Non-ideal Effects Research Articles

Smart pH Sensing: A Self-Sensitivity Programmable Platform with Multi-Functional Charge-Trap-Flash ISFET Technology

This study presents a novel pH sensor platform utilizing charge-trap-flash-type metal oxide semiconductor field-effect transistors (CTF-type MOSFETs) for enhanced sensitivity and self-amplification. Traditional ion-sensitive field-effect transistors (ISFETs) face challenges in commercialization due to low sensitivity at room temperature, known as the Nernst limit. To overcome this limitation, we explore resistive coupling effects and CTF-type MOSFETs, allowing for flexible adjustment of the amplification ratio. The platform adopts a unique approach, employing CTF-type MOSFETs as both transducers and resistors, ensuring efficient sensitivity control. An extended-gate (EG) structure is implemented to enhance cost-effectiveness and increase the overall lifespan of the sensor platform by preventing direct contact between analytes and the transducer. The proposed pH sensor platform demonstrates effective sensitivity control at various amplification ratios. Stability and reliability are validated by investigating non-ideal effects, including hysteresis and drift. The CTF-type MOSFETs’ electrical characteristics, energy band diagrams, and programmable resistance modulation are thoroughly characterized. The results showcase remarkable stability, even under prolonged and repetitive operations, indicating the platform’s potential for accurate pH detection in diverse environments. This study contributes a robust and stable alternative for detecting micro-potential analytes, with promising applications in health management and point-of-care settings.

Mancha3D Code: Multipurpose Advanced Nonideal MHD Code for High-Resolution Simulations in Astrophysics

The Mancha3D code is a versatile tool for numerical simulations of magnetohydrodynamic (MHD) processes in solar/stellar atmospheres. The code includes nonideal physics derived from plasma partial ionization, a realistic equation of state and radiative transfer, which allows performing high-quality realistic simulations of magnetoconvection, as well as idealized simulations of particular processes, such as wave propagation, instabilities or energetic events. The paper summarizes the equations and methods used in the Mancha3D (Multifluid (-purpose -physics -dimensional) Advanced Non-ideal MHD Code for High resolution simulations in Astrophysics 3D) code. It also describes its numerical stability and parallel performance and efficiency. The code is based on a finite difference discretization and a memory-saving Runge–Kutta (RK) scheme. It handles nonideal effects through super-time-stepping and Hall diffusion schemes, and takes into account thermal conduction by solving an additional hyperbolic equation for the heat flux. The code is easily configurable to perform different kinds of simulations. Several examples of the code usage are given. It is demonstrated that splitting variables into equilibrium and perturbation parts is essential for simulations of wave propagation in a static background. A perfectly matched layer (PML) boundary condition built into the code greatly facilitates a nonreflective open boundary implementation. Spatial filtering is an important numerical remedy to eliminate grid-size perturbations enhancing the code stability. Parallel performance analysis reveals that the code is strongly memory bound, which is a natural consequence of the numerical techniques used, such as split variables and PML boundary conditions. Both strong and weak scalings show adequate performance up to several thousands of processors (CPUs).

Noise tailoring, noise annealing, and external perturbation injection strategies in memristive Hopfield neural networks

The commercial introduction of a novel electronic device is often preceded by a lengthy material optimization phase devoted to the suppression of device noise as much as possible. The emergence of novel computing architectures, however, triggers a paradigm shift in noise engineering, demonstrating that non-suppressed but properly tailored noise can be harvested as a computational resource in probabilistic computing schemes. Such a strategy was recently realized on the hardware level in memristive Hopfield neural networks, delivering fast and highly energy efficient optimization performance. Inspired by these achievements, we perform a thorough analysis of simulated memristive Hopfield neural networks relying on realistic noise characteristics acquired on various memristive devices. These characteristics highlight the possibility of orders of magnitude variations in the noise level depending on the material choice as well as on the resistance state (and the corresponding active region volume) of the devices. Our simulations separate the effects of various device non-idealities on the operation of the Hopfield neural network by investigating the role of the programming accuracy as well as the noise-type and noise amplitude of the ON and OFF states. Relying on these results, we propose optimized noise tailoring and noise annealing strategies, comparing the impact of internal noise to the effect of external perturbation injection schemes.

Protoplanetary Disk Size under Nonideal Magnetohydrodynamics: A General Formalism with Inclined Magnetic Field

Many mechanisms have been proposed to alleviate the magnetic catastrophe, which prevents the Keplerian disk from forming inside a collapsing magnetized core. Such propositions include inclined field and nonideal magnetohydrodynamics effects, and have been supported with numerical experiments. Models have been formulated for typical disk sizes when a field threads the rotating disk, parallel to the rotation axis, while observations at the core scales do not seem to show evident correlation between the directions of angular momentum and the magnetic field. In the present study, we propose a new model that considers both vertical and horizontal fields and discuss their effects on the protoplanetary disk size.

An MPM-Based Phase-Field Simulation of Plating and Stripping of Lithium with a Solid Electrolyte Interphase

A methodology for performing phase-field simulations of plating and stripping in the presence of a solid electrolyte interphase (SEI) is presented and applied to a lithium metal electrode. Material point method (MPM) simulations are performed assuming a homogeneous SEI layer and are compared with experiment. Results are consistent with experiment for two electrolytes and confirm the dominance of the SEI layer in determining cell impedance. Notably, in some instances, the SEI potential drop greatly affected activation overpotential, differing from the applied potential. To accurately depict stripping current vs potential for SEI-free systems, the model considered non-ideal electrolyte effects: concentration-dependent salt activity coefficient, salt diffusion coefficient, and electrolyte conductivity. Conversely, systems with SEI layers displayed minimal non-ideal concentration-related electrolyte effects due to impedance originating primarily from the SEI. In plating scenarios, low SEI salt concentration negated the need for non-ideal SEI effects. However, for stripping, non-ideal salt-concentration dependent SEI effects were crucial in reproducing experimental behavior, owing to high salt concentration at the electrode/SEI interface.

Linearisation of Digital-to-Analog Converters by Model Predictive Control

Digital-to-analog converters (DACs) are used to reconstruct digital quantised signals in the analog domain. Practical DACs exhibit several non-ideal effects; principally integral non-linearity (INL). INL is caused by element mismatch, meaning actual output levels deviate from the ideal, causing distortion. To reduce this error, a method employing moving horizon optimal control is proposed, where INL has been integrated into the model. The model is built by precisely measuring the INL of the physical device and organising the data into a lookup table. Previous attempts at using moving horizon optimal quantiser (MHOQ) have assumed ideal quantisation and are therefore unable to reduce the impact of INL. Several other methods exist that can linearise and mitigate the impact of INL but have significant drawbacks, such as a lack of guaranteed stability, complexity, and the need to use specialised and custom circuit topologies that cannot be replicated with of-the-shelf equipment. The effectiveness of the proposed method is demonstrated via simulations and experiments on an of-the-shelf DAC.

Polarizabilities of the negative ions of hydrogen and positronium in nonideal classical plasmas

We investigate the polarizability of the negative ions of hydrogen and positronium embedded in nonideal classical plasmas using correlated exponential wavefunctions. The interactions among the charged particles in plasmas have been taken care of by a pseudopotential, derived from a solution of Bogolyubov's hierarchy equations. The effects of nonideality of plasma on the ground state energies and the static and dynamic dipole polarizabilities of the negative ions have been studied in detail for wide range of nonideality. The results show interesting features.

Effect of non-ideal mixture on flame–spray interaction in counterflow n-heptane/ethanol flames

This work presents a numerical study of bi-component n-heptane/ethanol spray flames in a counterflow to improve the understanding of the effect of non-ideal mixtures on the flame–spray interaction. The simulations of this spray configuration allow for the detailed examination of the real fluid behavior and its influence on gas-phase combustion kinetics for a wide range of relevant parameters, i.e., droplet composition, size, and gas strain rate. The results reveal that due to the large real activity coefficient of n-heptane and the resulting selective evaporation of the heavier component, the burning characteristics of the spray with a high initial ethanol content do not differ if non-ideal mixture is considered. Conversely, the flame structure with a low ethanol content is substantially different, and displacement of the flame towards the spray side of the configuration is found. A multiple reaction zone, displaying both partially-premixed and diffusion flames, exists, which is overestimated spatially if the fluid is assumed ideal. In general, the ideal prediction of real fluid would misinterpret the composition evaporation order, prolonging the droplet lifetime and consequently, enhancing the flame–spray interaction locally, which results in a lower flame temperature. A parameter characterizing the multicomponent droplet penetration is introduced, which highlights the appreciable non-ideal effects that vary with droplet size and composition, and most importantly, further demonstrates the necessity of considering the real fluid properties in design of next-generation engines with blended fuels.

Investigation of non-ideal effects in compressible boundary layers of dense vapors through direct numerical simulations

In this work, we present an investigation about the sources of dissipation in adiabatic boundary layers of non-ideal compressible fluid flows. Direct numerical simulations (DNS) of transitional, zero-pressure gradient boundary layer flows are performed for two fluids characterized by different complexity of the fluid molecules, namely, “air” and siloxane MM. Different sets of thermodynamic free-stream boundary conditions are selected to evaluate the influence of the fluid state on both the frictional loss and the dissipation mechanisms. The thermophysical properties of siloxane MM are calculated with a state-of-the-art equation of state. Results show that the dissipation due to both time-mean strain field, irreversible heat transfer, and turbulent dissipation differs significantly depending on both the molecular complexity of the fluid and its thermodynamic state. The dissipation coefficient calculated from the DNS results is then compared against the one obtained using a reduced-order model (ROM), which solves the two-dimensional boundary layer flow equations for an arbitrary fluid [M. Pini and C. De Servi, “Entropy generation in laminar boundary layers of non-ideal fluid flows,” in 2nd International Seminar on Non-Ideal Compressible Fluid Dynamics for Propulsion and Power (Springer, 2020), pp. 104–117]. Results from both the DNS and the ROM show that low values of the overall dissipation are observed in the case of fluids made of simple molecules, e.g., air, and if the fluid is at a thermodynamic state in the proximity of that of the vapor–liquid critical point.

Smoothed particle magnetohydrodynamics

Smoothed particle magnetohydrodynamics has reached a level of maturity that enables the study of a wide range of astrophysical problems. In this review, the numerical details of the modern SPMHD method are described. The three fundamental components of SPMHD are methods to evolve the magnetic field in time, calculate accelerations from the magnetic field, and maintain the divergence-free constraint on the magnetic field (no monopoles). The connection between these three requirements in SPMHD will be highlighted throughout. The focus of this review is on the methods that work well in practice, with discussion on why they work well and other approaches do not. Numerical instabilities will be discussed, as well as strategies to overcome them. The inclusion of non-ideal MHD effects will be presented. A prospective outlook on possible avenues for further improvements will be discussed.

Structural and Adsorption Properties of ZIF-8-7 Hybrid Materials Synthesized by Acid Gas-Assisted and De Novo Routes.

The tuning of micropore environments in zeolitic imidazolate frameworks (ZIFs) by mixed-linker synthesis has the potential for enabling new molecular separation properties. However, de novo synthesis of mixed-linker (hybrid) ZIFs is often challenging due to the disparate chemical properties of the different linkers. Here, we elucidate the structure and properties of an unconventional ZIF-8-7 hybrid material synthesized via a controlled-acid-gas-assisted degradation and reconstruction (solvent-assisted crystal redemption, SACRed) strategy. Selective insertion of benzimidazole (ZIF-7 linker) into ZIF-8 using SACRed is used as a facile method to generate a ZIF-8-7 hybrid material that is otherwise difficult to synthesize by de novo methods. Detailed crystal structure and textural characterizations clarify the significant differences in the microstructure of the SACRed-derived ZIF-8-7 hybrid material relative to a de novo synthesized hybrid of the same overall linker composition as well as the parent ZIF-8 material. Unary and binary adsorption measurements reveal the tunability of adsorption characteristics as well as the prevalence of nonideal cooperative mixture adsorption effects that lead to large deviations from predictions made with ideal adsorbed solution theory.

The origins of nonideality exhibited by monoclonal antibodies and Fab fragments in human serum.

The development of therapeutic antibodies remains challenging, time-consuming, and expensive. A key contributing factor is a lack of understanding of how proteins are affected by complex biological environments such as serum and plasma. Nonideality due to attractive or repulsive interactions with cosolutes can alter the stability, aggregation propensity, and binding interactions of proteins in solution. Fluorescence correlation spectroscopy (FCS) can be used to measure apparent second virial coefficient (B2,app ) values for therapeutic and model monoclonal antibodies (mAbs) that capture the nature and strength of interactions with cosolutes directly in undiluted serum and similar complex biological media. Here, we use FCS-derived B2,app measurements to identify the components of human serum responsible for nonideal interactions with mAbs and Fab fragments. Most mAbs exhibit neutral or slightly attractive interactions with intact serum. Generally, mAbs display repulsive interactions with albumin and mildly attractive interactions with IgGs in the context of whole serum. Crucially, however, these attractive interactions are much stronger with pooled IgGs isolated from other serum components, indicating that the effects of serum nonideality can only be understood by studying the intact medium (rather than isolated components). Moreover, Fab fragments universally exhibited more attractive interactions than their parental mAbs, potentially rendering them more susceptible to nonideality-driven perturbations. FCS-based B2,app measurements have the potential to advance our understanding of how physiological environments impact protein-based therapeutics in general. Furthermore, incorporating such assays into preclinical biologics development may help de-risk molecules and make for a faster and more efficient development process.

SpikeSim: An End-to-End Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks

Spiking Neural Networks (SNNs) are an active research domain towards energy efficient machine intelligence. Compared to conventional artificial neural networks (ANNs), SNNs use temporal spike data and bio-plausible neuronal activation functions such as Leaky-Integrate Fire/Integrate Fire (LIF/IF) for data processing. However, SNNs incur significant dot-product operations causing high memory and computation overhead in standard von-Neumann computing platforms. To this end, In-Memory Computing (IMC) architectures have been proposed to alleviate the “memory-wall bottleneck" prevalent in von-Neumann architectures. Although recent works have proposed IMC-based SNN hardware accelerators, the following key implementation aspects have been overlooked 1) the adverse effects of crossbar non-ideality on SNN performance due to repeated analog dot-product operations over multiple time-steps 2) hardware overheads of essential SNN-specific components such as the LIF/IF and data communication modules. To this end, we propose SpikeSim, a tool that can perform realistic performance, energy, latency and area evaluation of IMC-mapped SNNs. SpikeSim consists of a practical monolithic IMC architecture called SpikeFlow for mapping SNNs. Additionally, the non-ideality computation engine (NICE) and energy-latency-area (ELA) engine performs hardware-realistic evaluation of SpikeFlow-mapped SNNs. Based on 65nm CMOS implementation and experiments on CIFAR10, CIFAR100 and TinyImagenet datasets, we find that the LIF/IF neuronal module has significant area contribution (>11% of the total hardware area). To this end, we propose SNN topological modifications that leads to 1.24× and 10× reduction in the neuronal module’s area and the overall energy-delay-product value, respectively. Furthermore, in this work, we perform a holistic comparison between IMC implemented ANN and SNNs and conclude that lower number of time-steps are the key to achieve higher throughput and energy-efficiency for SNNs compared to 4-bit ANNs. The code repository for the SpikeSim tool is available at https://github.com/Intelligent-Computing-Lab-Yale/Quanitzation-aware-SNN-training-and-hardware-evaluation-for-IMC-Architectures

A Memristor Crossbar-Based Lyapunov Equation Solver

An analog memristor crossbar based Lyapunov equation solver is proposed in this paper. It is an extension of memristor crossbar linear equation solver, but taking into account of the regularity with Lyapunov equation in the organization of crossbar. Nonideal effects due to co-design with CMOS analog circuits are studied in detail. Verification using a Verilog-AMS tool is performed to justify that with proper scaling on the memristor conductance values and other circuit signals, the solution quality of Lyapunov matrix equation can be improved.

Supercritical Carbon Dioxide Shock Behavior Near the Critical Point

Abstract This paper aims to provide an understanding of sCO2 inviscid adiabatic normal shock behavior near the critical point and to develop an explicit tool for faster prediction of the shock relations that can aid the supercritical turbomachinery design process. An iterative algorithm was developed to compute shockwave behaviors for nonideal fluids. Three important shock behavior parameters were investigated: postshock Mach number, shock strength, and polytropic efficiency. A comparative study was carried out between air (ideal gas assumption), ideal gas CO2 (ideal gas assumption), and nonideal fluid CO2 (Span–Wagner equation of state). The distinct differences show the inadequacy of the perfect gas shock relations when predicting sCO2 shock behavior near the critical point. The results of nonideal fluid calculations show a general trend of stronger shock strengths and higher polytropic efficiencies toward lower preshock entropy conditions. This is also distinctive near the critical point due to the reduced speed of sound. Finally, explicit expressions for these parameters were retrieved using symbolic regression. The fitted models have significant improvements compared to the prediction from perfect gas shock relations with a 5–20% point reduction in relative errors. This study also shows the potential for machine learning to be applied in nonideal fluid effects modeling and the methodology developed in this paper can be easily introduced to other working fluids in their ranges of interest.

CO Laser Absorption Measurements During Syngas Combustion at High Pressure

Abstract Syngas is a desirable fuel for combustion in the Allam-Fetvedt cycle, which involves combustion under supercritical-CO2 conditions. While some work has been conducted in collecting ignition delay times (IDT) at the extreme pressures required by these systems, significant model deficiencies remain. Additionally, considerable barriers in terms of nonideal gas dynamic effects have been shown for these experiments in shock tubes. Further investigation into the fundamental combustion kinetics of H2/CO/CO2 mixtures is required. Time-resolved speciation measurements for target species have been shown to better aid in improving the understanding of underlying chemical kinetics than global ignition delay time measurements. Therefore, laser absorption measurements of CO were measured behind reflected shock waves during combustion of syngas at 5 and 10 bar and temperatures between 1080 and 2100 K. The mixtures investigated utilized H2-to-CO ratios of 1:1 and 1:4, respectively, each at stoichiometric conditions, allowing for discussions of the effect of initial fuel composition. A ratio of fuel to CO2 of 1:2 was also utilized to represent commercially available syngas. The mixtures were diluted in helium and argon (20% He, 76.5% Ar) to minimize thermal effects and to expedite CO thermal relaxation during the experiment. The resulting CO time histories were then compared to modern chemical kinetics mechanisms, and disagreement is seen for this system, which is assumed to be fairly well known. This study elucidates particular chemistry that needs improvement in moving toward a better understanding of syngas combustion at elevated pressures.

Stability analysis of alpha driven toroidal Alfvén eigenmodes observed in JET deuterium-tritium internal transport barrier plasmas

A toroidal Alfvén eigenmode (TAE) has been observed to be driven by alpha particles in a JET deuterium-tritium internal transport barrier plasma. The observation occurred 50 ms after the removal of neutral beam heating (NBI). The mode is observed on magnetics, soft-xray, interferometry and reflectometry measurements. We present detailed stability calculations using a similar tool set validated during deuterium only discharges. These calculations strongly support the conclusion that the observed mode is a TAE, and that this mode was destabilized by alpha particles. Non-ideal effects from the bulk plasma are interpreted as responsible for suppressing the majority of TAEs which were also driven by alpha particles, but the modes that match the observations are predicted to be particularly weak for these non-ideal effects. This mode located far from the core on the outboard midplane is found to be driven by both trapped and passing particles despite alpha particles originating in the core.

Toroidal Alfvén eigenmodes observed in low power JET deuterium–tritium plasmas

The Joint European Torus recently carried out an experimental campaign using a plasma consisting of both deuterium (D) and tritium (T). We observed a high-frequency mode using a reflectometer and an interferometer in a D-T plasma heated with low power neutral beam injection, . This mode was observed at a frequency and was located at major radii . The observed mode was identified as a toroidal Alfvén eigenmode (TAE) using the linear MHD code, MISHKA. Beam ions and fusion-born alpha particles were modelled using the full orbit particle tracking code LOCUST, which produces smooth distribution functions suitable for stability calculations without analytical fits or the use of moments. We calculated the stability of the 21 candidate modes using the HALO code. These calculations revealed that beam ions can drive TAEs with toroidal mode numbers with linear growth rates , while TAEs with n < 8 are damped by the beam ion population. Alpha particles drive modes with significantly smaller linear growth rates, due to the low alpha power generated almost exclusively by beam-thermal fusion reactions. Non-ideal effects were calculated using complex resistivity in the CASTOR code, leading to an assessment of radiative, collisional, and continuum damping for all 21 candidate modes. Ion Landau damping was modelled using Maxwellian distribution functions for bulk D and T ions in HALO. Radiative damping, the dominant bulk damping mechanism, suppresses modes with high toroidal mode numbers. Comparing the drive from energetic particles with damping from thermal particles, we find all but one of the candidate modes are damped. The single net-driven n = 9 TAE with a net growth rate matches experimental observations with a lab frequency and location . The TAE was driven by co-passing particles through the resonance. Both co- and counter-passing alpha particles drive the TAE through the resonance. Additional sideband resonances contribute significant drive for both beam and alpha particles.

3D simulations of magnetoconvection in a rapidly rotating supernova progenitor

ABSTRACT We present a first 3D magnetohydrodynamic (MHD) simulation of oxygen, neon, and carbon shell burning in a rapidly rotating $16\hbox{-}\mathrm{M}_\odot$ core-collapse supernova progenitor. We also run a purely hydrodynamic simulation for comparison. After $\mathord \approx 180\mathrm{s}$ ($\mathord \approx$ 15 and 7 convective turnovers, respectively), the magnetic fields in the oxygen and neon shells achieve saturation at 1011 and 5 × 1010 G. The strong Maxwell stresses become comparable to the radial Reynolds stresses and eventually suppress convection. The suppression of mixing by convection and shear instabilities results in the depletion of fuel at the base of the burning regions, so that the burning shell eventually move outward to cooler regions, thus reducing the energy generation rate. The strong magnetic fields efficiently transport angular momentum outwards, quickly spinning down the rapidly rotating convective oxygen and neon shells and forcing them into rigid rotation. The hydrodynamic model shows complicated redistribution of angular momentum and develops regions of retrograde rotation at the base of the convective shells. We discuss implications of our results for stellar evolution and for the subsequent core-collapse supernova. The rapid redistribution of angular momentum in the MHD model casts some doubt on the possibility of retaining significant core angular momentum for explosions driven by millisecond magnetars. However, findings from multidimensional models remain tentative until stellar evolution calculations can provide more consistent rotation profiles and estimates of magnetic field strengths to initialize multidimensional simulations without substantial numerical transients. We also stress the need for longer simulations, resolution studies, and an investigation of non-ideal effects.

Effects of volatility, viscosity, and non-ideality on particle–particle mixing timescales of secondary organic aerosols

Effects of volatility, viscosity, and non-ideality on particle–particle mixing timescales of secondary organic aerosols