Sugar-Based Artificial Synapse Runs on Femtojoules and Doubles as an Encryption Engine

Researchers at Qingdao University have built an artificial synapse out of one of biology’s most humble molecules: dextran, a natural polysaccharide sugar. The device, described in the Journal of Materials Science, is an organic optoelectronic synaptic transistor that consumes single-pulse energies as low as 2 femtojoules for optical signaling and 4.2 femtojoules for electrical signaling. Those figures are remarkable because a single basal excitatory synaptic transmission in the biological cerebral cortex typically costs between 1 and 10 femtojoules. In other words, this engineered sugar-gated transistor now operates in the same energy regime as the synapses inside your own brain, a milestone that has long eluded conventional organic synaptic devices plagued by high operating voltages and weak light sensitivity.

The secret lies in the dielectric layer. Instead of synthetic polymers or metal oxides, the team, led by Shuolei Wei, Linhao Cheng, Jiacheng Huang and Jie Su, used dextran, a glucan polysaccharide whose chains are densely decorated with hydroxyl groups. This chemistry makes the dielectric exceptionally hydrophilic, so it spontaneously harvests water molecules from the ambient air. Under an applied electric field, protons migrate efficiently through the internal hydrogen-bond network of the glucan chains, accumulating at the dielectric/semiconductor interface to form an electric double layer, or EDL. At a modest frequency of 20 Hz, the dextran dielectric exhibits a capacitance of 5.14 microfarads per square centimeter, a value high enough to grant the gate strong control over the transistor channel at very low voltages.

The semiconductor layer is PDBT-co-TT, also known as DPP-DTT, an organic polymer semiconductor well suited to phototransistor operation. The strong interfacial electric field established by the EDL does more than lower the operating power; it dramatically enhances the dissociation of photogenerated excitons in DPP-DTT. Excitons, the bound electron-hole pairs created when light is absorbed, often recombine before they can contribute useful current in organic semiconductors. The dextran-gated field tears them apart, yielding a photoconductive gain of approximately 10^3 under weak illumination. That gain means the device can respond to light signals far too faint for ordinary organic phototransistors to register, addressing one of the field’s most persistent limitations.

With this hardware in place, the device emulates the essential behaviors of a biological synapse. It reproduces paired-pulse facilitation, the phenomenon in which a second neural pulse arriving shortly after the first produces a stronger response, and it demonstrates the transition from short-term to long-term plasticity, the cellular basis of learning and memory. The photoresponse is wavelength-dependent, so the synapse distinguishes between different colors of light much as retinal circuits do. These are not merely demonstrations; they are the computational primitives that neuromorphic engineers need to build brain-inspired systems that process information the way neural tissue does, rather than shuttling data between separate memory and processor units in the von Neumann architecture.

The photoelectric synergy of the device opens unexpected applications. Because light pulses can write, amplify and erase conductance states, the team used the synapse to transmit information optically in Morse code, with selective optical signal amplification and erasure supporting the protocol. A short flash of light becomes a dot, a longer pulse a dash, and the transistor’s plastic conductance states carry the message. This suggests a route toward optical communication interfaces in which the sensing element and the processing element are the same physical device, cutting the energy and complexity that separate photodetectors from neural processing circuits in conventional designs.

Perhaps the most striking application is neuromorphic encryption. The researchers leveraged hardware-derived conductance sequences from the transistor as physical unclonable keys. Because these conductance sequences arise from the stochastic electrochemistry of the dextran EDL and the device’s own photoresponse history, they are effectively impossible to duplicate without possessing the physical hardware itself. Using these sequences, the system encrypted and decrypted images of handwritten digits from the MNIST dataset, a standard benchmark in machine vision. The encryption is neuromorphic in the deepest sense: the same synapse that computes also secures, merging memory, processing and cryptography into a single low-power element.

The work fits into a broader movement toward green organic neuromorphic devices. Earlier efforts in the field have explored dielectrics and active layers derived from wood nanopaper, human hair keratin, chitosan, pectin, chlorophyll and other natural polyelectrolytes, motivated by the promise of flexible, biocompatible and even degradable electronics. The Qingdao team’s dextran dielectric advances this agenda by combining environmental sustainability with the ultra-low power consumption and high optical sensitivity that practical neuromorphic systems demand. Prior natural polysaccharide synapses have shown promise, but few have reached the femtojoule regime while simultaneously delivering photoconductive gains near 10^3 and supporting encryption protocols.

The implications ripple outward. Wearable health monitors, implantable neural interfaces and distributed sensor networks all face the same bottleneck: they must sense, compute and communicate continuously on power budgets measured in microwatts or less. A synapse that senses light, computes with synaptic plasticity and encrypts with physical keys, all while drawing femtojoule-scale pulse energies, could relax those constraints fundamentally. The wavelength-dependent photoresponse adds a further dimension, hinting at neuromorphic vision systems that discriminate color at the sensor level, and the Morse-code demonstration points toward optical inter-synapse communication protocols for future brain-inspired networks.

Challenges remain before dextran-gated synapses reach commercial maturity. The reliance on ambient water molecules for proton transport raises questions about device behavior in extreme humidity or dryness, and the long-term stability of natural polysaccharide dielectrics under continuous electrical stress must be characterized. Yet the conceptual advance is clear and compelling. By gating an organic semiconductor with a sugar, the Qingdao researchers have shown that the path to brain-scale energy efficiency may run through green chemistry, and that the same physical device can sense, learn, communicate and encrypt. As neuromorphic computing races toward real-world deployment, this dextran-gated transistor offers a template for devices that are simultaneously ultra-low power, optically sensitive and environmentally sustainable, a rare and powerful combination in the emerging landscape of brain-inspired hardware.

Subject of Research: Electronic materials

Article Title: Dextran-gated organic optoelectronic synaptic transistors with ultra-low power consumption and neuromorphic encryption computing

Article References: Wei, S., Cheng, L., Huang, J., & Su, J. (2026). Dextran-gated organic optoelectronic synaptic transistors with ultra-low power consumption and neuromorphic encryption computing. Journal of Materials Science. https://doi.org/10.1007/s10853-026-13947-7

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13947-7

Keywords: neuromorphic computing, organic electronics, synaptic transistors, dextran, encryption, low-power devices, Dextran-gated, organic, optoelectronic, synaptic, transistors, ultra-low