Statistical Design Methodology Research Articles

Nanoparticle depressants in froth flotation – The effect of colloidal silica with different size and surface modifications on the selective separation of semi-soluble salt type minerals

Colloidal silica has been presented as a selective depressant in froth flotation separation of scheelite and calcite by our group in 2020. Here we analyze the effects of colloidal silica dosage, specific surface area (i.e. size), and modification with microflotation on pure scheelite, calcite, fluorite, and apatite minerals. In a reagents scale-up procedure batch flotation experiments were conducted on a low-grade scheelite ore using statistical experimental design methodology. Microflotation experiments showed colloidal silica selectively depressing calcite flotation with increasing intensity with reduced size of colloidal silica. The nanoparticulate depressant did not affect the recoveries of scheelite, apatite, and fluorite – typical ore minerals that occur associated with calcite. Batch flotation of a low-grade scheelite ore confirmed the observations made at the microscale: colloidal silica significantly improves the scheelite-calcite selectivity index. Here, we observe a series of relations between colloidal silica specific surface area and modification on different process indicators such as scheelite-calcite selectivity index, recoveries, and froth properties. These relations are assumed to be due to the different aggregation mechanisms of the colloidal silica dispersions. The aluminate-modified colloidal silica, which tends to form a coherent gel network in the presence of Ca2+, shows the strongest effect on reducing calcite recovery accompanied by a significant reduction in scheelite recovery compared to the non-functionalised and silane-modified colloidal silica.

Optimization of low-grade coal and refuse-derived fuel blends for improved co-combustion behavior in coal-fired power plants.

This study is aimed at utilizing three waste materials, i.e., solid refuse fuel (SRF), tire derived fuel (TDF), and sludge derived fuel (SDF), as eco-friendly alternatives to coal-only combustion in co-firing power plants. The contribution of waste materials is limited to ≤5% in the composition of the mixed fuel (coal + waste materials). Statistical experimental design and response surface methodology are employed to investigate the effect of mixed fuel composition (SRF, TDF, and SDF) on gross calorific value (GCV) and ash fusion temperature (AFT). A quadratic model is developed and statistically verified to apprehend mixed fuel constituents' individual and combined effects on GCV and AFT. Constrained optimization of fuel blend, i.e., GCV >1,250 kcal/kg and AFT >1,200 °C, using the polynomial models projected the fuel-blend containing 95% coal with 3.84% SRF, 0.35% TDF, and 0.81% SDF. The observed GCV of 5,307 kcal/kg and AFT of 1225 °C for the optimized blend were within 1% of the model predicted values, thereby establishing the robustness of the models. The findings from this study can foster sustainable economic development and zero CO2 emission objectives by optimizing the utilization of waste materials without compromising the GCV and AFT of the mixed fuels in coal-fired power plants.

Addressing amino acid-derived inhibitory metabolites and enhancing CHO cell culture performance through DOE-guided media modifications.

Previously, we identified six inhibitory metabolites (IMs) accumulating in Chinese hamster ovary (CHO) cultures using AMBIC 1.0 community reference medium that negatively impacted culture performance. The goal of the current study was to modify the medium to control IM accumulation through design of experiments (DOE). Initial over-supplementation of precursor amino acids (AAs) by 100% to 200% in the culture medium revealed positive correlations between initial AA concentrations and IM levels. A screening design identified 5 AA targets, Lys, Ile, Trp, Leu, Arg, as key contributors to IMs. Response surface design analysis was used to reduce initial AA levels between 13% and 33%, and these were then evaluated in batch and fed-batch cultures. Lowering AAs in basal and feed medium and reducing feed rate from 10% to 5% reduced inhibitory metabolites HICA and NAP by up to 50%, MSA by 30%, and CMP by 15%. These reductions were accompanied by a 13% to 40% improvement in peak viable cell densities and 7% to 50% enhancement in IgG production in batch and fed-batch processes, respectively. This study demonstrates the value of tuning specific AA levels in reference basal and feed media using statistical design methodologies to lower problematic IMs.

Optimization of Coagulation-Flocculation Process in Efficient Arsenic Removal from Highly Contaminated Groundwater by Response Surface Methodology.

Elevated arsenic (As) contamination in water, especially groundwater, has been recognized as a major problem of catastrophic proportions. This work explores As(V) removal via the coagulation-flocculation process by use of ferric chloride coagulant and polyacrylamide k16 co-coagulant as a first time. The effects of major operating variables such as coagulant dosing (50, 125 and 200 mg/L), co-coagulant dosing (5, 12.5 and 20 mg/L), pH (6, 7and 8), fast mixing time (1, 2 and 3 min), and fast mixing speed (110, 200 and 300 rpm) on As(V) removal efficiency were investigated by a Box-Behnken statistical experiment design (BBD) and response surface methodology (RSM). According to factors F values, coagulant dosing, rapid mixing speed, pH, and co-coagulant dosing showed the most effect on As(V) removal efficiency, and the rapid mixing time factor indicated the slightest effect. The proposed quadratic model was significant with a p value < 0.0001 and has satisfactorily described the experimental data with R2 and adjusted R2 values of 0.9855 and 0.9738, respectively. Predicted model optimal conditions with target of complete As(V) removal were coagulant dosing = 197.63 ppm, co-coagulant dosing = 19.55 ppm, pH = 7.37, fast mixing time = 1.43 min and fast mixing speed = 286.77 rpm. The treatment of Nazarabad well water sample with an initial As(V) concentration of 5 mg/L under the optimal conditions removed 100% As(V) with the volume of produced sludge of 10.7 mL/200 mL. Increasing coagulant dosing, co-coagulant dosing, fast mixing time and fast mixing speed operation parameters from low-level to high-level values indicated 78%, 20%, 10.52% and 9.47% increases in volume of the produced sludge, respectively. However, a reduction of 13.63% in volume of the produced sludge resulted via pH increases.

Optimization of tetracycline removal from water by iron-coated pine-bark biochar.

We synthesized iron-coated pine-bark biochar (Fe-PBB) and determined the optimal conditions for removing the antibiotic tetracycline from water. The Fe-PBB was synthesized by depositing iron oxide on pyrolyzed pine-bark waste via a facile co-precipitation method. Characterization (SEM, EDX, and TGA) showed successful deposition of a mass of approximately 27% (w/w) iron on the PBB to synthesize Fe-PBB. Fe-PBB exhibited five times higher adsorption capacity (~ 10mg/g) for tetracycline compared with PBB. The effects of initial tetracycline concentration, pH, temperature, and Fe-PBB dose on the adsorptionremoval of tetracycline from waterwere systematically investigated and optimized using a statistical experimental design and response surface methodology. The empirical relationship between the experimental factors and tetracycline removal was modeled, statistically validated through the analysis of variance, and used to predict the optimal conditions for adsorption removal of tetracycline. We found that ≥ 95% of the tetracycline can be removed at a tetracycline concentration of 1mg/L, pH of 7, temperature of50°C, and a Fe-PBB dose of 2g/L. The adsorption isotherm modeling study suggests that the adsorption of tetracycline can be attributed to the pore filling phenomenon and multilayer adsorption on theFe-PBB. Athermodynamics study showed that the adsorption occurs spontaneously withan endothermic reaction.

Formulation and Optimization of Diclofenac Sodium Loaded Ethylcellulose Nanoparticles

Design of experiment (DoE) is a useful time and cost-effective tool for analyzing the effect of independent variables on the formulation characteristics. The aim of this study is to evaluate the effect of the process variables on the characteristics involved in the preparation of Diclofenac Sodium (DC) loaded ethylcellulose (EC) nanoparticles (NP) using Central Composite Design (CCD). NP were prepared by W/O/W emulsion solvent evaporation method. Three factors were investigated (DC/EC mass ratio, PVA concentration, homogenization speed) in order to optimize the entrapment efficiency (EE) and the particle size of NP. The optimal formulation was characterized by Fourier Transform Infrared (FTIR), Scanning Electron Microscopy (SEM), Differential Scanning Calorimetry (DSC), and in vitro release. Optimized formulation showed an EE of 49.09 % and an average particle size of 226.83 nm with a polydispersity index of 0.271. No drug-polymer interaction was observed in FTIR and DSC analysis. SEM images showed that the particles are spherical and uniform. The in vitro release study showed a sustained release nature, 53.98 % of the encapsulated drug has been released over 24hours period. This study demonstrated that statistical experimental design methodology can optimize the formulation and the process variables to achieve favorable responses.

Synergetic Effect of Organic Flocculant and Montmorillonite Clay on the Removal of Nano-CuO by Coagulation-Flocculation-Sedimentation Process.

The widespread usage of nano-copper oxide particles (nano-CuO) in several industrial products and applications raises concerns about their release into water bodies. Thus, their elimination from drinking water is essential to reduce the risk to human health. This work investigated the removal of nano-CuO from pure water and montmorillonite clay (MC) suspensions using poly aluminum ferric chloride (PAFC) as well as cationic polyacrylamide (PAM) by the coagulation-flocculation-sedimentation (C/F/S) process. Moreover, the PAFC and PAFC/PAM flocculation performance for various nano-CuO particles concentrations, dosages, pH, settling times and stirring speeds were also investigated. The findings showed that the removal of nano-CuO and turbidity in MC suspension were higher as compared to pure water. Moreover, the combined effect of PAFC/PAM on the elimination of nano-CuO and turbidity was also substantially better than the individual use of PAFC or PAM. The efficient removal of CuO was observed in the solution containing higher mass concentration in the order (10 mg/L > 2.5 mg/L > 1 mg/L) with an increased coagulant dose. The improved removal performance of nano-CuO was observed in a pH range of 7–11 under various water matrices. The C/F/S conditions of nano-CuO were further optimized by the Box–Behnken statistical experiment design and response surface methodology. The PAFC/PAM dose resulted in the maximum removal of nano-CuO (10 mg/L) in both pure water (>97%) and MC suspension (>99%). The results of particle monitoring and Fourier transform infrared of composite flocs revealed that the main removal mechanism of nano-CuO may be the combined effect of neutralization, complexation as well as adsorption.

Application of Multivariate Optimization for Phenolic Compounds and Antioxidants Extraction from Moroccan Cannabis sativa Waste

A statistical simplex centroid design methodology was applied to determine the effects of different solvents and their mixtures on the yield, total polyphenol content, 2′2-dipheny-l-picrylhydrazyl (DPPH) radical scavenging activity, and ferric reducing antioxidant power (FRAP) of extracts from the waste of Cannabis sativa. The different extractor solvents (ethanol, methanol, water, and hexane) and their binary and ternary combinations were evaluated. The experimental results and their response surface models showed that the highest TPC yield values occur with the binary interaction between water and ethanol around the proportion of (ethanol, 70%; water, 30%). The desirability function showed that the optimal conditions were for TPC extraction ternary mixtures which consisted of 75% ethanol, 12.5% methanol, and 12.5% water. Ternary mixtures including water and binary mixture (ethanol 50% to 75%) yielded extracts with the best DPPH antioxidant activity, whereas pure methanol was the best solvent for extracting molecules with FRAP antioxidant capacity. The desirability function including all responses showed that the optimal solvent mixture consisted of 25% ethanol and 75% methanol.

Evaluation of phenanthrene removal from soil washing effluent by activated carbon adsorption using response surface methodology

Soil washing is a promising technology for the remediation of polycyclic aromatic hydrocarbons (PAH)-contaminated sites, but surfactant needs to be recovered to reduce remediation cost and avoid secondary pollution. In this study, activated carbon (AC), prepared from waste walnut shells, was applied to the adsorptive removal of phenanthrene (PHE) from synthetic soil washing effluent with Tween 80 as a model surfactant. Box-Behnken statistical experiment design (BBD) and response surface methodology (RSM) were used to investigate the influence of AC dosage, Tween 80 concentration and adsorption time, and their potential interaction effect on PHE removal. A response surface model was established based on the BBD experimental results. The goodness of fit of the model was confirmed by determination coefficient, coefficient of variation (CV) and residuals analysis. The RSM model indicates that AC dosage or adsorption time had positive effect on PHE removal while Tween 80 concentration had negative effect. The interaction effect between AC dosage and Tween 80 concentration was significant but the other two interaction effects were not. The 3D response surface plots were developed based on the RSM equation. The RSM model was validated by an additional experiment and the obtained result of PHE removal was very close to the model prediction, indicating the RSM model can effectively predict the PHE removal from soil washing effluent with activated carbon adsorption.

Development of a New Bioprocess for Clean Diosgenin Production through Submerged Fermentation of an Endophytic Fungus.

Diosgenin is used widely to synthesize steroidal hormone drugs in the pharmaceutical industry. The conventional diosgenin production process, direct acid hydrolysis of the root of Dioscorea zingiberensis C. H. Wright (DZW), causes large amounts of wastewater and severe environmental pollution. To develop a clean and effective method, the endophytic fungus Fusarium sp. CPCC 400226 was screened for the first time for the microbial biotransformation of DZW in submerged fermentation (SmF). Statistical design and response surface methodology (RSM) were implemented to develop the diosgenin production process using the Fusarium strains. The environmental variables that significantly affected diosgenin yield were determined by the two-level Plackett–Burman design (PBD) with nine factors. PBD indicates that the fermentation period, culture temperature, and antifoam reagent addition are the most influential variables. These three variables were further optimized using the response surface design (RSD). A quadratic model was then built by the central composite design (CCD) to study the impact of interaction and quadratic effect on diosgenin yield. The values of the coefficient of determination for the PBD and CCD models were all over 0.95. P-values for both models were 0.0024 and <0.001, with F-values of ∼414 and ∼2215, respectively. The predicted results showed that a maximum diosgenin yield of 2.22% could be obtained with a fermentation period of 11.89 days, a culture temperature of 30.17 °C, and an antifoam reagent addition of 0.20%. The experimental value was 2.24%, which was in great agreement with predicted value. As a result, over 80% of the steroidal saponins in DZW were converted into diosgenin, presenting a ∼3-fold increase in diosgenin yield. For the first time, we report the SmF of a Fusarium strain used to produce diosgenin through the microbial biotransformation of DZW. A practical diosgenin production process was established for the first time for Fusarium strains. This bioprocess is acid-free and wastewater-free, providing a promising environmentally friendly alternative to diosgenin production in industrial applications. The information provided in the current study may be applicable to produce diosgenin in SmF by other endophytic fungi and lays a solid foundation for endophytic fungi to produce natural products.

Bio-statistical optimization of lipase production by thermophilic Pseudomonas formosensis and its application on oral biofilm degradation

Oral biofilm formation is the defense mechanism exhibited by oral pathogens against antimicrobial agents responsible for causing several oral infections. Lipase mediated catalytic degradation of biofilm formed in-vitro by oral pathogens Enterococcus faecalis and Streptococcus mutans is attempted in the present approach. Lipase was produced from sesame oil cake biomass using thermophilic Pseudomonas formosensis TB5 isolated from sediment of Tarabalo hot spring, Odisha. The experiment was designed by using Design-Expert (v.6.0.7). The statistical method central composite design and response surface methodology was carried out to study the interaction between various parameters (pH, temperature, moisture and biosurfactant) on lipase production in a solid-state fermentation process. A quadratic regression model with (R2 = 0.8642), was found to be best fitting and predicted maximum lipase production to be 47.2IU/g at an optimum pH (8.34), temperature (51.63 °C), moisture (52.51%) and biosurfactant (1.36 mg) using sesame oil cake. Experimentally, lipase was produced at a concentration of 50.78IU/g at above predicted optimum conditions which validated the fitness of model, the value being very close to the predicted one. Lipase from P. formosensis was found to degrade biofilm of oral pathogens, proving to be scope of its use a prospective biological agent for dental biofilm treatment after undertaking further analysis.

Investigating the Result of Current Density, Temperature, and Electrolyte Concentration on COD: Subtraction of Petroleum Refinery Wastewater Using Response Surface Methodology

Electrochemical oxidation (EO) investigated chemical oxygen demand (COD) subtraction from petroleum refinery wastewater (PRW) as a capable remediation process. Titanium substrates coated with iridium–tantalum oxide mixtures (Ti/IrO2–Ta2O5) were used as the dimensional stable anode (DSA). The Box-Behnken Design (BBD), a statistical experimental design and response surface methodology (RSM), was used to matrix the current density, temperature, and electrolyte (NaCl) concentration variables, with COD removal efficiency as the response factor. A second-order verifiable relationship between the response and independent variables was derived where the analysis of variance displayed a high coefficient of determination value (R2 = 0.9799). The predicted values calculated with the model equations were very close to the experimental values where the model was highly significant. Based on the BBD for current density, the optimum process conditions, temperature and electrolyte (NaCl) concentration were 7.5 mA/cm2, 42 °C and 4.5 g/L, respectively. They were resulting in a COD removal efficiency of 99.83% after a 12-hour EO period.

Optimization of Antimony Removal by Coagulation-Flocculation-Sedimentation Process Using Response Surface Methodology

Coprecipitation-adsorption plays a significant role during coagulation-flocculation-sedimentation (C/F/S) of antimony (Sb) in water. This work uses a Box–Behnken statistical experiment design (BBD) and response surface methodology (RSM) to investigate the effects of major operating variables such as initial Sb(III, V) concentration (100–1000 µg/L), ferric chloride (FC) dose (5–50 mg/L), and pH (4–10) on redox Sb species. Experimental data of Sb(III, V) removal were used to determine response function coefficients. The model response value (Sb removal) showed good agreement with the experimental results. FC showed promising coagulation behavior of both Sb species under optimum pH (6.5–7.5) due to its high affinity towards Sb species and low residual Fe concentration. However, a high dose of 50 mg/L of FC is required for the maximum (88–93%) removal of Sb(V), but also for the highest (92–98%) removal of low initial concentrations of Sb(III). Furthermore, BBD and RSM were found to be reliable and feasible for determining the optimum conditions for Sb removal from environmental water samples by a C/F/S process. This work may contribute to a better understanding and prediction of the C/F/S behavior of Sb(III, V) species in aqueous environments, to reduce potential risks to humans.

Optimized Production of a Redox Metabolite (pyocyanin) by Pseudomonas aeruginosa NEJ01R Using a Maize By-Product.

Pseudomonas aeruginosa metabolizes pyocyanin, a redox molecule related to diverse biological activities. Culture conditions for the production of pyocyanin in a defined medium were optimized using a statistical design and response surface methodology. The obtained conditions were replicated using as substrate an alkaline residual liquid of cooked maize and its by-products. The untreated effluent (raw nejayote, RN) was processed to obtain a fraction without insoluble solids (clarified fraction, CL), then separated by a 30 kDa membrane where two fractions, namely, retentate (RE) and filtered (FI), were obtained. Optimal conditions in the defined medium were 29.6 °C, 223.7 rpm and pH = 6.92, which produced 2.21 μg mL−1 of pyocyanin, and by using the wastewater, it was possible to obtain 3.25 μg mL−1 of pyocyanin in the retentate fraction at 40 h. The retentate fraction presented the highest concentration of total solids related to the maximum concentration of pyocyanin (PYO) obtained. The pyocyanin redox behavior was analyzed using electrochemical techniques. In this way, valorization of lime-cooked maize wastewater (nejayote) used as a substrate was demonstrated in the production of a value-added compound, such as pyocyanin, a redox metabolite of Pseudomonas aeruginosa NEJ01R.

Flow Cytometric Analyses of Lymphocyte Markers in Immune Oncology: A Comprehensive Guidance for Validation Practice According to Laws and Standards.

Many anticancer therapies such as antibody-based therapies, cellular therapeutics (e.g., genetically modified cells, regulators of cytokine signaling, and signal transduction), and other biologically tailored interventions strongly influence the immune system and require tools for research, diagnosis, and monitoring. In flow cytometry, in vitro diagnostic (IVD) test kits that have been compiled and validated by the manufacturer are not available for all requirements. Laboratories are therefore usually dependent on modifying commercially available assays or, most often, developing them to meet clinical needs. However, both variants must then undergo full validation to fulfill the IVD regulatory requirements. Flow cytometric immunophenotyping is a multiparametric analysis of parameters, some of which have to be repeatedly adjusted; that must be considered when developing specific antibody panels. Careful adjustments of general rules are required to meet legal and regulatory requirements in the analysis of these assays. Here, we describe the relevant regulatory framework for flow cytometry-based assays and describe methods for the introduction of new antibody combinations into routine work including development of performance specifications, validation, and statistical methodology for design and analysis of the experiments. The aim is to increase reliability, efficiency, and auditability after the introduction of in-house-developed flow cytometry assays.

Performance targets defined by retro-techno-economic analysis for the use of soybean protein as saccharification additive in an integrated biorefinery

The use of additives in the enzymatic saccharification of lignocellulosic biomass can have positive effects, decreasing the unproductive adsorption of cellulases on lignin and reducing the loss of enzyme activity. Soybean protein stands out as a potential lignin-blocking additive, but the economic impact of its use has not previously been investigated. Here, a systematic evaluation was performed of the process conditions, together with a techno-economic analysis, for the use of soybean protein in the saccharification of hydrothermally pretreated sugarcane bagasse in the context of an integrated 1G-2G ethanol biorefinery. Statistical experimental design methodology was firstly applied as a tool to select the process variable solids loading at 15% (w/w) and soybean protein concentration at 12% (w/w), followed by determination of enzyme dosage at 10 FPU/g and hydrolysis time of 24 h. The saccharification of sugarcane bagasse under these conditions enabled an increase of 26% in the amount of glucose released, compared to the control without additive. The retro-techno-economic analysis (RTEA) technique showed that to make the biorefinery economically feasible, some performance targets should be reached experimentally such as increasing biomass conversion to ideally 80% and reducing enzyme loading to 5.6 FPU/g in the presence of low-cost soybean protein.

Use of Taguchi Robust Design to Optimize Rubber Glove Process

In this paper, Taguchi concept of robust process design and the classical statistical experimental design methodology are integrated for improving both the product quality and efficiency. It is a systematic method of optimizing a production process, and is concerned with productivity enhancement and cost effectiveness. The aim of this study is to investigate the effect of the inputs on the outputs in the presence of a noise factor and also to choose the best level settings of the control factors that will maximize the mean and minimize the variation in the glove's quality characteristics at minimal cost. The quality characteristic of the rubber glove that is considered in this study was the tensile strength. Taguchi L16, the orthogonal array is employed to run the experiments. The analysis of variance (ANOVA) and the signal-to-noise (S/N) ratio were performed. The BG interaction was identified as the important mean effect. However, factor (B), the latex temperature was not affected by factor (G), oven temperature after coagulation dip when it was at high but enhanced the strength when both were set at low. Factor (A), curing temperature profile affected both the mean and the process variability. The effect of humidity (H) appeared insignificant using ANOVA, but was significant in S/N ratio for the mean tensile strength. The preferred optimal setting were: A 2 B 1 C 1 D 1 F 2 H 1 G 1.

Investigation of olfactory interactions of low levels of five off-flavour causing compounds in a red wine matrix

The qualitative sensory perception of individual and of complex mixtures of five compounds, guaiacol ('burnt note'), o-cresol ('phenolic/tar'), 4-ethylphenol (4-EP, 'leather/barnyard'), 2-iso-butyl-3-methoxypyrazine (IBMP, 'green pepper/herbaceous'), and 2,4,6-trichloroanisole (TCA, 'cork taint/ mouldy') were tested in a partially de-aromatised red wine matrix using descriptive analysis by a trained panel of eleven judges. Compounds were characterised at peri- and sub-threshold concentrations using a partial D-optimal statistical design and response surface methodology. Results indicated that complex mixtures in red wine elicit an olfactory response that could not be predicted from the attributes or descriptors of single compounds. Positive sweet/fruity attributes were more intense in solutions containing fewer off-flavour compounds. Novel findings of this study include that IBMP at sub- and peri-threshold levels shows perceptual interaction with volatile phenols at the same levels, and samples containing combinations of these compounds manifested herbaceous and burnt characteristics. Olfactory interactions of this many off-flavour compounds have not been investigated previously in one study. The findings have direct implications for wines made from cultivars that are known to contain these compounds, and add to the understanding of the behaviour and impact of very low levels (peri- and sub-threshold) of volatile phenols, IBMP, and TCA derived from various sources during winemaking.

Level-expansion: A statistical sequential design methodology with application to nanomaterial synthesis

Nanotechnology is an era-defining breakthrough across science and engineering. For example, one-dimensional nanostructures such as nanowires, nanotubes, and nanobelts are widely regarded as critical building blocks for creating the next generation of devices in electronics, optics, energy, and biomedicine. Motivated by a practical problem of sequential synthesis of nanowires, we propose a new statistical design augmentation method, called level-expansion. For a fractional factorial design at two levels, this method creates a follow-up design by expanding some of the factors in the initial design to four elaborately chosen levels and reversing the signs of the remaining factors. The augmented design produced as such strikes a fine balance between dealiasing and entertaining nonlinear effects. Some statistical properties of the proposed method are derived. The effectiveness of the proposed method is successfully illustrated with a case study for growing a type of zinc-oxide nanowire. The use of level-expansion in the case study unveils some previously unknown nonlinear relationships between the concentration of polyethyleneimine and the length of nanowires. This finding is important for nanoscientists to invent new zinc-oxide nanowires with better macroscopic transport properties. Besides nanotechnology, the proposed method applies broadly to problems in many other scientific fields with similar traits where a follow-up design is needed for the dual purposes of investigating nonlinear effects and dealising.

From Process Corners to Statistical Circuit Design Methodology: Opportunities and Challenges

In this paper, we will focus on the problem of modeling global or die-to-die variation in semiconductor devices. We will demonstrate that the process corner-based approach for modeling global variation, which has been the dominant approach for design validation, has fundamental limitations in predicting the circuit performance variation. We will then show how a full statistical model of variation can accurately predict circuit behavior and discuss some of the challenges in moving from a corner-based design to statistical simulations.