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In this work report a physics based compact model of drain current for III-V-on-Insulator MOS transistor. The quantum confinement effect is been correctly incorporated using triangular potential well approximation. This model captures the variation of Fermi level, inversion carrier density and energy level of 1st sub-band with gate voltage inside quantum well. Our proposed model shows good agreement between modeling and TCAD simulation results. We implement the model in Verilog A environment and use in SPICE simulation framework. Our model predicted results match well with experimental data.

Bacteria are ubiquitous and it is reported that among them surface attached bacteria is over 99% population wise. However, the attached growth or sessile life of bacteria poses a different problem in human life. Chronic infection, contamination in food industries and biofouling in industrial materials are serious challenges which need to overcome. It is imperative to understand the bacterial adhesion and subsequent biofilm development to study biofilm-associated deceases and mitigating biofouling. In the present book chapter, the technical know-how of bacterial biofilm development has been depicted. A thorough understanding of the fundamental principles of bacterial biofilm would help to perceive new aspects of biofouling and pathogenicity associated with biofilm and how fouling could be controlled and contamination can be prevented. In this chapter, parameters affecting biofilm formation, the role of extracellular polymeric substances (EPS) and eDNA, the factors of materials which influence attachment and detachment of biofilm have been clearly described. The present chapter highlights the major factors involved in the signaling system to promote Biofilm formation.

Biofouling is a serious drawback found in technological tools exposed in an aqueous medium; it plays a significant role in selecting suitable materials used in a different industrial application like food processing industry, shipping yards, water treatment and desalting tools; consequently, it has huge impact viability and economic feasibility of those systems. Biofouling includes organic fouling, particulate/colloidal fouling and fouling occurred due to microbial/biological entities. The present chapters dealt about bacterial mediated biofouling. Bacterial-mediated biofouling represents the “Achilles heel” due to bacteria’s ability to multiply over time; this type of biofouling is potentially more dangerous. An iota of living cells attached to the surface can grow and form biofilms using the dissolve organic substances in the water. Bacterial biofouling is recently gaining much interest due to it’s severe economic and environmental adverse effects. In the present book chapter, the different types of biofouling and their causes have been highlighted. A thorough understanding of the fundamental principles of biofilm generation would help to prevent biofouling. Basics of biofilm development causing fouling and the factors affecting fouling have been depicted. A short discussion about the means to mitigate biofouling has been provided. The present chapters also described different anti-biofouling strategies adapted to in various industrial tools. A brief description of the influence of biofouling in water treatment, food processing, and biomedical devices has been provided. Advantages and disadvantages of bacterial-mediated biofouling have been discussed.

Ever increasing energy demand has induced fossil fuel consumption, consequently pollution and global warming driving the world towards an unprecedented high and potentially devastating energy crisis. Therefore, water and energy securities are considered as major concerns in present scenario. Organic waste/wastewater signifies as a potential renewable feedstock to generate various forms of bioenergy aside from the remediation process by regulating the biological process. Bioenergy has gained significant attention as a sustainable and futuristic alternative to fossil fuels. Using waste for bioenergy through its remediation has instigated considerable interest and has further opened a new avenue for the use of renewable and inexhaustible energy sources. Therefore, the field of wastewater management and alternative energy are the most unexplored fields of Biotechnology and Science (Massoud et al. 2009). Microbial fuel cell (MFC) is gaining popularity as a promising tool for simultaneous waste treatment and current generation without polluting environment. The complete breakdown of a wide range of organic substrates to carbon dioxide and water is usually only possible with several enzymatic reaction steps which is easily achieved in MFCs (Logan 2008). Though research on MFCs was initiated in the 1960s during NASA’s space explorations, rapid gain in MFC research was observed during the last two decades.

Microbial desalination cells (MDCs) are bioelectrochemical tools which exploit organic matter in wastewater to use as an energy source for desalinating salt water. These cells desalinate water by expending the electric potential gradient established by exoelectrogenic bacteria to drive ion transport through a series of ion exchange membranes (Kim and Logan 2013). This device has the potential to solve the world’s freshwater crisis. As such, a significant increase in the number of installed desalination capacities were noticed since the 1980s (Greenlee et al. 2009). However, conventional technology of desalination consumes high amounts of energy which is a matter of concern as the stocks of fossil fuels are rapidly depleting. Theoretically, if we consider a thermodynamically reversible process at 50% water recovery, the minimum energy required for desalination of typical sea water is approximately 1 kWh m−3. The most efficient systems of seawater desalination using reverse osmosis have achieved an energy requirement of only 1.8–2.2 kWh m−3. However, considering the energy needs for pre-treatment, pumping, etc., the overall consumption stands at about 3–4 kWh m−3, which is not efficient at all (Liu et al. 2011). MDCs have emerged as a solution to this problem because they accomplish environment friendly wastewater treatment and at the same time they drastically diminish the energy expenditure for desalination (Cao et al. 2009).

The present study demonstrated the feasibility of using an integrated approach of combining dark fermentation with MFCs to maximize the energy recovery from cellulosic substrate. Thermophillic dark-H2 fermentation exhibited maximum H2 production yield of 2.92 mol mol−1 hexose equivalent with an energy recovery of 28% which was highest reported till date. The total cumulative hydrogen potential of 3799 mL L−1 with maximum rate of hydrogen production of 865 mL h−1, and lag time of 1.84 h were determined by using modified Gompertz equation. Subsequent use of acid rich effluents in two chamber MFCs generated maximum power density of 85.05 mW m−2 with an energy recovery of 2.49%. Moreover, a 75% COD removal was also achieved with a coulombic efficiency of 13% illustrating its ability for wastewater treatment. By using this integrated approach, an overall energy recovery of 30.49% was achieved demonstrating both environmental and economic sustainability of the process.

An electrochemically active bacteria Pseudomonas aeruginosa IIT BT SS1 was isolated from a dark fermentative spent media fed anode, and a bioaugmentation technique using the isolated strain was used to improve the start-up time of a microbial fuel cell (MFC). Higher volumetric current density and lower start-up time were observed with the augmented system MFC-PM (13.7 A/m3) when compared with mixed culture MFC-M (8.72 A/m3) during the initial phase. This enhanced performance in MFC-PM was possibly due to the improvement in electron transfer ability by the augmented strain. However, pure culture MFC-P showed maximum volumetric current density (17 A/m3) due to the inherent electrogenic properties of Pseudomonas sp. An electrochemical impedance spectroscopic (EIS) study, along with matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) analysis, supported the influence of isolated species in improving the MFC performance. The present study indicates that the bioaugmentation strategy using the isolated Pseudomonas sp. can be effectively utilized to decrease the start-up time of MFC.

The present study deals with the preparation and characterization of low cost custom made KOH doped polyvinyl alcohol (PVA)–polydiallyldimethylammonium chloride (PDDA) anion exchange membranes (AEM). The synthesized membrane was used as a separator in single chambered microbial fuel cells (sMFCs). The membranes were characterized in terms of proton conductivity, oxygen diffusion, and ion exchange ability. The performance of sMFCs with newly prepared AEM separator was evaluated with respect to operating voltage and COD removal. Higher volumetric power density was achieved in case of PVA–PDDA composite membrane as compared to PVA–STA cation exchange membrane and commercial Ralex AEM mainly due to low internal resistance and less biofouling. The effect of PDDA content in composite membrane was evaluated in terms of current density and coulombic efficiency. The PDDA blending in membrane had significant influence on the reduction of impedance (improvement in anionic conductivity) and biofouling. A maximum power density of 6.68 W/m3 was obtained when Shewanella putrefaciens was used in lactate medium fed sMFC equipped with PVA–PDDA based MCA. Power output increased with membrane cathode assembly (MCA) surface area. An optimized quantity (0.5 mg/cm2) of 1% (w/v) PVA solution was found to be effective as suitable binder. PVA–PDDA composite membrane exhibited as a suitable alternative to the costly membrane commonly used in the MFC.

Biofouling commonly occurs on carbonaceous capacitive deionization electrodes in the process of treating natural waters. Although previous work reported the effect of electric fields on bacterial mortality for a variety of medical and engineered applications, the effect of electrode surface properties and the magnitude and polarity of applied electric fields on biofilm development has not been comprehensively investigated. This paper studies the formation of a Pseudomonas aeruginosa biofilm on a Papyex graphite (PA) and a carbon aerogel (CA) in the presence and the absence of an electric field. The experiments were conducted using a two-electrode flow cell with a voltage window of ±0.9 V. The CA was less susceptible to biofilm formation compared to the PA due to its lower surface roughness, lower hydrophobicity, and significant antimicrobial properties. For both positive and negative applied potentials, we observed an inverse relationship between biofilm formation and the magnitude of the applied potential. The effect is particularly strong for the CA electrodes and may be a result of cumulative effects between material toxicity and the stress experienced by cells at high applied potentials. Under the applied potentials for both electrodes, high production of endogenous reactive oxygen species (ROS) was indicative of bacterial stress. For both electrodes, the elevated specific ROS activity was lowest for the open circuit potential condition, elevated when cathodically and anodically polarized, and highest for the ±0.9 V cases. These high applied potentials are believed to affect the redox potential across the cell membrane and disrupt redox homeostasis, thereby inhibiting bacterial growth.

In this paper we present a simple model to study the threshold voltage variability due to line edge roughness (LER) for an n-channel EδDC MOS transistor. The concept of propagation of variance is utilized here. Impact of variation in rms amplitude and correlation length of edge fluctuation on threshold voltage variability is studied. The model is verified with calibrated technology computer aided design (TCAD) simulation results. Impact of channel engineering for reduction of LER induced threshold voltage variability is studied in detail.

Algae are single or multicellular photosynthetic organisms that can fix the atmospheric carbon into valuable lipids, proteins, carbohydrates, and fats. These algae are also capable of growing vigorously in different habitats from freshwater to brackish water environments and wastewater streams with nutrient uptake ability. These features make the algae themselves uniquely important in biofuel generation and wastewater treatment process along with CO2 sequestrations without competing with food crop land. The algae can also be used as a substrate for various biofuel generations, bioethanol, bio-butanol, hydrogen, methane, and many commercially valuable products. The applicability and renewability of algal fuel are most promising for the future biotechnological applications. Optimization of algal growth conditions and harvesting technology with desired biofuel generations at low processing cost can make the algae as one of the best sources of energy for future generations. Genetically modified algae which are capable to grow rapidly with generating high cellular lipids and carbohydrate content can be crucial for future energy demand.

Water and energy securities are emerging as increasingly important and vital issues for today’s world. Therefore, the field of wastewater management and alternative energy is one of the most unexplored fields of Biotechnology and Science. Microbial fuel cell (MFC) is emerging as a modern wastewater treatment technology which converts chemical energy stored in the bonds of organic matter present in wastewater directly into electricity using electrogenic bacteria as a catalyst, without causing environmental pollution. In this chapter, the technical know-how of MFC and biocatalyst has been depicted. A thorough understanding of the fundamental principles of microbial fuel cells would help to perceive new aspects of bioenergy conversions and how such systems could be integrated with the present energy generation systems to maximize the energy recovery. In this respect, MFCs show promise to treat wastewater with simultaneous production of renewable energy. In this chapter, the theories underlying the electron transfer mechanisms, the biochemistry and the microbiology involved, and the material characteristics of anode, cathode, and the separator have been clearly described. This chapter highlights the major factors involved toward the improvement bioelectricity production processes. Advance in the design of MFC Technology and the economy of the process are also included.

In recent years, hydrogen (H2) has emerged as a clean and attractive substitute fuel since it can be produced from renewable energy sources. Upon combustion of hydrogen, it generates only water as a major by-product. In hydrogen and fuel cell technology, hydrogen can be applied in fuel cell technology; it produces only water as a major by-product with high energy yield, hold great potential for meeting in a quite unique way by empowering the so-called hydrogen-based economy. To make hydrogen-based economy viable, it is crucial to use renewable resources in place of fossil fuels to produce hydrogen. In this direction, by considering attractive and renewable characteristics of hydrogen led us to improve a variety of biological processes for the production of hydrogen. Nonetheless, commercialization of the biological process depends on improvements in process design along with an understanding of the nature of hydrogen producing communities and process optimization. Thus, this chapter highlights the major factors involved towards the improvement of biohydrogen production processes. Environmental impact of hydrogen as carbon-neutral energy carrier is also discussed. This also includes a technical and economic analysis of the biohydrogen and its role in the proposed hydrogen economy coupled with fuel cell and in transport application. Technological advancements based on hydrogen-based fuel cell designs and process integration approaches are also discussed.

Behavioral modeling of a new type of seismic sensor referred to as Differential Inductive Seismic (DIS) sensor for monitoring of seismic frequencies that are very close to the natural frequencies of buildings and other structures is presented in this paper. The model is validated by finite element method analysis using COMSOL Multiphysics 4.3a results show that the DIS sensor is highly selective to vibrations at resonance frequency and has good sensitivity and noise immunity. The sensor emulator and its readout circuit (ROC) are physically implemented on Texas Instruments (TI) ASLK PRO board. The ROC faithfully retrieves the single-tone seismic signal.

The field of wastewater management and alternative energy are one of the most unexplored fields of environmental biotechnology. The biomethane is considered as renewable natural gas which can be derived from organic waste and sewage treatment. In recent past biomethane is emerging as a promising gaseous fuel utilized in a cogeneration or trigeneration power plant. Biomethane usually produced through anaerobic digestion in oxygen-deficient environment where a series of microorganisms convert the complex waste to biogas via liquefaction through a cascade of enzymes. Biomethane produced in anaerobic digester can be utilized for decentralized power generation, and additionally revenue can be gained in the form of a CO2 credits and/or other greenhouse gas emission credits. In the present book chapter, the technical know-how of anaerobic digestion and biocatalyst associated with digester has been depicted. A thorough understanding of the fundamental principles of anaerobic digestion would help to perceive new aspects of bioenergy conversions. The book chapter highlights the concise of biochemistry for biomethane production as well as important major factors involved in the process toward the realization of a stable biomethane-based economy. Successful application of anaerobic digester was found in pilot-scale potential wastewater treatment along with renewable energy production. The proper configuration anaerobic digester and efficiently pretreated “feedstock” are key to maximize the production of methane. Therefore, basics of reactor design designs based on process economy have been discussed.

Epitaxial delta-doped channel (EδDC) profile is a promising approach for extending the scalability of bulk metal oxide semiconductor (MOS) technology for low-power system-on-chip applications. A comparative study between EδDC bulk MOS transistor with gate length Lg = 22 nm and a conventional uniformly doped channel (UDC) bulk MOS transistor, with respect to various digital and analogue performances, is presented. The study has been performed using Silvaco technology computer-aided design device simulator, calibrated with experimental results. This study reveals that at smaller gate length, EδDC transistor outperforms the UDC transistor with respect to various studied performances. The reduced contribution of the lateral electric field in the channel plays the key role in this regard. Further, the carrier mobility in EδDC transistor is higher compared to UDC transistor. For moderate gate and drain bias, the impact ionisation rate of the carriers for EδDC MOS transistor is lower than that of the UDC transis...

Three different approaches were employed to improve single chambered microbial fuel cell (sMFC) performance using Shewanella putrefaciens as biocatalyst. Taguchi design was used to identify the key process parameter (anolyte concentration, CaCl₂ and initial anolyte pH) for maximization of volumetric power. Supplementation of CaCl₂ was found most significant and maximum power density of 4.92 W/m(3) was achieved. In subsequent approaches, effect on power output by riboflavin supplementation to anolyte and anode surface modification using nano-hematite (Fe₂O₃) was observed. Volumetric power density was increased by 44% with addition of 100 nM riboflavin to anolyte while with 0.8 mg/cm(2) nano-Fe₂O₃ impregnated anode power density and columbic efficiency increased by 40% and 33% respectively. Cyclic voltammetry revealed improvement in electrochemical activity of Shewanella with nano-Fe₂O₃ loading and electrochemical impedance depicted inverse relationship between charge transfer resistance and nano-Fe₂O₃ loading. This study suggests anodic improvement strategies for maximization of power output.

Manganese cobaltite nanorods (MnCo2O4 NRs) were prepared and tested as potential air-cathode catalyst for the single-chambered microbial fuel cells (sMFC). The power generation of sMFC increases with MnCo2O4 NRs loading to the cathode. The Polypyrrole (PPy) and Vulcan XC were used as conducting support to the MnCo2O4 NRs to form composites either by in situ or by mechanical mixing in the cathode fabrication. The cyclic voltammetry, linear sweep voltammetry and electrochemical impedance studies reveal that the in situ-MnCo2O4 NRs/PPy composite has higher catalytic activity than that of mechanically mixed-MnCo2O4NRs/PPy composite because of higher interfacial contact between MnCo2O4 NRs and PPy. The maximum volumetric power density with in situ-MnCo2O4 NRs/PPy, mechanically mixed-MnCo2O4 NRs/PPy, MnCo2O4 NRs/Vulcan XC and catalyst-free (only Vulcan XC) cathode was measured to be 6.11, 5.05, 4.22, and 1.77 W/m(3), respectively, in the sMFC. This suggests that PPy is not only a better conducting support than that of conventionally used Vulcan XC but also the cathode composite fabrication process is important for enhanced performance. The synergetic effect of MnCo2O4 NRs and PPy was found to play an important role for the improved energy recovery and it could be applied as an efficient and inexpensive cathode catalyst for the sMFC.

A major limitation associated with fermentative hydrogen production is the low substrate conversion efficiency. This limitation can be overcome by integrating the process with a microbial fuel cell (MFC) which converts the residual energy of the substrate to electricity. Studies were carried out to check the feasibility of this integration. Biohydrogen was produced from the fermentation of cane molasses in both batch and continuous modes. A maximum yield of about 8.23 mol H2/kg CODremoved was observed in the batch process compared to 11.6 mol H2/kg CODremoved in the continuous process. The spent fermentation media was then used as a substrate in an MFC for electricity generation. The MFC parameters such as the initial anolyte pH, the substrate concentration and the effect of pre-treatment were studied and optimized to maximize coulombic efficiency. Reductions in COD and total carbohydrates were about 85% and 88% respectively. A power output of 3.02 W/m3 was obtained with an anolyte pH of 7.5 using alkali pre-treated spent media. The results show that integrating a MFC with dark fermentation is a promising way to utilize the substrate energy.

The present study deals with the development and application of a proton-exchange polymer membrane separator consisting of graphene oxide (GO), poly(vinyl alcohol) (PVA), and silicotungstic acid (STA) in a single-chambered microbial fuel cell (sMFC). GO and the prepared membranes were characterized by FT-IR spectroscopy, XRD, SEM, TEM, and AC impedance analysis. Higher power was achieved with a 0.5 wt % GO-incorporated PVA–STA–GO membrane compared to a Nafion 117 membrane. The effects of oxygen crossover and membrane-cathode-assembly (MCA) area were evaluated in terms of current density and Coulombic efficiency. The electrochemical behavior of the membrane in an MFC was improved by adding different amounts of GO to the membrane to reduce biofouling and also to enhance proton conductivity. A maximum power density of 1.9 W/m3 was obtained when acetate wastewater was treated in an sMFC equipped with a PVA–STA–GO-based MCA. Therefore, PVA–STA–GO could be utilized as an efficient and inexpensive separator for ...

Performance of two-chambered microbial fuel cells (MFCs) using anion exchange membrane (AEM) was evaluated under batch mode with Shewanella putrefaciens in Luria broth. Maximum voltage and power density using Nafion and Ralex AEM were 0.676 V and 0.729 V and 39.2 ± 7.39 mW/m 2 and 57.8 ± 5.509 mW/m 2 respectively. Cathodic half cell potential was monitored along with cathodic pH and the results revealed that low power density was achieved in case of Nafion as compared to Ralex AEM mainly due to pH imbalance associated voltage losses using small external resistance of the same. Metabolite loss in AEM was found at higher current density which limits the Coulombic efficiency and power generation. A three parameters optimization showed that surface area of cathode had significant effect on the power generation. Effect of anode surface area, dissolve oxygen (DO) in catholyte and electrode spacing on power production were evaluated using AEM membrane.

This paper presents a technique for the modeling and design of a nano scale CMOS inverter circuit using artificial neural network and particle swarm optimization algorithm such that the switching characteristics of the circuit is symmetric, that is, has nearly equal rise and fall time and equal output high-to-low and low-to-high propagation delay. The channel width of the transistors and the load capacitor value are taken as design parameters. The designed circuit has been implemented at the transistor-level and simulated using TSPICE for 45 nm process technology. The PSO-generated results have been compared with SPICE results. A very good accuracy has been achieved. In addition, the advantage of the present approach over an existing approach for the same purpose has been demonstrated through simulation results.

The performance of the cathodic electron acceptors (CEA) used in the two-chambered microbial fuel cell (MFC) was in the following order: potassium permanganate (1.11V; 116.2 mW/m(2))>potassium persulfate (1.10 V; 101.7 mW/m(2))>potassium dichromate, K(2)Cr(2)O(7) (0.76 V; 45.9 mW/m(2))>potassium ferricyanide (0.78 V; 40.6 mW/m(2)). Different operational parameters were considered to find out the performance of the MFC like initial pH in aqueous solutions, concentrations of the electron acceptors, phosphate buffer and aeration. Potassium persulfate was found to be more suitable out of the four electron acceptors which had a higher open circuit potential (OCP) but sustained the voltage for a much longer period than permanganate. Chemical oxygen demand (COD) reduction of 59% was achieved using 10mM persulfate in a batch process. RALEX™ AEM-PES, an anion exchange membrane (AEM), performed better in terms of power density and OCP in comparison to Nafion®117 Cation Exchange Membrane (CEM).

This paper presents an automated procedure for generation of high-level topologies for continuous-time @S@D modulator system. A functional topology of the system is generated from the given transfer function model of the modulator. Mathematical transformation technique is applied iteratively over the initial topology to generate a functional topology which is optimized for modulator sensitivity, hardware complexity and relative power consumption. This is then implemented using behavioral models of operational transconductance amplifiers and capacitors. The generated high-level topology is ensured to work with reasonable accuracy under non-ideal conditions. The entire procedure has been implemented in Matlab/Simulink environment. Numerical results have been provided to demonstrate the procedure.

This paper presents an exploration procedure for mapping given functional specifications of an analog system to the specification parameters of individual component blocks of the system topology. A meet-in-the-middle approach has been followed for constructing the feasible design space. It is constructed as the intersection of an application-bounded specification space and a circuit-realizable specification space. The least squares support vector machine principle is used to accurately identify the actual geometry of the feasible design space. The reduced design space speeds up the exploration procedure. The benefit of our methodology is the ability to obtain practically correct circuit-level specifications of the component blocks of the system in a single pass. The effectiveness of the procedure has been demonstrated by considering a complete system. The simulation results satisfy the desired specifications of the system, validating the overall procedure.

Electrical equivalent circuit of 20 amino acids are realized based on their codons composition. The circuit is designed in Spice domain and 64 codons are realized using MOSFET to characterized amino acids based on their electrical responses.

In this paper with the help of technology computer-aided design (TCAD) simulation we present comparative study of analog and RF performance of an UTBOI- Si Substrate MOS transistor for two different channel materials: Si and InGaAs (with and without buffer). We have analyzed different analog and RF figure of merits such as transconductance, transconductance generation factor, output conductance, intrinsic gain and unity gain cut-off frequency. UTB-OI MOS transistor with InGaAs channel shows significant improvement in both analog and RF performance compared to that using Silicon channel. Addition of buffer layer further improves analog and RF performance.

The reliance on conventional fossil fuels has resulted in the imminent energy catastrophe with the combined challenge of global warming and the depletion of these energy reserves (Nayak BK, Pandit S, Das D, Biohydrogen. In: Kennes C, Veiga ria C (eds) Air pollution prevention and control, Chapter 15, Wiley, pp 345–381, 2013). Our earth today is facing many environmental problems, ranging from pollution, global warming due to the accumulation of CO2 in the atmosphere, depletion of natural energy sources like coal and petroleum and the increasing need for sustainable energy sources (Bentley, Energy Policy, 30(3):189–205, 2002). Research on renewable methods for producing energy has received utmost attention in last few years. Standing in such a situation, the use of microalgae to convert CO2 into potential biomass coupled with their ability to produce oxygen gas, assumes strategic importance (Popp et al, Renew Sustain Energy Rev 32:559–578, 2014). Significant research is being carried out in this field to exploit this ability of microalgae and integrate it with microbial fuel cells. This integration becomes especially favourable considering the fact that the phototrophic organisms act as in-situ generators of oxygen which facilitate the reaction in cathode chamber of the MFC. Further, microalgae also effectively removes phosphorous and nitrogen from the wastewater which might not be possible solely by the MFCs (Rozendal et al, Trends Biotechnol, 26(8):450–459, 2008). The use of phototrophic organisms in MFCs leads to the development of photosynthetic microbial fuel cells or PMFCs (Rosenbaum et al, Curr Opin Biotechnol, 21(3):259–264, 2010).

Metal–Oxide–Semiconductor Field-Effect Transistor (MOSFET) has emerged over the last few decades as the basic building block of almost all computing devices. This steady growth of MOS transistors is attributed to the scaling of the underlying MOS technology which at present has reached the nanoscale (sub-90 nm) regime. Although the industry roadmap has suggested that the MOS transistor in its classical form is rapidly approaching toward some fundamental physical limits, yet many semiconductor industries prefer to use classical MOS transistor device structure because of the simplicity of operation and success of the use of such transistors in low cost-integrated circuits and systems.

This paper presents a comprehensive study of the reverse substrate bias effects of an n-channel epitaxial delta doped channel (EδDC) MOS transistor. The transistor consists of a two layered channel structure, a low doped epitaxial layer followed by a high doped screening layer. The study has been performed using Silvaco TCAD device simulator, calibrated with experimental results. Significant amount of substrate bias effect has been achieved in EδDC transistor in comparison to conventional uniform doped channel transistor (UDC), even for gate length as small as 22nm. The screening phenomenon of the depletion region leads to better control of the channel by substrate and is the key to enhanced substrate bias effect in EδDC transistor. The variations of leakage power dissipation and intrinsic delay with substrate bias have been compared for EδDC and UDC transistor. Significant amount of leakage power saving is achieved in EδDC transistor in comparison to UDC transistor, at the cost of reduced intrinsic speed. The dependence of the substrate sensitivity of the EδDC transistor on the epitxial region thickness and concentration of the high doped screening region has been investigated.

This paper presents the analytical models for the long channel and short channel threshold voltage of Deeply Depleted Channel (DDC) MOS transistor. The model predicted results are compared with TCAD simulation results. This paper also reports the comparative study of the analog performances of the DDC MOS transistor with those of a uniformly doped transistor. The TCAD tool is calibrated with published data of DDC MOS transistor. The better immunity of the DDC MOS transistor in comparison to the conventional bulk MOS transistor is demonstrated through simulation results.

The statistical variability of flicker noise for a nano-scale NMOS transistor due to intra-die variations in channel length, oxide thickness and mobility has been characterized. This has been done through theoretical estimations as well Monte Carlo-HSPICE simulation technique. BSIM-SPICE process parameters have been chosen for characterization purpose. The present work explicitly depicts the dependence of flicker noise variability on various causes of variability and device design parameters. 45 nm CMOS process technology has been considered in the present work. The theoretical model can be effectively used for statistical characterization which is essential for robust analog and RF circuit design.

This paper presents an improved g m /I D methodology for the design of low-power CMOS operational transconductance amplifier (OTA) circuit using nano-scale CMOS technology. This methodology takes into considerations the dependence of the Early voltage parameter with the bias points of a nano-scale MOS transistor. With such considerations, the DC voltage gain of the circuit can be controlled by adjusting the bias points of the transistors and keeping the channel length constant. The advantage of the improved methodology over the traditional methodology has been discussed and illustrated with simulation results.

This paper presents a semi analytical technique for estimating the effects of intra-die process variations on the performances of an nMOS transistor. The intra-die process variability sources considered in the work are Random Discrete Dopants (RDD), Channel Length Variation (CLV), Oxide Thickness Variation (OTV) and Mobility Fluctuation (MF). The analog performances which are studied are transconductance g m , intrinsic speed f t , thermal noise spectral density S n and flicker noise spectral density S f. The estimation technique is based on BSIMIV-SPICE process parameters. The mean and standard deviation of the performance variations are estimated. The estimated results are verified through Monte Carlo (MC)-HSPICE simulation results.

This paper presents an adaptive technique for generation of data required for construction of artificial neural network-based performance model of nano-scale CMOS inverter circuit. The training data are generated from the samples through SPICE simulation. The proposed algorithm has been compared to standard progressive sampling algorithms like arithmetic sampling and geometric sampling. The advantages of the present approach over the others have been demonstrated. The ANN predicted results have been compared with actual SPICE results. A very good accuracy has been obtained., {"references":["Georges.G.E. Gielen and Rob.A. Rutenbar. Computer-Aided Design of\nAnalog and Mixed-Signal Integrated Circuits. Proceedings of the IEEE,\nVol.88:pp.1825-1852, December 2000.","T. McConaghy and G. Gielen. Automation in Mixed-Signal Design:\nChallenges and Solutions in the Wake of the Nano Era. In Proc. of\nICCAD, pages 461-463, November 2006.","Rob.A. Rutenbar, Georges.G.E. Gielen, and J.Roychowdhury. Hierarchical\nModeling, Optimization, and Synthesis for System-Level Analog\nand RF Designs. Proceedings of the IEEE, Vol.95:pp.640-669, March\n2007.","W. Daems, G. Gielen, and W. Sansen. Simulation-Based Generation of\nPosynomial Performance Models for the Sizing of Analog Integrated\nCircuits. IEEE Trans. CADICS, Vol.22:pp.517-534, May 2003.","M. Avci and T. Yildirim. Neural Network Based MOS Transistor\nGeometry Decision for TSMC 0.18 Process Technology. In Proc. of\nICCS, pages 615-622, 2006.","F. Gunes, F. Gurgen, and G. Torpi, H. Signal-noise neural network\nmodel for active microwave devices. IEE Proceedings Circuits Devices\nand Systems, Vol.143:pp.1-8, 1996.","N. Kahraman and T. Yildirim. Technology Independent Circuit Sizing\nfor Fundamental Analog Circuits using Artificial Neural Networks. In\nProc. of PRIME, pages 1-4, 2008.","N. Kahraman and T. Yildirim. Technology independent circuit sizing\nfor standard cell based design using neural network. Digital Signal\nProcessing, Vol.19:pp.708-714, 2009.","F. Djeffala, M. Chahdib, A. Benhayaa, and M.L. Hafianea. An approach\nbased on neural computation to simulate the nanoscale CMOS circuit.\nSolid State Electronics, Vol.51:pp.48-56, 2007.\n[10] S.K. Mandal, S. Sural, and A. Patra. ANN-and PSO-Based Synthesis\nof On-Chip Spiral Inductors for RF ICs. IEEE Transaction CADICS,\nVol.27:pp.188-192, January 2008.\n[11] G.H. John and P. Langley. Static Versus Dynamic Sampling for Data\nMining. In Proc. of Knowledge Discovery and Data Mining, 1996.\n[12] F. Provost, D. Jensen, and T. Oates. Efficient Progressive Sampling. In\nProc. of Knowledge Discovery and Data Mining, pages 23-32, 1999.\n[13] C. Meek, B. Thiesson, and D. Heckerman. The Learning-Curve Sampling\nMethod Applied to Model-Based Clustering. Journal of Machine\nLearning Research, Vol.2:pp.397-418, February 2002.\n[14] A. Satyanarayana and I. Davidson. A Dynamic Adaptive Sampling\nAlgorithm for Real World Applications: Finger Print Recognition and\nFace Recognition. In Proc. of ISMIS, pages 631-640, 2005.\n[15] V.K. Devabhaktuni and Q.J. Zhang. Neural Network Training-Driven\nAdaptive Sampling Algorithm for Microwave Modeling. In Proc. of\nEuropean Microwave Conference, 2000.\n[16] G. Wolfe and R. Vemuri. Adaptive Sampling and Modeling of Analog\nCircuit Performance Parameters with Pseudo-Cubic Splines. In Proc. of\nICCAD, pages 931-836, 2004.\n[17] D. Dhabak and S. Pandit. Performance Modeling of Nano-scale CMOS\nInverter using Artificial Neural Network. In Proc. of IESPC, pages 33-\n36, 2011.\n[18] Q.J. Zhang, K.C. Gupta, and V.K. Devabhaktuni. Artificial Neural\nNetworks for RF and Microwave Design: From Theory to Practice. IEEE\nTrans. MTT, Vol.51:1339-1350, April 2003.\n[19] W. Zhao and Y. Cao. New Generation of Predictive Technology Model\nfor Sub-45 nm Early Design Exploration. IEEE Transactions Electron\nDevices, Vol.53:pp.2816-2823, November 2006.\n[20] L. Kuipers and H. Niederreiter. Uniform distribution of sequences. Dover\nPublications.\n[21] I. C. Yeh. Modeling of Strength of High-Performance Concrete\nusing Artificial Neural Network. Cement and Concrete Research,\nVol.28:pp.1797-1808, 1998.\n[22] http://archive.ics.uci.edu/ml/datasets/Concrete+Compressive+Strength."]}

Microbial carbon capture cells (MCCs) were constructed with cyanobacteria growing in a photo biocathode in dual-chambered flat plate mediator-less MFCs separated by an anion exchange membrane from the anode compartment containing Shewanella putrefaciens. The performance of the MCC with Anabaena sparged with CO(2)-air mixture was compared with that of a conventional cathode sparged with air only. The power densities achieved were 57.8 mW/m(2) for Anabaena sparged with a CO(2)-air mixture, 39.2 mW/m(2) for CO(2)-air mixture sparging only, 29.7 mW/m(2) for Anabaena sparged with air, and 19.6 mW/m(2) for air sparging only. The pH of the cathode containing Anabaena gradually increased from 7 to 9.12 and power generation decreased from 34.7 to 23.8 mW/m(2) 17 due to pH imbalance associated voltage losses without CO(2)-air mixture sparging. Sparging with a 5% CO(2)-air mixture produced maximum power of 100.1 mW/m(2). In addition, the power density of MCC increased by 31% when nitrate was added into the catholyte.

This paper presents a systematic methodology for the generation of high-level performance models for analog component blocks. The transistor sizes of the circuit-level implementations of the component blocks along with a set of geometry constraints applied over them define the sample space. A Halton sequence generator is used as a sampling algorithm. Performance data are generated by simulating each sampled circuit configuration through SPICE. Least squares support vector machine (LS-SVM) is used as a regression function. Optimal values of the model hyper parameters are determined through a grid search-based technique and a genetic algorithm- (GA-) based technique. The high-level models of the individual component blocks are combined analytically to construct the high-level model of a complete system. The constructed performance models have been used to implement a GA-based high-level topology sizing process. The advantages of the present methodology are that the constructed models are accurate with respect to real circuit-level simulation results, fast to evaluate, and have a good generalization ability. In addition, the model construction time is low and the construction process does not require any detailed knowledge of circuit design. The entire methodology has been demonstrated with a set of numerical results.

The variation of intra-die process parameters play a significant role in determining the yield of an analog/RF circuit. This paper presents statistical results demonstrating the effect of variations of process parameters on a nano-scale CMOS voltage controlled oscillator circuit. A statistical model relating the process parameter variations and the performance variations has been constructed using artificial neural network. The constructed model shows accuracy similar to that obtained though Monte Carlo analysis technique, however, consuming much less time.

In this paper, we study the effect of the variation of process parameters on the performance of a voltage controlled oscillator (VCO) and an inverter with technology scaling. The spread in performances is shown to be Gaussian in nature, considering the fact that the distributions of process parameters are also Gaussian in nature. The spreads in performances increase with technology scaling. These have been verified through HPSICE simulation results.