Researchers show molecular devices that switch between memory, logic and synapse roles, enabling adaptive neuromorphic computing directly within electronic materials.
As computing systems push beyond silicon limits, researchers seek materials that can do more than simply store and process data. Molecular electronics once promised ultra compact devices, but real world molecular behaviour proved unpredictable. In parallel, neuromorphic computing has aimed to build hardware that can learn and adapt like the brain. Yet most existing platforms rely on rigid materials that only imitate learning through complex circuitry.
To address this gap, researchers at the Indian Institute of Science have demonstrated a new way to encode adaptive intelligence directly into molecular matter. Led by Sreetosh Goswami at the Centre for Nano Science and Engineering, the team developed molecular devices whose function can be changed on demand. A single device can act as memory, logic, analog processor, selector, or electronic synapse, depending on how it is stimulated.
The adaptability comes from chemical design. The researchers synthesised 17 ruthenium based molecular complexes and showed that tiny changes in molecular structure and surrounding ions strongly influence how electrons move. By tuning this chemistry, the same device can switch between digital and analog behaviour across a wide range of conductance states.
To explain this behaviour, the team developed a theoretical framework combining quantum chemistry and body physics. The model captures how electron transport, molecular oxidation and reduction and ion rearrangement together determine switching dynamics and stability. This allows device function to be predicted from molecular structure. The approach combines memory and computation within the same material, opening a pathway toward neuromorphic hardware where learning is built into matter itself.
Key features of the research include:
- Chemically designed molecular devices with adaptive behaviour
- Multiple functions encoded in a single device
- Unified memory and computation in the same material
- Predictive theory linking molecular structure to function
Sreebrata Goswami, Visiting Scientist at CeNSE and co-author on the study who led the chemical design, says, “It is rare to see adaptability at this level in electronic materials. Here, chemical design meets computation, not as an analogy, but as a working principle.”
