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Temperature-doping phase diagram and endurance in Ce-doped HfO2
Authors:
Amit Kumar Shah,
Haidong Lu,
Kawshan Hathurusingha,
Alexei Gruverman,
Xiaoshan Xu
Abstract:
The structural and ferroelectric properties of epitaxial Hf1-xCexO2 (CHO) thin films in the ultrathin regime are investigated as a function of Ce concentration (5% <= x <= 20%) and temperature. A temperature-doping phase diagram is established for 10 nm films, showing a systematic evolution from the ferroelectric orthorhombic phase to tetragonal and cubic phases with increasing Ce content. The ort…
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The structural and ferroelectric properties of epitaxial Hf1-xCexO2 (CHO) thin films in the ultrathin regime are investigated as a function of Ce concentration (5% <= x <= 20%) and temperature. A temperature-doping phase diagram is established for 10 nm films, showing a systematic evolution from the ferroelectric orthorhombic phase to tetragonal and cubic phases with increasing Ce content. The orthorhombic-tetragonal transition temperature decreases from ~800°C at x = 5% to $~300°C$ at x = 15%, indicating strong stabilization of higher-symmetry phases with doping. Consistently, the remanent polarization decreases from ~15 to $3.8 μC/cm2$ as x increases from 5% to 20%. In contrast, the endurance improves significantly, with higher Ce concentrations exhibiting markedly enhanced cycling stability up to 108 cycles. The opposing trends of polarization and endurance are correlated with reduced orthorhombic distortion, suggesting that fatigue mitigation in Ce-doped HfO2 is linked to structural evolution. These results provide a framework for optimizing composition and reliability in ultrathin ferroelectric HfO2 devices.
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Submitted 29 July, 2026;
originally announced July 2026.
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Computational Insights into Defect Induced Modulation in Electronic Properties of 2D Nitride Monolayers
Authors:
Shreya G. Sarkar,
Kuneh Parag Shah,
Brahmananda Chakraborty
Abstract:
Two-dimensional (2D) nitride materials such as hexagonal boron nitride (h-BN), graphitic carbon nitride (g-C$_3$N$_4$), and beryllonitrene (BeN$_4$) have emerged as promising candidates for next generation electronic, optoelectronic, and energy applications due to their unique structural and electronic properties. This study presents a systematic investigation of the effects of vacancy defect, spe…
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Two-dimensional (2D) nitride materials such as hexagonal boron nitride (h-BN), graphitic carbon nitride (g-C$_3$N$_4$), and beryllonitrene (BeN$_4$) have emerged as promising candidates for next generation electronic, optoelectronic, and energy applications due to their unique structural and electronic properties. This study presents a systematic investigation of the effects of vacancy defect, specifically the role of nitrogen and constituent atom vacancies on the electronic properties of these materials. Our findings reveal that the introduction of nitrogen vacancies significantly alters the electronic characteristics of these materials. In h-BN, the presence of a nitrogen monovacancy significantly lowers the work function from 5.97 eV to 3.45 eV, one of the lowest values reported for any 2D material. Additionally, this defect reduces the band gap from 4.6 eV to 0.64 eV, driving the material toward half-metallic behavior. This is accompanied by the emergence of flat bands near the Fermi level, indicative of strong electron-electron interactions. In g-C$_3$N$_4$, nitrogen vacancies lead to a decrease in work function and band gap, with double nitrogen vacancies rendering the material nearly metallic. In BeN$_4$, nitrogen vacancies result in minimal charge redistribution and a slight increase in work function, highlighting the material's unique electronic behavior. These results underscore the potential of vacancy engineering in tuning the electronic properties of 2D nitride materials, offering avenues for the design of materials with tailored work functions and band gaps for applications in optoelectronics, spintronics, and catalysis.
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Submitted 15 October, 2025;
originally announced October 2025.
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Particle-hole symmetry in the pseudogap phase of moderately underdoped cuprate high temperature superconductors evidenced from joint density of states analysis
Authors:
Niraj Kumar Shah,
Junjing Zhao,
Utpal Chatterjee
Abstract:
In conventional superconductors, the energy scale associated with the superfluid stiffness is much larger compared to the pairing energy and hence, the superconducting transition temperature (Tc) is entirely dictated by the superconducting (SC) energy gap. The phase rigidity of the SC condensate in unconventional superconductors, on the other hand, can be low enough to enable destruction of superc…
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In conventional superconductors, the energy scale associated with the superfluid stiffness is much larger compared to the pairing energy and hence, the superconducting transition temperature (Tc) is entirely dictated by the superconducting (SC) energy gap. The phase rigidity of the SC condensate in unconventional superconductors, on the other hand, can be low enough to enable destruction of superconductivity via phase incoherence and persistence of an energy gap even at the absence of macroscopic superconductivity above Tc. This is considered a possible mechanism of the pseudogap (PG) state of cuprate high temperature superconductors (HTSCs). We have investigated the electronic energy (ω) and momentum-separation vector (q) dependence of the joint density of states (JDOS), derived from the autocorrelated Angle Resolved Photoemission Spectroscopy (ARPES) data, from moderately underdoped Bi2Sr2CaCu2O8+δHTSC samples at temperatures below and above Tc. We found that q-space structure of the constant ω JDOS intensity maps and the dispersions of the JDOS peaks are essentially the same both below and above Tc. Furthermore, the dispersions of the JDOS peaks above Tc are particle-hole symmetric. These observations evince similarity between the nature of the energy gap below and above Tc, which supports preformed pairing scenario for the PG state at least in the moderately underdoped regime.
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Submitted 15 September, 2025;
originally announced September 2025.
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Machine Learning Time Propagators for Time-Dependent Density Functional Theory Simulations
Authors:
Karan Shah,
Attila Cangi
Abstract:
Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under external time-dependent perturbations such as laser fields. In this work, we present a machine learning approach to accelerate electron dynamics simulations based on real time TDDFT using autoregressive neural operators as time-propagators for the electron density. By leveraging physics-…
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Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under external time-dependent perturbations such as laser fields. In this work, we present a machine learning approach to accelerate electron dynamics simulations based on real time TDDFT using autoregressive neural operators as time-propagators for the electron density. By leveraging physics-informed constraints and featurization, and high-resolution training data, our model achieves superior accuracy and computational speed compared to traditional numerical solvers. We demonstrate the effectiveness of our model on a class of one-dimensional diatomic molecules under the influence of a range of laser parameters. This method has potential in enabling on-the-fly modeling of laser-irradiated molecules and materials by utilizing fast machine learning predictions in a large space of varying experimental parameters of the laser.
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Submitted 1 December, 2025; v1 submitted 22 August, 2025;
originally announced August 2025.
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Thermal transport characteristics of impinging ferrofluid droplets in the presence of a magnetic field
Authors:
Ram Krishna Shah,
Saptarshi Mandal
Abstract:
Droplet interactions with solid surfaces are fundamental to natural phenomena and hold significant commercial relevance across diverse applications. While the impingement dynamics of conventional aqueous droplets on solid substrates are well-characterized, the behavior of non-aqueous droplets, particularly those influenced by external force fields like electric or magnetic fields, remains a less e…
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Droplet interactions with solid surfaces are fundamental to natural phenomena and hold significant commercial relevance across diverse applications. While the impingement dynamics of conventional aqueous droplets on solid substrates are well-characterized, the behavior of non-aqueous droplets, particularly those influenced by external force fields like electric or magnetic fields, remains a less explored domain. This study addresses this gap by investigating the impact of a magnetic field on the impingement dynamics of ferrofluid droplets on a heated solid surface. Ferrofluids are unique colloidal suspensions of magnetic nanoparticles within a non-magnetic carrier fluid, enabling external manipulation of their dynamic properties through magnetic forces. The application of a magnetic field introduces an attractive force within the ferrofluid, fundamentally altering the droplet's spreading behavior and, consequently, its transport characteristics upon impact. Our findings reveal a substantial increase in both the maximum spreading diameter and the contact time between the droplet and the substrate, directly leading to enhanced thermal transport efficiency. Furthermore, the magnetic force effectively suppresses droplet bounce-off from hydrophobic surfaces. These critical parameters can be precisely controlled by adjusting the strength of the induced magnetic force. Such interactions can be used in the design of thermal switches and thermal management systems. The multi-physics interactions of magnetic fields, fluid flow, interface tracking, and heat transfer within the multiphase system are computationally modelled to examine the effect of Weber number and contact angle on maximum spreading and associated heat transfer characteristics.
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Submitted 6 August, 2025; v1 submitted 25 June, 2025;
originally announced June 2025.
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Strong tunability of epitaxial relationship and reconstruction at improper ferroelectric interface
Authors:
Xin Li,
Yu Yun,
Guodong Ren,
Arashdeep Singh Thind,
Amit Kumar Shah,
Rohan Mishra,
Xiaoshan Xu
Abstract:
The atomic structures at epitaxial film-substrate interfaces determine scalability of thin films and can result in new phenomena. However, it is challenging to control the interfacial structures since they are decided by the most stable atomic bonding. In this work, we report strong tunability of the epitaxial interface of improper ferroelectric hexagonal ferrites deposited on spinel ferrites. The…
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The atomic structures at epitaxial film-substrate interfaces determine scalability of thin films and can result in new phenomena. However, it is challenging to control the interfacial structures since they are decided by the most stable atomic bonding. In this work, we report strong tunability of the epitaxial interface of improper ferroelectric hexagonal ferrites deposited on spinel ferrites. The selection of two interface types, related by a 90 deg rotation of in-plane epitaxial relations and featured by disordered and hybridized reconstructions respectively, can be achieved by growth conditions, stacking sequences, and spinel compositions. While the disordered type suppresses the primary K3 structure distortion and ferroelectricity in hexagonal ferrites, the hybridized type is more coherent with the distortion with minimal suppression. This tunable interfacial structure provides critical insight on controlling interfacial clamping and may offer a solution for the long-standing problem of practical critical thickness in improper ferroelectrics.
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Submitted 8 May, 2025;
originally announced May 2025.
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Antiferroelectricity with metastable polar state from Kittel model
Authors:
Amit Kumar Shah,
Xin Li,
Guodong Ren,
Yu Yun,
Rohan Mishra,
Xiaoshan Xu
Abstract:
We have revisited the Kittel model that describes antiferroelectricity (AFE) in terms of two sublattices of spontaneous polarization with antiparallel couplings. By constructing the comprehensive phase diagram including the antiferroelectric, ferroelectric, and paraelectric phases in the parameter space, we identified an AFE phase with stable antipolar states and metastable polar state (SAMP) due…
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We have revisited the Kittel model that describes antiferroelectricity (AFE) in terms of two sublattices of spontaneous polarization with antiparallel couplings. By constructing the comprehensive phase diagram including the antiferroelectric, ferroelectric, and paraelectric phases in the parameter space, we identified an AFE phase with stable antipolar states and metastable polar state (SAMP) due to the weak coupling between sublattices. We found that the metastability of the polar state in SAMP phase could lead to apparent remanent polarization, depending on the measurement timescale. This explains the observed ferroelectric behavior of orthorhombic hafnia, which is predicted to be antipolar by density functional theories.
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Submitted 6 May, 2025; v1 submitted 5 April, 2025;
originally announced April 2025.
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Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations
Authors:
Attila Cangi,
Lenz Fiedler,
Bartosz Brzoza,
Karan Shah,
Timothy J. Callow,
Daniel Kotik,
Steve Schmerler,
Matthew C. Barry,
James M. Goff,
Andrew Rohskopf,
Dayton J. Vogel,
Normand Modine,
Aidan P. Thompson,
Sivasankaran Rajamanickam
Abstract:
We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states,…
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We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states, and total energy. The package integrates data sampling, model training and scalable inference into a unified library, while ensuring compatibility with standard DFT and molecular dynamics codes. We demonstrate MALA's capabilities with examples including boron clusters, aluminum across its solid-liquid phase boundary, and predicting the electronic structure of a stacking fault in a large beryllium slab. Scaling analyses reveal MALA's computational efficiency and identify bottlenecks for future optimization. With its ability to model electronic structures at scales far beyond standard DFT, MALA is well suited for modeling complex material systems, making it a versatile tool for advanced materials research.
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Submitted 29 November, 2024;
originally announced November 2024.
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Improper flexoelectricity in hexagonal rare-earth ferrites
Authors:
Xin Li,
Guodong Ren,
Yu Yun,
Arashdeep Singh Thind,
Amit Kumar Shah,
Abbey Bowers,
Rohan Mishra,
Xiaoshan Xu
Abstract:
Flexoelectricity is a universal effect that generates electric polarization due to broken inversion symmetry caused by local strain gradient. The large strain gradient at nanoscale makes flexo-electric effects, especially in nanoscopic ferroelectric materials, promising in sensors, actuator, energy harvesting, and memory applications. In this work, we studied flexoelectricity in hexagonal ferrites…
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Flexoelectricity is a universal effect that generates electric polarization due to broken inversion symmetry caused by local strain gradient. The large strain gradient at nanoscale makes flexo-electric effects, especially in nanoscopic ferroelectric materials, promising in sensors, actuator, energy harvesting, and memory applications. In this work, we studied flexoelectricity in hexagonal ferrites h-YbFeO3, an improper ferroelectric expected to have weak piezoelectricity and low sensitivity to depolarization field, which are advantageous for studying flexoelectric effects. We show that in h-YbFeO3 epitaxial thin films, strain gradient on the order of 10^6 m-1 occurs near grain boundaries and edge dislocation, which has a significant impact on the non-polar K3 structural distortion that induces spontaneous polarization. The phenomenological model based on the Landau theory of improper ferroelectricity suggests an indirect flexoelectric effect on the order of 10 nC/m in h-YbFeO3, which is substantially larger than the expectation from Kogan mechanism. These results reveal a novel microscopic mechanism of coupling between strain gradient and polarization mediated by structural distortion, which we call improper flexoelectricity.
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Submitted 28 May, 2025; v1 submitted 25 September, 2024;
originally announced September 2024.
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Antiferroelectric Hafnia Down to the 2D Limit
Authors:
Xin Li,
Guodong Ren,
Haidong Lu,
Kartik Samanta,
Amit Kumar Shah,
Kai Huang,
Pravan Omprakash,
Yu Yun,
Pratyush Buragohain,
Huibo Cao,
Yan Wu,
Jordan A. Hachtel,
Andrew R. Lupini,
Miaofang Chi,
Juan Carlos Idrobo,
Evgeny Y. Tsymbal,
Alexei Gruverman,
Rohan Mishra,
Xiaoshan Xu
Abstract:
Antiferroelectricity is a material property characterized by alternating electric dipoles spontaneously ordered in antiparallel directions. Antiferroelectrics are promising for energy storage, solid-state cooling, and memory technologies; however, these materials are scarce, and their scalability remains largely unexplored. In this work, we demonstrate that single-crystalline hafnia, a lead-free C…
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Antiferroelectricity is a material property characterized by alternating electric dipoles spontaneously ordered in antiparallel directions. Antiferroelectrics are promising for energy storage, solid-state cooling, and memory technologies; however, these materials are scarce, and their scalability remains largely unexplored. In this work, we demonstrate that single-crystalline hafnia, a lead-free CMOS-compatible material, exhibits antiferroelectricity under compressive-strain conditions. We observe antiparallel sublattice polarization and stable double-hysteresis in single-crystalline (111)-oriented epitaxial La-doped hafnia films grown on yttrium-stabilized zirconia and show that the antipolar orthorhombic phase of hafnia adheres to the Kittel model of antiferroelectricity. Notably, compressive strain strengthens the antiferroelectric order in thinner La-doped hafnia films, achieving an unprecedented 850 C ordering temperature in the two-dimensional limit, highlighting hafnia's potential for advanced antiferroelectric devices.
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Submitted 2 August, 2025; v1 submitted 3 August, 2024;
originally announced August 2024.
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Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators
Authors:
Karan Shah,
Attila Cangi
Abstract:
Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under various external perturbations such as laser fields. In this work, we present a novel approach to accelerate real time TDDFT based electron dynamics simulations using autoregressive neural operators as time-propagators for the electron density. By leveraging physics-informed constraints…
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Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under various external perturbations such as laser fields. In this work, we present a novel approach to accelerate real time TDDFT based electron dynamics simulations using autoregressive neural operators as time-propagators for the electron density. By leveraging physics-informed constraints and high-resolution training data, our model achieves superior accuracy and computational speed compared to traditional numerical solvers. We demonstrate the effectiveness of our model on a class of one-dimensional diatomic molecules. This method has potential in enabling real-time, on-the-fly modeling of laser-irradiated molecules and materials with varying experimental parameters.
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Submitted 25 July, 2024; v1 submitted 12 July, 2024;
originally announced July 2024.
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A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry
Authors:
Lenz Fiedler,
Karan Shah,
Michael Bussmann,
Attila Cangi
Abstract:
With the growth of computational resources, the scope of electronic structure simulations has increased greatly. Artificial intelligence and robust data analysis hold the promise to accelerate large-scale simulations and their analysis to hitherto unattainable scales. Machine learning is a rapidly growing field for the processing of such complex datasets. It has recently gained traction in the dom…
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With the growth of computational resources, the scope of electronic structure simulations has increased greatly. Artificial intelligence and robust data analysis hold the promise to accelerate large-scale simulations and their analysis to hitherto unattainable scales. Machine learning is a rapidly growing field for the processing of such complex datasets. It has recently gained traction in the domain of electronic structure simulations, where density functional theory takes the prominent role of the most widely used electronic structure method. Thus, DFT calculations represent one of the largest loads on academic high-performance computing systems across the world. Accelerating these with machine learning can reduce the resources required and enables simulations of larger systems. Hence, the combination of density functional theory and machine learning has the potential to rapidly advance electronic structure applications such as in-silico materials discovery and the search for new chemical reaction pathways. We provide the theoretical background of both density functional theory and machine learning on a generally accessible level. This serves as the basis of our comprehensive review including research articles up to December 2020 in chemistry and materials science that employ machine-learning techniques. In our analysis, we categorize the body of research into main threads and extract impactful results. We conclude our review with an outlook on exciting research directions in terms of a citation analysis.
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Submitted 25 February, 2022; v1 submitted 3 October, 2021;
originally announced October 2021.
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On the length scale dependence of DNA conformational change under local perturbation
Authors:
Soumyadip Banerjee,
Kushal Shah,
Shaunak Sen
Abstract:
Conformational change of a DNA molecule is frequently observed in multiple biological processes and has been modelled using a chain of strongly coupled oscillators with a nonlinear bistable potential. While the mechanism and properties of conformational change in the model have been investigated and several reduced order models developed, the conformational dynamics as a function of the length of…
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Conformational change of a DNA molecule is frequently observed in multiple biological processes and has been modelled using a chain of strongly coupled oscillators with a nonlinear bistable potential. While the mechanism and properties of conformational change in the model have been investigated and several reduced order models developed, the conformational dynamics as a function of the length of the oscillator chain is relatively less clear. To address this, we used a modified Lindstedt-Poincare method and numerical computations. We calculate a perturbation expansion of the frequency of the model's nonzero modes, finding that approximating these modes with their unperturbed dynamics, as in a previous reduced order model, may not hold when the length of the DNA model increases. We investigate the conformational change to local perturbation in models of varying lengths, finding that for chosen input and parameters, there are two regions of DNA length in the model, first where the minimum energy required to undergo the conformational change increases with DNA length; and second, where it is almost independent of the length of the DNA model. We analyze the conformational change in these models by adding randomness to the local perturbation, finding that the tendency of the system to remain in a stable conformation against random perturbation decreases with an increase in the DNA length. These results should help to understand the role of the length of a DNA molecule in influencing its conformational dynamics.
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Submitted 6 August, 2020; v1 submitted 12 November, 2019;
originally announced November 2019.
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Mesoscale Organization and Dynamics in Binary Ionic Liquid Mixtures
Authors:
Tyler Cosby,
Utkarsh Kapoor,
Jindal K. Shah,
Joshua Sangoro
Abstract:
The impact of mesoscale organization on dynamics and ion transport in binary ionic liquid mixtures is investigated by broadband dielectric spectroscopy, dynamic-mechanical spectroscopy, x-ray scattering, and molecular dynamics simulations. The mixtures are found to form distinct liquids with macroscopic properties that significantly deviate from weighted contributions of the neat components. For i…
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The impact of mesoscale organization on dynamics and ion transport in binary ionic liquid mixtures is investigated by broadband dielectric spectroscopy, dynamic-mechanical spectroscopy, x-ray scattering, and molecular dynamics simulations. The mixtures are found to form distinct liquids with macroscopic properties that significantly deviate from weighted contributions of the neat components. For instance, it is shown that the mesoscale morphologies in ionic liquids can be tuned by mixing to enhance the static dielectric permittivity of the resulting liquid by as high as 100$\%$ relative to the neat ionic liquid components. This enhancement is attributed to the intricate role of interfacial dynamics associated with the changes in the mesoscopic aggregate morphologies in these systems. These results demonstrate the potential to design the physicochemical properties of ionic liquids through control of solvophobic aggregation
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Submitted 7 May, 2019;
originally announced May 2019.
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Evidence of robust 2D transport and Efros-Shklovskii variable range hopping in disordered topological insulator (Bi2Se3) nanowires
Authors:
Biplab Bhattacharyya,
Alka Sharma,
Bhavesh Sinha,
Kunjal Shah,
Suhas Jejurikar,
T. D. Senguttuvan,
Sudhir Husale
Abstract:
We report the experimental observation of variable range hopping conduction in focused-ion-beam (FIB) fabricated ultra-narrow nanowires of topological insulator (Bi2Se3). The value of the exponent in the hopping equation was extracted as ~ 1/2 for different widths of nanowires, which is the proof of the presence of Efros-Shklovskii hopping transport mechanism in a strongly disordered system. High…
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We report the experimental observation of variable range hopping conduction in focused-ion-beam (FIB) fabricated ultra-narrow nanowires of topological insulator (Bi2Se3). The value of the exponent in the hopping equation was extracted as ~ 1/2 for different widths of nanowires, which is the proof of the presence of Efros-Shklovskii hopping transport mechanism in a strongly disordered system. High localization lengths (0.5nm, 20nm) were calculated for the devices. A careful analysis of the temperature dependent fluctuations present in the magnetoresistance curves, using the standard Universal Conductance Fluctuation theory, indicates the presence of 2D topological surface states. Also, the surface state contribution to the conductance was found very close to one conductance quantum. We believe that our experimental findings shed light on the understanding of quantum transport in disordered topological insulator based nanostructures.
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Submitted 16 August, 2017; v1 submitted 16 August, 2017;
originally announced August 2017.
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Analysis and validation of low-frequency noise reduction in MOSFET circuits using variable duty cycle switched biasing
Authors:
Kapil Jainwal,
Mukul Sarkar,
Kushal Shah
Abstract:
Randomization of the trap state of defects present at the gate Si-SiO$_2$ interface of MOSFET is responsible for the low-frequency noise phenomena such as Random Telegraph Signal (RTS), burst, and 1/\textit{f} noise. In a previous work, theoretical modelling and analysis of the RTS noise in MOS transistor was presented and it was shown that this 1/\textit{f} noise can be reduced by decreasing the…
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Randomization of the trap state of defects present at the gate Si-SiO$_2$ interface of MOSFET is responsible for the low-frequency noise phenomena such as Random Telegraph Signal (RTS), burst, and 1/\textit{f} noise. In a previous work, theoretical modelling and analysis of the RTS noise in MOS transistor was presented and it was shown that this 1/\textit{f} noise can be reduced by decreasing the duty cycle ($f_{D}$) of switched biasing signal. In this paper, an extended analysis of this 1/\textit{f} noise reduction model is presented and it is shown that the RTS noise reduction is accompanied with shift in the corner frequency ($f_{c}$) of the 1/\textit{f} noise and the value of shift is a function of continuous ON time ({$T_{on}$}) of the device. This 1/\textit{f} noise reduction is also experimentally demonstrated in this paper using a circuit configuration with multiple identical transistor stages which produces a continuous output instead of a discrete signal. The circuit is implemented in 180~nm standard CMOS technology, from UMC. According to the measurement results, the proposed technique reduces the 1/\textit{f} noise by approximately 5.9 dB at $f_{s}$ of 1~KHz for 2 stage, which is extended up to 16 dB at $f_{s}$ of 5 MHz for 6 stage configuration.
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Submitted 4 April, 2017;
originally announced April 2017.
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The Removal of Single Layers from Multi-Layer Graphene by Low Energy Electron Stimulation
Authors:
Jason D. Jones,
Rakesh K. Shah,
Guido F. Verbeck,
Jose M. Perez
Abstract:
The removal of single atomic layers from multi-layer graphene using a He plasma is reported. By applying sample biases of -60 and +60 V during He plasma exposure, layer removal is found to be due to electrons instead of He ions or neutrals in the plasma. The rate of layer removal depends on exposure time, sample bias and pre-annealing treatments. Optical contrast microscopy and atomic force micros…
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The removal of single atomic layers from multi-layer graphene using a He plasma is reported. By applying sample biases of -60 and +60 V during He plasma exposure, layer removal is found to be due to electrons instead of He ions or neutrals in the plasma. The rate of layer removal depends on exposure time, sample bias and pre-annealing treatments. Optical contrast microscopy and atomic force microscopy studies show that the removal of C atoms occurs approximately one layer at a time across the entire multi-layer sample with no observable production of large pits or reduction in lateral dimensions. Layer removal is proposed to arise from the electron-stimulated dissociation of C atoms from the basal plane. This process differs from plasma techniques that use reactive species to etch multi-layer graphene.
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Submitted 15 February, 2012;
originally announced February 2012.
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Tailoring the physical properties of poly(3-Hexylthiophene) thin films using electro-spray deposition
Authors:
M. Ali,
M. Abbas,
S. K. Shah,
E. Bontempi,
P. Colombi,
A. Di Cicco,
R. Gunnella
Abstract:
Structural and electronic properties of homogeneous poly(3-Hexylthiophene) (P3HT) films ob- tained from the electro-spray method were presented by means of grazing incidence x-ray diffrac- tion, atomic force microscopy, optical absorption, photoelectron spectroscopy and (photo)electrical conductivity. Different structural conformations were obtained starting from different solution con- centration…
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Structural and electronic properties of homogeneous poly(3-Hexylthiophene) (P3HT) films ob- tained from the electro-spray method were presented by means of grazing incidence x-ray diffrac- tion, atomic force microscopy, optical absorption, photoelectron spectroscopy and (photo)electrical conductivity. Different structural conformations were obtained starting from different solution con- centrations and flow rate conditions. The electro-spray method was shown to effectively expand the control of the conformation and assembling of the polymers films, opening the way to the possibility of tailoring film characteristics according to device specifications.
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Submitted 28 June, 2011;
originally announced June 2011.
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Water coordination structures and the excess free energy of the liquid
Authors:
Safir Merchant,
Jindal K. Shah,
D. Asthagiri
Abstract:
For a distinguished water molecule, the solute water, we assess the contribution of each coordination state to its excess chemical potential, using a molecular aufbau approach. In this approach, we define a coordination sphere, the inner-shell, and separate the excess chemical potential into packing, outer-shell, and local chemical contributions; the coordination state is defined by the number of…
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For a distinguished water molecule, the solute water, we assess the contribution of each coordination state to its excess chemical potential, using a molecular aufbau approach. In this approach, we define a coordination sphere, the inner-shell, and separate the excess chemical potential into packing, outer-shell, and local chemical contributions; the coordination state is defined by the number of solvent water molecules within the coordination sphere. The packing term accounts for the free energy of creating a solute-free coordination sphere in the liquid. The outer-shell term accounts for the interaction of the solute with the fluid outside the coordination sphere and it is accurately described by a Gaussian model of hydration for coordination radii greater than the minimum of the oxygen-oxygen pair correlation function. Consistent with the conventional radial cut-off used for defining hydrogen-bonds in liquid water, theory helps identify a chemically meaningful coordination radius. The local chemical contribution is recast as a sum over coordination states. The n-th term in this sum is given by the probability of observing n water molecules inside the coordination sphere in the absence of the solute water times a factor accounting for the interaction of the solute with the inner-shell solvent water molecules. Using this molecular aufbau expansion, we monitor the change in the chemical contribution due to the incremental increase in n. We find that though four water molecules are needed to fully account for the chemical term, the first added water accounts for nearly half the chemical term. Our results emphasize the need to acknowledge the intrinsic occupancy of a solute-free coordination sphere together with solute-solvent interactions in rationalizing the tetrahedral coordination of the solute water.
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Submitted 5 January, 2011;
originally announced January 2011.
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Anisotropic weakly localized transport in nitrogen-doped ultrananocrystalline diamond films
Authors:
Kunjal V Shah,
Dmitry Churochkin,
Zivayi Chiguvare,
Somnath Bhattacharyya
Abstract:
We establish the dominant effect of anisotropic weak localization (WL) in three dimensions associated with a propagative Fermi surface, on the conductivity correction in heavily nitrogen doped ultrananocrystalline diamond (UNCD) films based on magneto-resistance studies at low temperatures. Also, low temperature electrical conductivity can show weakly localized transport in 3D combined with the ef…
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We establish the dominant effect of anisotropic weak localization (WL) in three dimensions associated with a propagative Fermi surface, on the conductivity correction in heavily nitrogen doped ultrananocrystalline diamond (UNCD) films based on magneto-resistance studies at low temperatures. Also, low temperature electrical conductivity can show weakly localized transport in 3D combined with the effect of electron-electron interactions in these materials, which is remarkably different from the conductivity in 2DWL or strong localization regime. The corresponding dephasing time of electronic wavefunctions in these systems described as ~ T^-p with p < 1, follows a relatively weak temperature dependence compared to the generally expected nature for bulk dirty metals having $p \geq 1$. The temperature dependence of Hall (electron) mobility together with an enhanced electron density has been used to interpret the unusual magneto-transport features and show delocalized electronic transport in these n-type UNCD films, which can be described as low-dimensional superlattice structures.
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Submitted 24 November, 2010; v1 submitted 22 July, 2010;
originally announced July 2010.
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The sinusoid and the phasor
Authors:
Kushal Shah,
Harishankar Ramachandran
Abstract:
Mathieu equation is widely used to study several natural phenomenon. In this paper, we show that replacing the sinusoid in the Mathieu equation with a phasor can lead to solutions that behave in a totally different way. Solutions of Mathieu equation are either bounded or grow unboundedly at an exponential rate. Solutions of this new equation are always unbounded and grow linearly with time.
Mathieu equation is widely used to study several natural phenomenon. In this paper, we show that replacing the sinusoid in the Mathieu equation with a phasor can lead to solutions that behave in a totally different way. Solutions of Mathieu equation are either bounded or grow unboundedly at an exponential rate. Solutions of this new equation are always unbounded and grow linearly with time.
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Submitted 10 June, 2010; v1 submitted 8 June, 2010;
originally announced June 2010.