arXiv subjects

Shubham Jadhav

Publications and source records attributed to Shubham Jadhav.

5 recordsLinked to original sources

arXiv2026

COFFEE: A Carbon-Modeling and Optimization Framework for HZO-based FeFET eNVMs

Information and communication technologies account for a growing portion of global environmental impacts. While emerging technologies, such as emerging non-volatile memories (eNVM), offer a promising solution to energy efficient computing, their end-to-end footprint is not well understood. Understanding the environmental impact of hardware systems over their life cycle is the first step to realizing sustainable computing. This work conducts a detailed study of one example eNVM device: hafnium-zirconium-oxide (HZO)-based ferroelectric field-effect transistors (FeFETs). We present COFFEE, the first carbon modeling framework for HZO-based FeFET eNVMs across life cycle, from hardware manufacturing (embodied carbon) to use (operational carbon). COFFEE builds on data gathered from a real semiconductor fab and device fabrication recipes to estimate embodied carbon, and architecture level eNVM design space exploration tools to quantify use-phase performance and energy. Our evaluation shows that, at 2 MB capacity, the embodied carbon per unit area overhead of HZO-FeFETs can be up to 11% higher than the CMOS baseline, while the embodied carbon per MB remains consistently about 4.3x lower than SRAM across different memory capacity. A further case study applies COFFEE to an edge ML accelerator, showing that replacing the SRAM-based weight buffer with HZO-based FeFET eNVMs reduces embodied carbon by 42.3% and operational carbon by up to 70%.

cs.AR↗

arXiv2025

Lorentzian Switching Dynamics in HZO-based FeMEMS Synapses for Neuromorphic Weight Storage

Neuromorphic computing demands synaptic elements that can store and update weights with high precision while being read non-destructively. Conventional ferroelectric synapses store weights in remnant polarization states and might require destructive electrical readout, limiting endurance and reliability. We demonstrate a ferroelectric MEMS (FeMEMS) based synapse in which analog weights are stored in the piezoelectric coefficient $d_{31,eff}$ of a released Hf$_{0.5}$Zr$_{0.5}$O$_2$ (HZO) MEMS unimorph. Partial switching of ferroelectric domains modulates $d_{31,eff}$, and a low-amplitude mechanical drive reads out the weight without read-disturb in the device yielding more than 7-bit of programming levels. The mechanical switching distribution function follows a Lorentzian distribution as a logarithmic function of partial poling voltage ($V_p$) consistent with nucleation-limited switching (NLS), and the median threshold extracted from electromechanical data obeys a Merz-type field-time law with a dimensionless exponent $\alpha = 3.62$. These relationships establish a quantitative link between mechanical weights and electrical switching kinetics. This mechanically read synapse avoids depolarization and charge-injection effects, provides bipolar weights (well suited for excitatory and inhibitory synapses), directly reveals partial domain populations, and offers a robust, energy-efficient route toward high-bit neuromorphic hardware.

cs.ET↗

arXiv2024

Ferroelectric AlBN Films by Molecular Beam Epitaxy

We report the properties of molecular beam epitaxy deposited AlBN thin films on a recently developed epitaxial nitride metal electrode Nb2N. While a control AlN thin film exhibits standard capacitive behavior, distinct ferroelectric switching is observed in the AlBN films with increasing Boron mole fraction. The measured remnant polarization Pr of 15 uC/cm2 and coercive field Ec of 1.45 MV/cm in these films are smaller than those recently reported on films deposited by sputtering, due to incomplete wake-up, limited by current leakage. Because AlBN preserves the ultrawide energy bandgap of AlN compared to other nitride hi-K dielectrics and ferroelectrics, and it can be epitaxially integrated with GaN and AlN semiconductors, its development will enable several opportunities for unique electronic, photonic, and memory devices.

cond-mat.mtrl-sci↗

arXiv2023

Fabrication and Characterization of AlN-based, CMOS compatible Piezo-MEMS Devices

This paper details the development of high-quality, c-axis oriented AlN thin films up to 2 μm thick, using sputtering on platinum-coated SOI substrates for use in piezoelectric MEMS. Our comprehensive studies illustrate how important growth parameters such as the base Pt electrode quality, deposition temperature, power, and pressure, can influence film quality. With careful adjustment of these parameters, we managed to manipulate residual stresses (from compressive -1.2 GPa to tensile 230 MPa), and attain a high level of orientation in the AlN thin films, evidenced by < 5deg FWHM X-Ray diffraction peak widths. We also report on film surface quality regarding roughness, as assessed by atomic force microscopy, and grain size, as determined through scanning electron microscopy. Having attained the desired film quality, we proceeded to a fabrication process to create piezoelectric micromachined ultrasound transducers (PMUTs) with the AlN on SOI material stack, using deep reactive ion etching (DRIE). Initial evaluations of the vibrational behavior of the created devices, as observed through Laser Doppler Vibrometry, hint at the potential of these optimized AlN thin films for MEMS transducer development.

physics.app-ph↗

arXiv2022

HZO-based FerroNEMS MAC for In-Memory Computing

This paper demonstrates a hafnium zirconium oxide (HZO)-based ferroelectric NEMS unimorph as the fundamental building block for very low-energy capacitive readout in-memory computing. The reported device consists of a 250 $μ$m $\times$ 30 $μ$m unimorph cantilever with 20 nm thick ferroelectric HZO on 1 $μ$m $SiO_2$.Partial ferroelectric switching in HZO achieves analog programmable control of the piezoelectric coefficient ($d_{31}$) which serves as the computational weight for multiply-accumulate (MAC) operations. The displacement of the piezoelectric unimorph was recorded by actuating the device with different input voltages $V_{in}$. The resulting displacement was measured as a function of the ferroelectric programming/poling voltage $V_p$. The slopes of central beam displacement ($δ_{max}$) vs $V_{in}$ were measured to be between 182.9nm/V (for -8 $V_p$) and -90.5nm/V (for 8 $V_p$), demonstrating that $V_p$ can be used to change the direction of motion of the beam. The resultant ($δ_{max}$) from AC actuation is in the range of -18 to 36 nm and is a scaled product of the input voltage and programmed $d_{31}$ (governed by the $V_p$). The multiplication function serves as the fundamental unit for MAC operations with the ferroelectric NEMS unimorph. The displacement from many such beams can be added by summing the capacitance changes, providing a pathway to implement a multi-input and multi-weight neuron. A scaling and fabrication analysis suggests that this device can be CMOS compatible, achieving high in-memory computational throughput.

physics.app-ph↗