Christopher L. Hinkle

Improved Reliability and Thermal Stability in Amorphous Oxide Semiconductor Transistors

Christopher L. Hinkle

Three-dimensional integration with logic and memory co-located in the upper levels above high-performance silicon transistors is being explored to enable new functionality and improved system-level performance. Achieving this vision requires back-end-of-line (BEOL) compatible semiconductor materials and device processes, which remain a significant …

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Determining and Mitigating Stoichiometry, Structural, and Mobility Degradation in Low-Temperature Grown GaN for Thin Film Transistors

Tian Sun, Guanyu Zhou, Christopher L. Hinkle

Gallium nitride (GaN) is a promising channel material for back-end-of-line (BEOL) access transistors owing to its wide bandgap and high electron mobility, which together enable a high I on / I off current ratio and suppressed leakage. However, conventional metal organic chemical …

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Atomic Layer Deposited Amorphous Ge-Doped Indium Oxide with Enhanced Mobility-Stability-Crystallization Resistance Tradeoff

Yushan Lee, Xingtian Wang, Jiahui Duan, Guanyu Zhou et autres

In this work, we demonstrate the potential of germanium-doped indium oxide (Ge:In2O3) as a promising oxide semiconductor offering an improved tradeoff among mobility, electrical stability, and crystallization resistance. This makes it suitable for both500 °C 1T1C DRAM process. Through a comparative study …

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(Invited) Novel Metals for Scaled Interconnects

Christopher L. Hinkle

Copper (Cu) interconnects are an increasingly important bottleneck in integrated circuits due to energy consumption and latency caused by the notable increase in Cu resistivity as dimensions decrease, primarily due to electron scattering at surfaces. Here, we showcase the potential of two …

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Room-temperature ferromagnetism in monolayer WSe2

Rehan Younas, Guanyu Zhou, Xinyu Liu, Sabyasachi Tiwari et autres

Substitutional doping of magnetic impurities in monolayer transition metal dichalcogenides is a potentially promising route to create above room temperature 2D ferromagnets. Recent reports, however, reveal significant inconsistencies between multiple experimental observations and theoretical calculations. To unravel these apparent discrepancies, a comprehensive …

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PtCoO2 for Scaled Interconnects

Yansong Li, Guanyu Zhou, Michelle M. Kelley, Sadiq Shahriyar Nishat et autres

Copper (Cu) interconnects are an increasingly important bottleneck in integrated circuits due to energy consumption and latency caused by the notable increase in Cu resistivity as dimensions decrease, primarily due to electron scattering at surfaces. Herein, the potential of a directional conductor, …

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Scalable and Contamination-Free Selenium-Assisted Exfoliation of Transition Metal Dichalcogenides WSe2 and MoSe2

Rehan Younas, Guanyu Zhou, Christopher L. Hinkle

In two-dimensional (2D) materials research, exfoliating 2D transition metal dichalcogenides (TMDs) from their growth substrates for device fabrication remains a significant challenge. Current methods, such as those involving polymers, metals, or chemical etchants, suffer from limitations like contamination, defect introduction, and a …

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AI-Accelerated Electronic Materials Discovery and Development

Christopher C. Price, Ichiro Takeuchi, James M. Rondinelli, Wei Chen et autres

Recent advances in AI applied to high-throughput materials discovery, synthesis, and processing offer a pathway to accelerated breakthroughs and scaled optimization of advanced electronic materials for data-intensive computation.

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Predicting and Accelerating Nanomaterial Synthesis Using Machine Learning Featurization

Christopher C. Price, Yansong Li, Guanyu Zhou, Rehan Younas et autres

Materials synthesis optimization is constrained by serial feedback processes that rely on manual tools and intuition across multiple siloed modes of characterization. We automate and generalize feature extraction of reflection high-energy electron diffraction (RHEED) data with machine learning to establish quantitatively predictive …

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Predicting and Accelerating Nanomaterials Synthesis Using Machine Learning Featurization

Christopher C. Price, Yansong Li, Guanyu Zhou, Rehan Younas et autres

Materials synthesis optimization is constrained by serial feedback processes that rely on manual tools and intuition across multiple siloed modes of characterization. We automate and generalize feature extraction of reflection high-energy electron diffraction (RHEED) data with machine learning to establish quantitatively predictive …

(Invited) Bulk Traps in Layered 2D Gate Dielectrics

Jaemin Shin, Tyafur Rahman Pathan, Guanyu Zhou, Christopher L. Hinkle

Ultra-thin ferromagnets, when coupled with magnetoelectric or multiferroic materials, could potentially enable highly energy-efficient electric field control of the magnet for use in nanoelectronic memories. Substitutional doping of magnetic impurities in monolayer transition metal dichalcogenides (TMDs) may be a promising way to …

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(Invited) Bulk Traps in Layered 2D Gate Dielectrics

Jaemin Shin, Tyafur Rahman Pathan, Guanyu Zhou, Christopher L. Hinkle

In this work, we synthesize new 2D layered dielectrics and fabricate metal-insulator-metal (MIM) capacitors to determine their viability for scaled gate dielectrics (ZrNCl, HfNCl, BiOCl, and Mg(OH)2) in transition metal dichalcogenide-based transistors. While successful synthesis and fabrication was demonstrated, the properties of …

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