Circuit-level modelling and simulation of carbon nanotube devices

The growing academic interest in carbon nanotubes (CNTs) as a promising novel class of electronic materials has led to significant progress in the understanding of CNT physics including ballistic and non-ballistic electron transport characteristics. Together with the increasing amount of theoretical analysis and experimental studies into the properties of CNT transistors, the need for corresponding modelling techniques has also grown rapidly. This research is focused on the electron transport characteristics of CNT transistors, with the aim to develop efficient techniquesto model and simulate CNT devices for logic circuit analysis.The contributions of this research can be summarised as follows. Firstly, to accelerate the evaluation of the equations that model a CNT transistor, while maintaining high modelling accuracy, three efficient numerical techniques based on piece-wise linear, quadratic polynomial and cubic spline approximation have been developed. The numerical approximation simplifies the solution of the CNT transistor’s self-consistent voltage such that the calculation of the drain-source current is accelerated by at least two orders of magnitude. The numerical approach eliminates complicated calculations in the modelling process and facilitates the development of fast and efficient CNT transistor models for circuit simulation.Secondly, non-ballistic CNT transistors have been considered, and extended circuit-level models which can capture both ballistic and non-ballistic electron transport phenomena, including elastic scattering, phonon scattering, strain and tunnelling effects, have been developed. A salient feature of the developed models is their ability to incorporate both ballistic and non-ballistic transport mechanisms without a significant computational cost. The developed models have been extensively validated against reported transport theories of CNT transistors and experimental results.Thirdly, the proposed carbon nanotube transistor models have been implemented on several platforms. The underlying algorithms have been developed and tested in MATLAB, behaviourallevel models in VHDL-AMS, and improved circuit-level models have been implemented in two versions of the SPICE simulator. As the final contribution of this work, parameter variation analysis has been carried out in SPICE3 to study the performance of the proposed circuit-level CNT transistor models in logic circuit analysis. Typical circuits, including inverters and adders, have been analysed to determine the dependence of the circuit’s correct operation on CNT parameter variation

A Fast, Numerical Circuit-Level Model of Carbon Nanotube Transistor

Recently proposed circuit-level models of carbon nanotube transistor (CNT) for SPICE-like simulators suffer from numerical complexities as they rely on numerical evaluation of integrals or internal Newton-Raphson iterations to find solutions of non-linear dependencies or both. Recently an approach has been proposed which eliminates the need for numerical integration when calculating the charge densities in CNTFET through the use of piece-wise linear approximation. This paper builds on the effective employment of linear approximation to accelerate the CNT model speed when evaluating the source-drain current of the CNT, but rather than using symbolic solutions as reported, we propose to employ a numerical linearization of charge density dependence on the self-consistent voltage to obtain a dramatic reduction in the CPU time. Our results show a speed up of up to almost four orders of magnitude compared with the theoretical CNT model implemented in FETToy, used as a reference for verifying newer models. Comparisons of drain-source current characteristics of the new model against that in FETToy are presented, confirming the accuracy of the proposed approach

HSPICE implementation of a numerically efficient model of CNT transistor

This paper presents the algorithms of an implementation of a numerically efficient carbon nanotube transistor (CNT) model in HSPICE. The model is derived from cubic spline non-linear approximation of the non-equilibrium mobile charge density. The spline algorithm exploits a rapid and accurate solution of the numerical relationship between the charge density and the self-consistent voltage, which results in the acceleration of deriving the current through the channel without losing much accuracy. The output I-V characteristics of the proposed model have been compared with those of a recent HSPICE implementation of the Stanford CNT model and published experimental I-V curves. The results show superior accuracy of the proposed model while maintaining similar CPU time performance. Two versions of the HSPICE macromodel implementation have been developed and validated, one to reflect ballistic transport only and another with non-ballistic effects. To further validate the model a complementary logic inverter has also been implemented using the proposed technique and simulated in HSPICE

Quantifying the short-term dynamics of soil organic carbon decomposition using a power function model

Introduction Soil heterotrophic respiration (R h, an indicator of soil organic carbon decomposition) is an important carbon efflux of terrestrial ecosystems. However, the dynamics of soil R h and its empirical relations with climatic factors have not been well understood. Methods We incubated soils of three subtropical forests at five temperatures (10, 17, 24, 31, and 38 °C) and five moistures (20, 40, 60, 80, and 100% water holding capacity (WHC)) over 90 days. R h was measured throughout the course of the incubation. Three types of models (log-linear, exponential, and power model) were fitted to the measurements and evaluated based on the coefficient of determination (r 2) and Akaike Information Criterion (AIC) of the model. Further regression analysis was used to derive the empirical relations between model parameters and the two climatic factors. Results Among the three models, the power function model (R h = R 1 t −k) performed the best in fitting the descending trend of soil R h with incubation time (r 2 \u3e 0.69 for 26 of 30 models). Both R 1 and k generally increased linearly with soil temperature but varied quadratically with soil moisture in the three forest soils. Conclusions This study demonstrated that the power function model was much more accurate than the exponential decay model in describing the decomposition dynamics of soil organic carbon (SOC) in mineral soils of subtropical forests. The empirical relations and parameter values derived from this incubation study may be incorporated into process-based ecosystem models to simulate R h responses to climate changes

Exogenous glutathione improves high root-zone temperature tolerance by modulating photosynthesis, antioxidant and osmolytes systems in cucumber seedlings

To investigate the physiological responses of plants to high root-zone temperature (HT, 35 °C) stress mitigated by exogenous glutathione (GSH), cucumber (Cucumis sativus L.) seedlings were exposed to HT with or without GSH treatment for 4 days and following with 4 days of recovery. Plant physiological variables, growth, and gene expression related to antioxidant enzymes and Calvin cycle were quantified. The results showed that HT significantly decreased GSH content, the ratio of reduced to oxidized glutathione (GSH/GSSG), chlorophyll content, photosynthesis and related gene expression, shoot height, stem diameter, as well as dry weight. The exogenous GSH treatment clearly lessened the HT stress by increasing the above variables. Meanwhile, HT significantly increased soluble protein content, proline and malondialdehyde (MDA) content as well as O2•− production rate, the gene expression and activities of antioxidant enzymes. The GSH treatment remarkably improved soluble protein content, proline content, antioxidant enzymes activities, and antioxidant enzymes related gene expression, and reduced the MDA content and O2•− production rate compared to no GSH treatment in the HT condition. Our results suggest that exogenous GSH enhances cucumber seedling tolerance of HT stress by modulating the photosynthesis, antioxidant and osmolytes systems to improve physiological adaptation

Model Simulation of Cucumber Yield and Microclimate Analysis in a Semi-closed Greenhouse in China

Adequate greenhouse environmental management is very important for improving resource use efficiency and increasing vegetable yield. The objective of this study was to explore suitable climate and cultivation management for cucumber to achieve high yield and build optimal yield models in semi-closed greenhouses. A fruit cucumber cultivar Deltastar was grown over 4 years in greenhouse and weekly data of yields (mean, highest and lowest) and environmental variables, including total radiation, air temperature, relative humidity, and carbon dioxide (CO2) concentration were collected. Regression analyses were applied to develop the relationships and build best regression models of yields with environmental variables using the first 2 years of data. Data collected in years 3 and 4 were used for model validation. Results showed that total radiation, nutrient, temperature, CO2 concentration, and average nighttime relative humidity had significant correlations with cucumber yields. The best regression models fit the mean, lowest, and highest yields very well with R2 values of 0.67, 0.66, and 0.64, respectively. Total radiation and air temperature had the most significant contributions to the variations of the yields. Our results of this study provide useful information for improving greenhouse climate management and yield forecast in semi-closed greenhouses

Responses of soil respiration and its temperature/moisture sensitivity to precipitation in three subtropical forests in southern China

Both long-term observation data and model simulations suggest an increasing chance of serious drought in the dry season and extreme flood in the wet season in southern China, yet little is known about how changes in precipitation pattern will affect soil respiration in the region. We conducted a field experiment to study the responses of soil respiration to precipitation manipulations – precipitation exclusion to mimic drought, double precipitation to simulate flood, and ambient precipitation as control (abbr. EP, DP and AP, respectively) – in three subtropical forests in southern China. The three forest sites include Masson pine forest (PF), coniferous and broad-leaved mixed forest (MF) and monsoon evergreen broad-leaved forest (BF). Our observations showed that altered precipitation strongly influenced soil respiration, not only through the well-known direct effects of soil moisture on plant and microbial activities, but also by modification of both moisture and temperature sensitivity of soil respiration. In the dry season, soil respiration and its temperature sensitivity, as well as fine root and soil microbial biomass, showed rising trends with precipitation increases in the three forest sites. Contrarily, the moisture sensitivity of soil respiration decreased with precipitation increases. In the wet season, different treatments showed different effects in three forest sites. The EP treatment decreased fine root biomass, soil microbial biomass, soil respiration and its temperature sensitivity, but enhanced soil moisture sensitivity in all three forest sites. The DP treatment significantly increased soil respiration, fine root and soil microbial biomass in the PF only, and no significant change was found for the soil temperature sensitivity. However, the DP treatment in the MF and BF reduced soil temperature sensitivity significantly in the wet season. Our results indicated that soil respiration would decrease in the three subtropical forests if soil moisture continues to decrease in the future. More rainfall in the wet season could have limited effect on the response of soil respiration to the rising of temperature in the BF and MF

Comparative Proteomics of Root Apex and Root Elongation Zones Provides Insights into Molecular Mechanisms for Drought Stress and Recovery Adjustment in Switchgrass

Switchgrass plants were grown in a Sandwich tube system to induce gradual drought stress by withholding watering. After 29 days, the leaf photosynthetic rate decreased significantly, compared to the control plants which were watered regularly. The drought-treated plants recovered to the same leaf water content after three days of re-watering. The root tip (1cm basal fragment, designated as RT1 hereafter) and the elongation/maturation zone (the next upper 1 cm tissue, designated as RT2 hereafter) tissues were collected at the 29th day of drought stress treatment, (named SDT for severe drought treated), after one (D1W) and three days (D3W) of re-watering. The tandem mass tags mass spectrometry-based quantitative proteomics analysis was performed to identify the proteomes, and drought-induced differentially accumulated proteins (DAPs). From RT1 tissues, 6156, 7687, and 7699 proteins were quantified, and 296, 535, and 384 DAPs were identified in the SDT, D1W, and D3W samples, respectively. From RT2 tissues, 7382, 7255, and 6883 proteins were quantified, and 393, 587, and 321 proteins DAPs were identified in the SDT, D1W, and D3W samples. Between RT1 and RT2 tissues, very few DAPs overlapped at SDT, but the number of such proteins increased during the recovery phase. A large number of hydrophilic proteins and stress-responsive proteins were induced during SDT and remained at a higher level during the recovery stages. A large number of DAPs in RT1 tissues maintained the same expression pattern throughout drought treatment and the recovery phases. The DAPs in RT1 tissues were classified in cell proliferation, mitotic cell division, and chromatin modification, and those in RT2 were placed in cell wall remodeling and cell expansion processes. This study provided information pertaining to root zone-specific proteome changes during drought and recover phases, which will allow us to select proteins (genes) as better defined targets for developing drought tolerant plants. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD017441

Effects of Heat Shock on Photosynthetic Properties, Antioxidant Enzyme Activity, and Downy Mildew of Cucumber (Cucumis sativus L.)

Heat shock is considered an abiotic stress for plant growth, but the effects of heat shock on physiological responses of cucumber plant leaves with and without downy mildew disease are still not clear. In this study, cucumber seedlings were exposed to heat shock in greenhouses, and the responses of photosynthetic properties, carbohydrate metabolism, antioxidant enzyme activity, osmolytes, and disease severity index of leaves with or without the downy mildew disease were measured. Results showed that heat shock significantly decreased the net photosynthetic rate, actual photochemical efficiency, photochemical quenching coefficient, and starch content. Heat shock caused an increase in the stomatal conductance, transpiration rate, antioxidant enzyme activities, total soluble sugar content, sucrose content, soluble protein content and proline content for both healthy leaves and downy mildew infected leaves. These results demonstrate that heat shock activated the transpiration pathway to protect the photosystem from damage due to excess energy in cucumber leaves. Potential resistance mechanisms of plants exposed to heat stress may involve higher osmotic regulation capacity related to an increase of total accumulations of soluble sugar, proline and soluble protein, as well as higher antioxidant enzymes activity in stressed leaves. Heat shock reduced downy mildew disease severity index by more than 50%, and clearly alleviated downy mildew development in the greenhouses. These findings indicate that cucumber may have a complex physiological change to resist short-term heat shock, and suppress the development of the downy mildew disease

Drought-Induced Leaf Proteome Changes in Switchgrass Seedlings

Switchgrass (Panicum virgatum) is a perennial crop producing deep roots and thus highly tolerant to soil water deficit conditions. However, seedling establishment in the field is very susceptible to prolonged and periodic drought stress. In this study, a “sandwich” system simulating a gradual water deletion process was developed. Switchgrass seedlings were subjected to a 20-day gradual drought treatment process when soil water tension was increased to 0.05 MPa (moderate drought stress) and leaf physiological properties had expressed significant alteration. Drought-induced changes in leaf proteomes were identified using the isobaric tags for relative and absolute quantitation (iTRAQ) labeling method followed by nano-scale liquid chromatography mass spectrometry (nano-LC-MS/MS) analysis. Additionally, total leaf proteins were processed using a combinatorial library of peptide ligands to enrich for lower abundance proteins. Both total proteins and those enriched samples were analyzed to increase the coverage of the quantitative proteomics analysis. A total of 7006 leaf proteins were identified, and 257 (4% of the leaf proteome) expressed a significant difference (p \u3c 0.05, fold change \u3c0.6 or \u3e1.7) from the non-treated control to drought-treated conditions. These proteins are involved in the regulation of transcription and translation, cell division, cell wall modification, phyto-hormone metabolism and signaling transduction pathways, and metabolic pathways of carbohydrates, amino acids, and fatty acids. A scheme of abscisic acid (ABA)-biosynthesis and ABA responsive signal transduction pathway was reconstructed using these drought-induced significant proteins, showing systemic regulation at protein level to deploy the respective mechanism. Results from this study, in addition to revealing molecular responses to drought stress, provide a large number of proteins (candidate genes) that can be employed to improve switchgrass seedling growth and establishment under soil drought conditions (Data are available via ProteomeXchange with identifier PXD004675)