Researchers built a molecular film that stores 16,384 states — and used it to create an analog computer that works like a brain

Graphene molecule
Graphene molecule (Image credit: Shutterstock)

Researchers from the Indian Institute of Science (IISc) have successfully built a molecular film that stores 16,384 conductance states, According to TechXplore. It shows us a potential future where we go beyond the limits of classical binary and even up-and-coming quantum computing.

To put things into context, binary computing has a two-bit resolution, meaning it has only two possible states, 1 and 0, and it can store only one. On the other hand, quantum computing can represent 2^n states simultaneously, with n representing the number of qubits. So, if your quantum computer has four qubits, you can store up to 16 states. However, the study published in the Nature Journal says that this chip can handle 14-bit resolution (or 2^14). This means it can reliably store 16,384 states, all while using small amounts of energy.

The research team, led by Assistant Professor Sreetosh Goswami at the Centre for Nano Science and Engineering (CeNSE) at IISc, used the movement of molecules and ions within the material film to represent particular memory states. They then used precise times electrical pulses to trace the movement of these molecules and then map each of them to a specific signal, allowing them to build a “molecular diary” of the different states within the molecular film.

Goswami tells TechXplore, “This project brought together the precision of electrical engineering with the creativity of chemistry, letting us control molecular kinetics very precisely inside an electronic circuit powered by nanosecond voltage pulses.” As these molecules change their electronic states, the chip can perform complex computations, like matrix multiplication, in a single step.

Because these memory states can store and process much more information, these molecular films would work well as a neuromorphic accelerator, acting similarly to how the neurons in human brains work. However, what makes this accelerator different from other experimental DNA technology is how easily it could be integrated with existing silicon chips to boost performance and efficiency.

To prove its capabilities, the research team used the chip to recreate the ‘Pillars of Creation’ using raw James Webb Space Telescope data. The original image was created using NASA’s Pleiades supercomputer, which had a theoretical peak of 608.83 GFlop/s and a power rating of 2,090 kW. However, with their neuromorphic accelerator paired with a desktop computer, they could output the same image at a fraction of the time and energy required.

This development is encouraging, as humanity’s global computing requirements are increasing exponentially annually. While many still think that quantum computing is still the holy grail of data processing, this neuromorphic accelerator seems like a closer and more viable solution. At the moment, the research team is now developing this molecular film into a completely integrated chip. “This is a completely home-grown effort, from materials to circuits and systems,” Goswami told TechXplore. “We are well on our way to translating this technology into a system-on-a-chip.”

Jowi Morales
Contributing Writer

Jowi Morales is a tech enthusiast with years of experience working in the industry. He’s been writing with several tech publications since 2021, where he’s been interested in tech hardware and consumer electronics.

  • edzieba
    Classical computing has 2 possible states and quantum computing has 16 possible states if you have four qubits — but this one has 16,384 possible states.
    Gargling the marketing blurb a bit too hard here. A binary system with 4 bits will also have 16 possible states. A binary computer with 14 bits will have 16,384 states.
    Then you have trinary computers, where a bit can have 3 states. You have NAND cells, which can have (today) 32 possible states per cell (PKC). You have encoding states like QAM where a single symbol can have hundreds of states (e.g. 32768-QAM has, as expected, 32,768 possible states).

    As per the original paper, all the "16,384 possible states!" sillyness is just because their ADC sampling precision was 14 bits.
    Reply
  • DougMcC
    edzieba said:
    Gargling the marketing blurb a bit too hard here. A binary system with 4 bits will also have 16 possible states. A binary computer with 14 bits will have 16,384 states.
    Then you have trinary computers, where a bit can have 3 states. You have NAND cells, which can have (today) 32 possible states per cell (PKC). You have encoding states like QAM where a single symbol can have hundreds of states (e.g. 32768-QAM has, as expected, 32,768 possible states).

    As per the original paper, all the "16,384 possible states!" sillyness is just because their ADC sampling precision was 14 bits.
    And to suggest that a 14bit storage/processing system is somehow competitive with QC badly misunderstands why Quantum Computing is so powerful.
    Reply
  • bit_user
    edzieba said:
    You have NAND cells, which can have (today) 32 possible states per cell (PKC).
    My thoughts, exactly. NAND is an apt point of comparison, where up to 5 bits per cell have been demonstrated to work at production-grade reliability levels. IIRC, we've even seen robust demonstrations of 7 bits per cell, on industrial-focused implementations using older, low-density process nodes (note: this test chip also used a very old process node, as is typical of research chips).

    edzieba said:
    As per the original paper,
    Thanks for that. I followed the link in the article (which went to another news article about the paper), but didn't take the additional step of looking at the nature.com link, since I knew it'd be paywalled. However, I just now followed your link and I'm glad I did because the abstract does a far better job of characterizing their accomplishment than either Toms' or the TechXPlore news articles about it.

    From the paper's abstract:
    "Here we introduce an analog molecular memristor based on a Ru-complex of an azo-aromatic ligand with 14-bit resolution. Precise kinetic control over a transition between two thermodynamically stable molecular electronic states facilitates 16,520 distinct analog conductance levels, which can be linearly and symmetrically updated or written individually in one time step, substantially simplifying the weight update procedure over existing neuromorphic platforms. The circuit elements are unidirectional, facilitating a selector-less 64 \00d7 64 crossbar-based dot-product engine that enables vector–matrix multiplication, including Fourier transform, in a single time step. We achieved more than 73 dB signal-to-noise-ratio, four orders of magnitude improvement over the state-of-the-art methods, while consuming 460\00d7 less energy than digital computers."
    So, essentially, their goal wasn't to build a denser memory, but rather to build a better analog computing system suitable for accelerating neuromorphic computations (which is a key detail, since it requires only approximate accuracy).

    Analog computing is far from new. The efficiency benefits are well-known. Credit to the researchers for pushing the state of the art, in this area.
    Reply