arXiv subjects

Amit Lal

Publications and source records attributed to Amit Lal.

11 recordsLinked to original sources

arXiv2026

Evaluating SAP RPT-1 for Enterprise Business Process Prediction: In-Context Learning vs. Traditional Machine Learning on Structured SAP Data

Tabular foundation models aim to make machine learning accessible for enterprise data without task-specific training. This paper presents the first independent evaluation of SAP's Retrieval Pretrained Transformer (RPT-1) from a practitioner perspective. RPT-1 is a compact 64.6 MB model pretrained on 1.34 TB of structured data across 3.1 million tables. We benchmark it against tuned gradient-boosted decision trees (XGBoost, LightGBM, CatBoost) on three SAP business scenarios: demand forecasting across SD/MM/PP modules, predictive data integrity in BC/MM/QM, and financial risk classification in FI/CO/AR. Across five-fold cross-validation on datasets ranging from 2,500 to 3,200 rows, RPT-1 reaches 91-96% of tuned GBDT accuracy without any training examples. The classification gap is modest at 3.6-4.1 percentage points on AUC-ROC, though regression tasks show wider gaps of 8.9-11.1 percentage points on R-squared. An interesting finding is a crossover at roughly 75-100 context rows where RPT-1 actually outperforms XGBoost under limited data. Based on these results, we propose a practical hybrid workflow: use RPT-1 for rapid screening, then train GBDT selectively where prediction accuracy justifies the effort. All experiments are reproducible through publicly available Hugging Face Spaces.

cs.LG↗

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

Kilovolt Pyroelectric Voltage Generation and Electrostatic Actuation With Fluidic Heating

Integrated micro power generators are crucial components for micro robotic platforms to demonstrate untethered operation and to achieve autonomy. Current micro robotic electrostatic actuators typically require hundreds to thousands of voltages to output sufficient work. Pyroelectricity is one such source of high voltages that can be scaled to small form factors. This paper demonstrates a distributed pyroelectric high voltage generation mechanism to power kV actuators using alternating exposure of crystals to hot and cold water (300C to 900C water temperature). Using this fluidic temperature control, a pyroelectrically generated voltage of 2470 V was delivered to a 2 pF storage capacitor yielding a 6.10 {\mu}J stored energy. A maximum energy of 17.46 {\mu}J was delivered to a 47 pF capacitor at 861 V. The recirculating water can be used to heat a distributed array of converters to generate electricity in distant robotic actuator sections. The development of this distributed system would enable untethered micro-robot to be operated with a flexible body and free of battery recharging, which advances its applications in the real world.

cs.RO↗

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

Quantum Transport in Graphene Using Surface Acoustic Wave Resonators

Surface acoustic waves (SAWs) provide a contactless method for measuring the wavevector-dependent conductivity. This technique has been used to discover emergent length scales in the fractional quantum Hall regime of traditional, semiconductor-based heterostructures. SAWs would appear to be an ideal match for van der Waals (vdW) heterostructures, but the right combination of substrate and experimental geometry to allow access to the quantum transport regime has not yet been found. We demonstrate that SAW resonant cavities fabricated on LiNbO$_3$ substrates can be used to access the quantum Hall regime of high-mobility, hexagonal boron nitride (hBN) encapsulated graphene heterostructures. Our work establishes SAW resonant cavities as a viable platform for performing contactless conductivity measurements in the quantum transport regime of vdW materials.

cond-mat.mes-hall↗

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↗

arXiv2021

Epitaxial Sc$_x$Al$_{1-x}$N on GaN is a High K Dielectric

Epitaxial Sc$_x$Al$_{1-x}$N thin films of ~100 nm thickness grown on metal polar GaN exhibit significantly enhanced relative dielectric permittivity ($\epsilon_r$) values relative to AlN. $\epsilon_r$ values of ~17 to 21 for Sc contents of 17 to 25% (x=0.17 to 0.25) measured electrically by capacitance-voltage (CV) measurements at 500 kHz frequency indicate Sc$_x$Al$_{1-x}$N has the largest relative dielectric permittivity of any existing nitride material. This points toward the usage of Sc$_x$Al$_{1-x}$N as potential epitaxial, single-crystalline dielectric material that can be deposited in situ on GaN and AlN electronic and photonic devices for enhanced performance.

physics.app-ph↗

arXiv2021

Ferroelectricity in Polar ScAlN/GaN Epitaxial Semiconductor Heterostructures

Room temperature ferroelectricity is observed in lattice-matched ~18% ScAlN/GaN heterostructures grown by molecular beam epitaxy on single-crystal GaN substrates. The epitaxial films have smooth surface morphologies and high crystallinity. Pulsed current-voltage measurements confirm stable and repeatable polarization switching in such ferroelectric/semiconductor structures at several measurement conditions, and in multiple samples. The measured coercive field values are Ec~0.7 MV/cm at room temperature, with remnant polarization Pr~10 μC/cm2 for ~100 nm thick ScAlN layers. These values are substantially lower than comparable ScAlN control layers deposited by sputtering. Importantly, the coercive field of MBE ScAlN is smaller than the critical breakdown field of GaN, offering the potential for low voltage ferroelectric switching. The low coercive field ferroelectricity of ScAlN on GaN heralds the possibility of new forms of electronic and photonic devices with epitaxially integrated ferroelectric/semiconductor heterostructures that take advantage of the GaN electronic and photonic semiconductor platform, where the underlying semiconductors themselves exhibit spontaneous and piezoelectric polarization.

cond-mat.mtrl-sci↗

arXiv2018

Multi-beam RF accelerators for ion implantation

We report on the development of a radio frequency (RF) linear accelerator (linac) for multiple-ion beams that is made from stacks of low cost wafers. The accelerator lattice is comprised of RF-acceleration gaps and electrostatic quadrupole focusing elements that are fabricated on 10-cm wafers made from printed circuit board or silicon. We demonstrate ion acceleration with an effective gradient of about 0.5 MV per meter with an array of 3 by 3 beams. The total ion beam energies achieved to date are in the 10 keV range with total ion currents in tests with noble gases of ~0.1mA. We discuss scaling of the ion energy (by adding acceleration modules) and ion currents (with more beams) for applications of this multi-beam RF linac technology to ion implantation and surface modification of materials.

physics.acc-ph↗

arXiv2016

Structured illumination microscopy image reconstruction algorithm

Structured illumination microscopy (SIM) is a very important super-resolution microscopy technique, which provides high speed super-resolution with about two-fold spatial resolution enhancement. Several attempts aimed at improving the performance of SIM reconstruction algorithm have been reported. However, most of these highlight only one specific aspect of the SIM reconstruction -- such as the determination of the illumination pattern phase shift accurately -- whereas other key elements -- such as determination of modulation factor, estimation of object power spectrum, Wiener filtering frequency components with inclusion of object power spectrum information, translocating and the merging of the overlapping frequency components -- are usually glossed over superficially. In addition, most of the work reported lie scattered throughout the literature and a comprehensive review of the theoretical background is found lacking. The purpose of the present work is two-fold: 1) to collect the essential theoretical details of SIM algorithm at one place, thereby making them readily accessible to readers for the first time; and 2) to provide an open source SIM reconstruction code (named OpenSIM), which enables users to interactively vary the code parameters and study it's effect on reconstructed SIM image.

cs.CV↗