Nature Search

3D Integration of functionally diverse 2D materials for optoelectronic reservoir computing

The authors demonstrate the integration of In₂Se₃ photodetectors with MoS₂ memtransistors in a 3D stack, enabling efficient near-sensor data processing. This setup allows dynamic calibration and robust handling of device variations, improving time-series prediction accuracy in computing systems.

Anirban Chowdhury
Anshul Rasyotra
Saptarshi Das
ResearchOpen Access21 Nov 2025
Nature Communications

Volume: 16, P: 1-10
Publisher Correction: High-performance p-type field-effect transistors using substitutional doping and thickness control of two-dimensional materials

Mayukh Das
Dipanjan Sen
Saptarshi Das
Amendments and Corrections14 Nov 2024
Nature Electronics

Volume: 8, P: 93
A complementary two-dimensional material-based one instruction set computer

A two-dimensional one instruction set computer has been fabricated based on complementary metal–oxide–semiconductor technology by leveraging the heterogeneous integration of large-area n-type MoS₂ and p-type WSe₂ field-effect transistors.

Subir Ghosh
Yikai Zheng
Saptarshi Das
Research11 Jun 2025
Nature

Volume: 642, P: 327-335
Multifunctional 2D FETs exploiting incipient ferroelectricity in freestanding SrTiO₃ nanomembranes at sub-ambient temperatures

Sen et al. report the stacking of a perovskite incipient ferroelectric nanomembrane with atomically thin 2D material for a back-end-of-line compatible ferroelectric-like field effect transistors, functioning as a cryogenic memory at 15 K and as an inference engine at room temperature.

Dipanjan Sen
Harikrishnan Ravichandran
Saptarshi Das
ResearchOpen Access30 Dec 2024
Nature Communications

Volume: 15, P: 1-12
High-performance p-type field-effect transistors using substitutional doping and thickness control of two-dimensional materials

Substitutionally doped two-dimensional diselenides can be used to make p-type field-effect transistors with reduced contact resistance and good electrostatic control by varying the thickness of the channel and contact regions.

Mayukh Das
Dipanjan Sen
Saptarshi Das
Research06 Nov 2024
Nature Electronics

Volume: 8, P: 24-35
A stochastic encoder using point defects in two-dimensional materials

This study demonstrates how point defects in 2D semiconductors can be harnessed for neuromorphic computing. By using random telegraph noise in WSe₂ field-effect transistors, the researchers improve inference accuracy of noise-inflicted medical images.

Harikrishnan Ravichandran
Theresia Knobloch
Saptarshi Das
ResearchOpen Access04 Dec 2024
Nature Communications

Volume: 15, P: 1-11
Robust chemical analysis with graphene chemosensors and machine learning

Machine learning models trained with extensive datasets generated by ion-sensitive field-effect transistor sensors can classify complex liquids and quantify changes in chemical composition.

Andrew Pannone
Aditya Raj
Saptarshi Das
Research09 Oct 2024
Nature

Volume: 634, P: 572-578
A bio-inspired visuotactile neuron for multisensory integration

Designing bio-inspired multisensory neurons remains a challenge. Here, the authors develop an artificial visuotactile neuron based on the integration of a photosensitive monolayer MoS₂ memtransistor and a triboelectric tactile sensor capable of super-additive response, inverse effectiveness effect, and temporal congruency.

Muhtasim Ul Karim Sadaf
Najam U Sakib
Saptarshi Das
ResearchOpen Access15 Sept 2023
Nature Communications

Volume: 14, P: 1-12
An all 2D bio-inspired gustatory circuit for mimicking physiology and psychology of feeding behavior

Implementing emotional aspects like physiology and psychology in decision-making remains a challenge. Here, the authors propose a bio-inspired gustatory circuit based on 2D materials that mimics adaptive feeding behavior in humans, considering both physiological states (hunger) and psychological states (appetite).

Subir Ghosh
Andrew Pannone
Saptarshi Das
ResearchOpen Access27 Sept 2023
Nature Communications

Volume: 14, P: 1-10
Hardware implementation of Bayesian network based on two-dimensional memtransistors

Bayesian networks are applied to resolve several types of probabilistic problems. Here, Das et al. develop a stochastic computing hardware platform using two-dimensional memtransistors for the implementation of Bayesian network with high accuracy.

Yikai Zheng
Harikrishnan Ravichandran
Saptarshi Das
ResearchOpen Access23 Sept 2022
Nature Communications

Volume: 13, P: 1-11

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