is expanded frommodel synapsesto acharge‐integrating model neuron. In these serial membrane networks, it is possible to create distributions of voltage‐sensitive gates capable of trapping ionic charge. This trapped charge creates transmembrane potential differences that drive changes in the system's net capacitance through electrowetting, providing a synaptic weight that changes in response to the history and timing of input signals. This fundamental change from interfacial memory (dimensions of the membrane) to internal memory (charge trapped within the droplets) provides a functional plasticity capable of multiple weights, longer‐term retention roughly an order of magnitude greater than memory stored in the membranes alone, and programming‐erasure.
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- Award ID(s):
- 2310360
- PAR ID:
- 10641022
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Electronic Materials
- Volume:
- 11
- Issue:
- 6
- ISSN:
- 2199-160X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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