The effect of heat treatment on the corrosion resistance of 440C stainless steel in 20% HNO<Subscript>3</Subscript> + 2.5% Na<Subscript>2</Subscript>Cr<Subscript>2</Subscript>O<Subscript>7</Subscript> solution

The effect of heat treatment on the corrosion resistance of 440C stainless steel was investigated in a 20% HNO₃ + 2.5% Na₂Cr₂O₇ solution using electrochemical noise (ECN) measurements, electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM) examinations. The noise resistance (Rn), which has been found to be inversely related to the localized corrosion rate, was measured to be 5.7E + 08 Ω-cm², 4.2E + 08 Ω-cm², and 3.7E + 04 Ω-cm² for the oil-quenched, air-quenched, and vacuum furnace cooled (VFC) samples, respectively, after 1200 s exposures. The Rn for all heat treat conditions stabilized within a range of 1.0E + 07 Ω-cm² to 3.2E + 08 Ω-cm² after 2 h exposures. The EIS response showed a polarization resistance (R _p) on the order of 6.6E + 04 Ω-cm², 5.3E + 04 Ω-cm², and 1.1E + 04 Ω-cm² for the oil-quenched, air-quenched, and VFC samples, respectively, after 2 h exposures. The EIS data are in good agreement with ECN data and indicate that after longer exposures, general corrosion mechanisms dominate and the corrosion rates are comparable. SEM examinations of specimens subjected to 1200 s exposures revealed that severity of pitting and intergranular corrosion damage was consistent with trends in the Rn data. Specifically, the electrochemical noise data as well as SEM examinations of specimens revealed a higher localized corrosion resistance of the hardened specimens during the early stages of passivation. This greater resistance to localized corrosion can be attributed to an increased stability of the natural passive film resulting from a higher concentration of chromium atoms in solution for the martensite phase.     

Bias optimization of 2.4 GHz double gate MOSFET RF mixer

The optimum biasing points and structural design parameters for novel nano-scale double gate MOSFET (DG-MOSFET) radio frequency mixers are investigated at 2.4 GHz. Our objective is to analyze and identify the correlation of the conversion gain of the mixer circuit with the signal amplitude of the local oscillator (LO) as well as different device parameters, such as the gate length (L _gate ), doping concentration (N _A ) and body thickness (t _Si ), thus minimizing signal loss and power consumption and increasing stability. The most important figure of merit is found to be the LO DC bias that determines the level of non-linearity in the transconductance response. Furthermore, we observe that in properly designed DG-MOSFETs $(\hbox{L}_{gate} \ge 3t_{Si}),\; \hbox{L}_{gate}$ and N _A have limited impact on the conversion gain of the mixer, while t _Si has a more significant role to play. Although the mixing performance of DG-MOSFETs is ultimately limited by the short channel effects perpetrated by any given structural constraint, an optimum body thickness t _Si exists in each case to maximize the conversion gain. Thus, we illustrate how 2D and quantum-corrected simulations can identify the optimum body thickness and optimum bias conditions in such compact nano-scale mixers.     

Electro-Chemical Modeling Challenges of Biological Ion Pumps

We outline the basic operational, structural and functional features of ion motive ATPases: trans-membrane proteins central to biological functions of all animal cells. As an example we discuss the modeling problems associated with the operation of the surface membrane Na⁺,K⁺-ATPase and skeletal muscle sarcoplasmic reticulum Ca²⁺-ATPase and focus on the frameworks required for their solution. There are three basic problems: identification of the pathway for ion permeation, prediction of ion binding rate coefficients and affinities based on the structure of the protein, and prediction of conformational changes of protein structure and the associated movement of charges within the membrane dielectric. A solution strategy useful in approaching the first two problems and preliminary results obtained using molecular dynamics simulations are also presented.Supported by NIH grant NS22979.     

Search for Optimum and Scalable COSMOS

We introduce a novel CMOS device architecture capable of building complementary logic operation using only a single gate stack. The new architecture, named complementary orthogonal stacked MOS (COSMOS), places the n and p-MOSFETs perpendicular to one another under a single gate, integrating them vertically as well as laterally. The COSMOS architecture would not only mean significant savings in active device area of a conventional static CMOS pair, but also significant reductions in RC device parasitics. We demonstrate how the device may be built, operated and optimized for symmetric operation, as well as verifying logic NOT operation via 3D device simulations. COSMOS architecture appears to have peculiar scaling trends such as increasing threshold at reduced gate dimensions. The increase in drive voltages lead to faster operation at the expense of higher static leakage and loss of noise margins.     

Removal of nitrate from water by electroreduction and electrocoagulation.

The aim of this work was to investigate the feasibility of the removal of nitrate from water by applying electrochemical methods such as electroreduction and electrocoagulation. In electroreduction, removal of nitrate to an allowable concentration has been accomplished at the pH range of 5-7 with energy consumption value of 1 x 10(-3) kWh g(-1). In electrocoagulation, an allowable concentration of nitrate has been achieved at the pH range of 9-11 with energy consumption value of 0.5 x 10(-4) kWh g(-1). Full removal of nitrate was also possible but with higher energy consumptions for these two methods.     

Analysing robot swarm behaviour via probabilistic model checking

An alternative to deploying a single robot of high complexity can be to utilise robot swarms comprising large numbers of identical, and much simpler, robots. Such swarms have been shown to be adaptable, fault-tolerant and widely applicable. However, designing individual robot algorithms to ensure effective and correct overall swarm behaviour is actually very difficult. While mechanisms for assessing the effectiveness of any swarm algorithm before deployment are essential, such mechanisms have traditionally involved either computational simulations of swarm behaviour, or experiments with robot swarms themselves. However, such simulations or experiments cannot, by their nature, analyse all possible swarm behaviours. In this paper, we will develop and apply the use of automated probabilistic formal verification techniques to robot swarms, involving an exhaustive mathematical analysis, in order to assess whether swarms will indeed behave as required. In particular we consider a foraging robot scenario to which we apply probabilistic model checking.     

Corrosion of Type 7075-T73 Aluminum in a 10% HNO3 + Fe2(SO4)3 Deoxidizer Solution

Localized corrosion damage in Type 7075-T73 aluminum was investigated for a HNO₃ + Fe₂(SO₄)₃ deoxidizer solution which is frequently used for surface pretreatment prior to anodizing. The corrosion damage was quantified in the time domain using the electrochemical noise resistance (Rn) and in the frequency domain using the spectral noise impedance (Rsn). The Rsn was derived from an equivalent electrical circuit model that represented the corrosion cell implemented in the present study. These data are correlated to scanning electron microscopy (SEM) examinations and corresponding statistical analysis based on digital image analysis of the corroded surfaces. Other data used to better understand the corrosion mechanisms include the open circuit potential (OCP) and coupling-current time records. Based on statistical analysis of the pit structures for 600 and 1200 s exposures, the best fit was achieved with a 3-paramater lognormal distribution. It was observed for the 1200 s exposure that a small population of pits continued to grow beyond a threshold critical size of 10 μm. In addition, significant grain boundary attack was observed after 1200 s exposure. These data are in good agreement with the electrochemical data. Specifically, the Rn was computed to be 295 and 96 Ω-cm² for 600 and 1200 s exposures, respectively. The calculated value of Rsn, theoretically shown to be equal to Rn in the low frequency limit, was higher than Rn for a 1200 s exposure period. However, better agreement between the Rn and Rsn was found for frequencies above 0.01 Hz. Experimental results on the measurement performance for potassium chloride (KCl) saturated double-junction Ag/AgCl and single-junction Hg/Hg₂Cl₂ reference electrodes in the low-pH deoxidizer solution are also compared.     

Ab Initio Insight into the Interaction of Metal-Decorated Fluorinated Carbon Fullerenes with Anti-COVID Drugs

We theoretically investigated the adsorption of two common anti-COVID drugs, favipiravir and chloroquine, on fluorinated C₆₀ fullerene, decorated with metal ions Cr³⁺, Fe²⁺, Fe³⁺, Ni²⁺. We focused on the effect of fluoridation on the interaction of fullerene with metal ions and drugs in an aqueous solution. We considered three model systems, C₆₀, C₆₀F₂ and C₆₀F₄₈, and represented pristine, low-fluorinated and high-fluorinated fullerenes, respectively. Adsorption energies, deformation of fullerene and drug molecules, frontier molecular orbitals and vibrational spectra were investigated in detail. We found that different drugs and different ions interacted differently with fluorinated fullerenes. Cr³⁺ and Fe²⁺ ions lead to the defluorination of low-fluorinated fullerenes. Favipiravir also leads to their defluorination with the formation of HF molecules. Therefore, fluorinated fullerenes are not suitable for the delivery of favipiravir and similar drugs molecules. In contrast, we found that fluorine enhances the adsorption of Ni²⁺ and Fe³⁺ ions on fullerene and their activity to chloroquine. Ni²⁺-decorated fluorinated fullerenes were found to be stable and suitable carriers for the loading of chloroquine. Clear shifts of infrared, ultraviolet and visible spectra can provide control over the loading of chloroquine on Ni²⁺-doped fluorinated fullerenes.     

Feedback controls on urban air pollution

A conceptual frame of reference for viewing the various functions of an air pollution control agency in a metropolitan area is the conventional feedback-control diagram. A series of such diagrams is presented and discussed, to indicate a possible sequence of developmental stages through which an integrated system may evolve.     

Forecasting Ambient Air SO2 Concentrations Using Artificial Neural Networks

An Artificial Neural Networks (ANNs) model is constructed to forecast SO₂ concentrations in Izmir air. The model uses meteorological variables (wind speed and temperature) and measured particulate matter concentrations as input variables. The correlation coefficient between observed and forecasted concentrations is 0.94 for the network that uses all three variables as input parameters. The root mean square error value of the model is 3.60 μg/mt³. Considering the limited number of available input variables, model performances show that ANNs are a promising method of modeling to forecast ambient air SO₂ concentrations in Izmir.