Advanced high-k dielectric stacks with polySi and metal gates: Recent progress and current challenges. - Evgeni P. Gusev; Vijay Narayanan; Martin M. Frank (IBM J. Res. Dev., 2006)

Germanium channel MOSFETs: Opportunities and challenges. - Huiling Shang; Martin M. Frank; Evgeni P. Gusev; Jack O. Chu; Stephen W. Bedell; Kathryn W. Guarini; Mei-Kei Ieong (IBM J. Res. Dev., 2006)

High-k/metal gate innovations enabling continued CMOS scaling. - Martin M. Frank (ESSCIRC, 2011)

Electron mobility in thin In0.53Ga0.47As channel. - Eduard Cartier; Atreya Majumdar; K.-T. Lee; Takashi Ando; Martin M. Frank; John Rozen; Keith A. Jenkins; C. Liang; C.-W. Cheng; John Bruley; M. Hopstaken; Pranita Kerber; et al. (ESSDERC, 2017)

PBTI in InGaAs MOS capacitors with Al2O3/HfO2/TiN gate stacks: Interface-state generation. - Eduard Cartier; Martin M. Frank; Takashi Ando; John Rozen; Vijay Narayanan (IRPS, 2018)

Reliability Challenges with Materials for Analog Computing. - Eduard A. Cartier; Wanki Kim; Nanbo Gong; Tayfun Gokmen; Martin M. Frank; Douglas M. Bishop; Youngseok Kim; Seyoung Kim; Takashi Ando; Ernest Y. Wu; Praneet Adusumilli; John Rozen; et al. (IRPS, 2019)

Emerging Neural Workloads and Their Impact on Hardware. - David Brooks 001; Martin M. Frank; Tayfun Gokmen; Udit Gupta; Xiaobo Sharon Hu; Shubham Jain; Ann Franchesca Laguna; Michael T. Niemier; Ian O'Connor; Anand Raghunathan; Ashish Ranjan 001; Dayane Reis; et al. (DATE, 2020)

Filament Localization and Characterization in Hf02 ReRAM Cells using Laser Stimulation. - Franco Stellari; Ernest Y. Wu; Martin M. Frank; Leonidas E. Ocala; Takashi Ando; Peilin Song (ESSDERC, 2022)

Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited). - Martin M. Frank; Ning Li; Malte J. Rasch; Shubham Jain; Ching-Tzu Chen; Ramachandran Muralidhar; Jin-Ping Han; Vijay Narayanan; Timothy Philip; Kevin Brew; Andrew Simon; Iqbal Saraf; et al. (IRPS, 2023)

Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited). - Hsinyu Tsai; Pritish Narayanan; Shubham Jain; Stefano Ambrogio; Kohji Hosokawa; Masatoshi Ishii; Charles Mackin; Ching-Tzu Chen; Atsuya Okazaki; Akiyo Nomura; Irem Boybat; Ramachandran Muralidhar; et al. (ISCAS, 2023)

A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh. - Shubham Jain; Hsinyu Tsai; Ching-Tzu Chen; Ramachandran Muralidhar; Irem Boybat; Martin M. Frank; Stanislaw Wozniak; Milos Stanisavljevic; Praneet Adusumilli; Pritish Narayanan; Kohji Hosokawa; Masatoshi Ishii; et al. (IEEE Trans. Very Large Scale Integr. Syst., 2023)