Heterojunction‐Driven Stochasticity: Bi‐Heterojunction Noise‐Enhanced Negative Transconductance Transistor in Image Generation

Reliable true-random number generator (TRNG) hardware demands amplified intrinsic noise and multi-bit entropy output, which are difficult to achieve in conventional single-device TRNG implementation. A bi-heterojunction noise-enhanced negative transconductance (BHN-NTC) transistor is presented, incorporating an asymmetric PTCDI-C13 layer into an NTC transistor. This design enhances electron injection, expanding the NTC region (19 → 27 V) and increasing negative transconductance (-0.036 µS at V<sub>GS</sub> = -11 V → -0.073 µS at V<sub>GS</sub> = -15 V) by reducing the electron injection barrier (≈2.13 eV → ≈0.41 eV). The bi-heterojunction configuration introduces a strong correlation between noises, including trapping/detrapping and generation/recombination processes. This property enables a threefold higher entropy throughput in TRNG, achieving a 3-bit output per sampling event. The BHN-NTC-driven TRNG leverages increased noise-induced entropy to generate more diverse latent vectors, mitigating mode collapse and enabling the synthesis of high-quality, realistic images. This significantly enhances StyleGAN2-based image generation, improving performance metrics such as Frechet inception distance (FID) (18.7 → 8.3), kernel inception distance (KID) (0.024 → 0.009), inception score (IS) (6.5 → 9.2), and multi-scale structural similarity (MS-SSIM) (0.43 → 0.21). Consequently, the BHN-NTC transistor establishes a scalable stochastic noise platform, advancing applications in secure electronics and probabilistic stochastic computing.

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Publication Details

Journal
Advanced Materials
Published
2025-06-25
DOI
https://doi.org/10.1002/adma.202505150
Citations
6
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
4.38

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article

Heterojunction‐Driven Stochasticity: Bi‐Heterojunction Noise‐Enhanced Negative Transconductance Transistor in Image Generation

Wonjun Shin, Ryun‐Han Koo, J. Q. Song, Eun Kwang Lee et al.
6 citations
Advanced Materials
Advanced Memory and Neural Computing
4.38
article

Heterojunction‐Driven Stochasticity: Bi‐Heterojunction Noise‐Enhanced Negative Transconductance Transistor in Image Generation

Wonjun Shin, Ryun‐Han Koo, J. Q. Song, Eun Kwang Lee, Hocheon Yoo, Chang‐Hyun Kim, Young-Min Han
article en
6 citations

Abstract

Reliable true-random number generator (TRNG) hardware demands amplified intrinsic noise and multi-bit entropy output, which are difficult to achieve in conventional single-device TRNG implementation. A bi-heterojunction noise-enhanced negative transconductance (BHN-NTC) transistor is presented, incorporating an asymmetric PTCDI-C13 layer into an NTC transistor. This design enhances electron injection, expanding the NTC region (19 → 27 V) and increasing negative transconductance (-0.036 µS at V<sub>GS</sub> = -11 V → -0.073 µS at V<sub>GS</sub> = -15 V) by reducing the electron injection barrier (≈2.13 eV → ≈0.41 eV). The bi-heterojunction configuration introduces a strong correlation between noises, including trapping/detrapping and generation/recombination processes. This property enables a threefold higher entropy throughput in TRNG, achieving a 3-bit output per sampling event. The BHN-NTC-driven TRNG leverages increased noise-induced entropy to generate more diverse latent vectors, mitigating mode collapse and enabling the synthesis of high-quality, realistic images. This significantly enhances StyleGAN2-based image generation, improving performance metrics such as Frechet inception distance (FID) (18.7 → 8.3), kernel inception distance (KID) (0.024 → 0.009), inception score (IS) (6.5 → 9.2), and multi-scale structural similarity (MS-SSIM) (0.43 → 0.21). Consequently, the BHN-NTC transistor establishes a scalable stochastic noise platform, advancing applications in secure electronics and probabilistic stochastic computing.

Advanced MaterialsVol. 37(41)
Seoul National University (KR), University of Ottawa (CA), Hanyang University (KR), Sungkyunkwan University (KR), Pukyong National University (KR), Anyang University (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion
Affordable and clean energy
Openalex Percentile: Top 5%
Advanced Memory and Neural Computing
4.38
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