Yield Coefficient Research Articles

Batch fermentation and GC-MS analysis of biocontrol agent, Bacillus amyloliquefaciens strain KSAS6 and its impact on soilborne fungus, Sclerotium bataticola

Background: Sclerotium bataticola, a soil-born fungus, is responsible for charcoal rot in a variety of plants. It is also responsible for causing substantial damage to a wide range of horticultural crops around the world.Methods: Fifteen different Bacillus isolates were isolated and evaluated for their ability to inhibit S. batatacola's growth. The promising bacterial isolate was molecularly identified using NCBI-Blast and phylogenetic tree analysis of the 16S rRNA gene. Batch fermentation was performed in a stirred tank bioreactor to maximize culture biomass and secondary metabolite synthesis. Gas chromatography-mass spectrometry was used to discover secondary metabolite compounds.Results: The KSAS6 isolate was the most effective for inhibiting the fungal growth of mycelial cells, with a 48.2% inhibition percentage. The probable biocontrol agent, B. amyloliquefaciens strain KSAS6, was identified and recorded in GenBank under the accession number PQ271636. The culture biomass and secondary metabolites were maximized by the batch fermentation technique, reaching the highest achievable level of 2.1 g L-1 at 11 hours. This was accomplished while maintaining a steady specific growth rate (µ) of 0.13 h-1. Based on the observations, the biomass yield coefficient was found to be 0.37 g cells/g glucose. Among the 21 secondary metabolite compounds identified in GC-MS analysis, diisooctyl phthalate was the highest compound (43.31%).Conclusion: The strain of rhizobacterium B. amyloliquefaciens known as KSAS6 can inhibit the growth of S. bataticola, which makes it a promising candidate for the biocontrol of fungal infections in plants.Keywords: Sclerotium bataticola; Bacillus amyloliquefaciens; Batch fermentation; Secondary metabolites; antifungal

A parallel bioreactor strategy to rapidly determine growth-coupling relationships for bioproduction: a mevalonate case study

BackgroundThe climate crisis and depleting fossil fuel reserves have led to a drive for ‘green’ alternatives to the way we manufacture chemicals, and the formation of a bioeconomy that reduces our reliance on petrochemical-based feedstocks. Advances in Synthetic biology have provided the opportunity to engineer micro-organisms to produce compounds from renewable feedstocks, which could play a role in replacing traditional, petrochemical based, manufacturing routes. However, there are few examples of bio-manufactured products achieving commercialisation. This may be partially due to a disparity between academic and industrial focus, and a greater emphasis needs to be placed on economic feasibility at an earlier stage. Terpenoids are a class of compounds with diverse use across fuel, materials and pharmaceutical industries and can be manufactured biologically from the key intermediate mevalonate.ResultsHere, we report on a method of utilising parallel bioreactors to rapidly map the growth-coupling relationship between the specific product formation rate, specific substrate utilisation rate and specific growth rate. Using mevalonate as an example product, a maximum product yield coefficient of 0.18 gp/gs was achieved at a growth rate (μ) of 0.34 h−1. However, this process also led to the formation of the toxic byproduct acetate, which can slow growth and cause problems during downstream processing. By using gene editing to knock out the ackA-pta operon and poxB from E. coli BW25113, we were able to achieve the same optimum production rate, without the formation of acetate.ConclusionsWe demonstrated the power of using parallel bioreactors to assess productivity and the growth-coupling relationship between growth rate and product yield coefficient of mevalonate production. Using genetic engineering, our resultant strain demonstrated rapid mevalonate formation without the unwanted byproduct acetate. Mevalonate production is quantified and reported in industrially relevant units, including key parameters like conversion efficiency that are often omitted in early-stage publications reporting only titre in g/L.

Alkalinity enhanced hydrolysis of primary sludge for carbon source recovery and its impact on denitrification in wastewater treatment.

Primary sludge can serve as an internal carbon source for denitrification in wastewater treatment plants (WWTPs). This study explores the use of alkaline treatment to produce a fermentation broth from primary sludge, which predominantly contains short-chain volatile fatty acids (VFAs), with acetic acid and propionic acid making up over 65% of the total VFAs. The performance of this fermentation broth as a sole carbon source for denitrification was compared with that of sodium acetate, acetic acid, methanol, and ethanol in both biofilm and activated sludge systems. The results revealed that the denitrification rate achieved using the fermentation broth was as high as 2.1661mg NO3--N/(g MLSS·h), which was slightly lower than that of sodium acetate and acetic acid but higher than that of methanol and ethanol. The fermentation broth demonstrated a high heterotrophic yield (0.7183), an equivalent specific carbon requirement for denitrification as acetic acid and sodium acetate, and a rapid denitrification start-up. Moreover, variations in the VFAs/SCOD ratios in the fermentation broth did not significantly impact the denitrification rate or substrate biodegradation rate. However, the yield coefficient and specific carbon requirement for denitrification were found to vary significantly depending on the carbon source used. This study concludes that with appropriate treatment, fermented broth from primary sludge can be an effective carbon source comparable to commercial external carbon sources, significantly reducing carbon emissions.

Steel Scrap Yield Prediction in Basic Oxygen Steelmaking Based on Random Forest and Neural Networks

Steel scrap is a primary raw material in basic oxygen steelmaking. However, its yield is influenced by numerous factors, making accurate prediction challenging. This study explores and predicts the steel scrap yield in the basic oxygen steelmaking process using machine learning techniques. First, the interquartile range method is applied to clean the collected steelmaking process data. By analyzing the blow loss of molten iron and the amount of steel obtained from the scrap, a deviation coefficient of scrap yield is defined and calculated. Next, a correlation analysis and a feature importance analysis using the random forest algorithm identify the factors influencing the deviation coefficient of scrap yield. Finally, a multilayer neural network regression model is constructed to predict the deviation coefficient of scrap yield. The model achieves a mean squared error of 0.00051 on the test set, with an accuracy rate of 96.89% for absolute errors within ±0.05. This method not only effectively predicts scrap yield but also provides a reference for calculating steel materials and controlling costs in the steelmaking process.

Diminished water yield coefficient of glacial catchments in Northwest China

Study region19 glacial catchments located in Northwest China. Study focusThe water yield coefficient (denoted as WYc) of glacier catchments in Northwest China has changed over the past six decades, closely linked to shifts in land cover dynamics. However, quantifying the impacts of climate and land cover changes on glacier catchments remains challenging due to the complexity of glacier hydrological processes and the scarcity of long-term glacier runoff data. In this study, the Budyko equation was coupled with a glacier runoff model to enable quantitative analysis of the factors driving changes in water yield (WY). Path analysis was then employed to assess the direct and indirect effects of climate and landscape changes on the WYc. New hydrological insight for the regionThe results indicated that 14 out of 19 catchments experienced a decline in WYc, particularly in those with greater glacier coverage. Glacier retreat and increased vegetation greenness adversely affected WYc by increasing the catchment parameter, with effects of −26.42 % and −25.21 %, respectively. Although overall WY in the catchments has increased—driven primarily by increased precipitation and glacier storage loss, with contribution rates of 100.66 % and 25.05 %, respectively—the diminished WYc is expected to decelerate the rate of WY increase. This trend poses significant challenges for water resource management in arid and water-scarce regions.

Effect of inoculated sludge concentration on start-up of anammox reactor: Nitrogen removal performance and metabolic pathways

The anammox process is efficient for nitrogen removal but faces challenges due to slow bacterial growth and limited inoculated sludge supply. This study examined the effects of different inoculated sludge concentrations (3.5, 7, and 14 g/L) on start-up and nitrogen metabolism in anammox reactors. Three identical reactors were operated under controlled conditions, with comprehensive analysis of nitrogen removal efficiency, sludge characteristics, and microbial community dynamics through metagenomic and transcriptomic approaches. Results demonstrated that higher inoculated sludge concentrations accelerated reactor start-up, with the 14 g/L reactor achieving stable operation in 13 days compared to 44 days for the 3.5 g/L reactor. However, the improvement in nitrogen removal rate showed a boundary effect, not proportional to the increase in sludge concentration. Notably, reactors with higher inoculated sludge concentrations exhibited lower sludge loads but higher sludge yield coefficients. Metagenomic analysis revealed Candidatus Kuenenia as the dominant anammox bacteria, with decreasing hydrazine dehydrogenase (hdh) gene expression levels observed at higher sludge concentrations, suggesting hydrazine synthesis as a potential rate-limiting step. This study provides novel insights into the optimal range of inoculated sludge concentration for anammox reactor start-up and elucidates the underlying metabolic mechanisms, offering valuable guidance for practical engineering applications.

Effect of Moisture Depletion Rate and Irrigation Water Depth on the Productivity and Water Use Efficiency of Soybean Crop (Glycine max L.) Merr. under Drip Irrigation and Fixed Sprinkler Irrigation Systems

Background: Water management and its appropriate use are priorities in arid and semi-arid areas across the globe. Methods: A field experiment was carried out at Hisar in Al-Tunkopry district, Kirkuk Governorate, during 2023 summer season. Split-split plot design was adopted to implement the experiment, using randomized complete blocks design (RCBD). The main plots included irrigation method factor (sprinkler and drip) and the moisture depletion rate was placed in the sub plots (60 and 70% of the available water) while varing irrigation depth were placed in the sub-sub plots (50, 75 and 100)% of the net irrigation depth. Result: Results of the study revealed that the water requirement of the soybean crop under the sprinkler irrigation system reached 1275.9 and 1272.9 mm season-1 at 100% of net irrigation depth and at moisture depletion rates of 60 and 70%, respectively and in drip irrigation system it reached 1170.6 and 1201 mm season-1 for an irrigation level of 100% of the net irrigation depth and at a moisture depletion rate of 60 and 70%, respectively. The yield coefficient values (0.52, 0.90, 1.01, 0.90) and (0.44, 0.85, 0.96, 0.52) at a moisture depletion of 60% for the two methods (drip and sprinkler irrigation). The highest seed yield was 4.094 Mg ha-1 for the sprinkler irrigation treatment with a moisture depletion rate of 60% and an irrigation water level of 50% of the net irrigation depth, while the lowest yield was 2.41800 Mg ha-1 for the drip irrigation treatment with a moisture depletion rate of 60 and a level of 75% of the net depth. The drip irrigation achieved the highest water use efficiency 0.607072 kg m-3, in comparison to the sprinkler irrigation 0.362063 kg m-3.

A novel uncertainty quantification method for electricity performance of building photovoltaic systems from multiple weather data sources

Distributed photovoltaic (PV) systems on buildings offer a promising solution for local renewable energy integration. As interest in sustainable energy grows, the demand for building PV systems is increasing. However, a significant challenge lies in accurately quantifying the uncertainty associated with building PV performance, particularly when considering multiple weather data sources. This study proposes a novel uncertainty quantification method to address this challenge. A case study of a building PV system with a PV wall and roof in Tianjin, China, is utilized to demonstrate the proposed method. Three types of weather data from different sources are considered: typical meteorological year data, multi-year historical data, and climate change projections. Uncertainty is quantified using a weighted-mean approach, incorporating weights based on recency, period, and accuracy of the data sources. Results indicate that the proposed method effectively integrates uncertainties from various data sources, providing reliable long-term energy yield estimates for PV systems. The variation coefficient of annual yield for the PV wall and roof system across ten typical meteorological year files is approximately 10 %. This study contributes to a comprehensive understanding of uncertainty in building PV performance, enabling informed decision-making in sustainable building design and energy management.

DFT supported studies of multi-responsive AIE active fluorophores for the sensitive fluorescence recognition of p-nitrophenol and pH: Vapor phase and solution mode sensing

Designing of an aggregation-induced emission (AIE) active multi-responsive fluorophores for the sensitive recognition of targeted analytes has been a hot spot in recent time. In pursuit of this endeavor, two chromene core sensors KG01 and KG02, installed with phenyl rotors, were efficiently designed, synthesized, and characterized through NMR spectroscopy. Proposed fluorophores demonstrated striking features of structure–property relationships, including solvatochromism and J-aggregates-based aggregation induced emission (AIE). Subsequently, well-thought-out developed sensors KG01 and KG02 were subjected to photoinduced electron transfer (PET) operated fluorescence quenching driven optical tracing of p-nitrophenol (p-NP) in the co-existence of competing analytes, with LOD down to 4.7 and 6.6 nM, respectively. Further, diversified theoretical calculations were executed to validate J-aggregates, supreme selectivity of sensors towards p-NP and PET as its primary sensing mechanism. Additionally, Jobs plot experiment, dynamic light scattering (DLS) size distribution, and 1H NMR titration assay also endorsed the selective p-NP sensing. Further, reported sensors were exploited for the fluorescence along with visual recognition of trifluoroacetic acid (TFA) and sodium hydroxide (NaOH). Interestingly, devised sensor KG01 disclosed naked-eye detection of TFA vapors. Furthermore, real water sample analysis, engineering of hand-held thin layer chromatography (TLC) plates-based fluorescent kits, and fabrication of logic devices were carried out to signify the convenient point-of-need applications of the proposed sensors. To the best of our knowledge, sensors KG01 and KG02 are first-ever solvatochromic and AIEgen chromenes with good quantum yield (Φ) and absorption coefficient as potential candidates to establish a range of easy-to-apply platforms for the selective and sensitive distinguishing of different aforementioned analytes. Given the role of p-NP as a priority pollutant from industrial sources with severe ecological and health impacts, these fluorescence sensors offer promising potential for developing cost-effective tools for rapid and precise trace-level detection. Additionally, industrial seepage of TFA and NaOH into water reserves poses serious health risks. These fluorescence sensors could be adapted to create devices capable of detecting these contaminants at nanomolar concentrations.

КОЛИЧЕСТВЕННЫЕ КРИТЕРИИ ОЦЕНКИ МОРОЗОСТОЙКОСТИ НА ОСНОВЕ АНАЛИЗА ГИДРОДИНАМИЧЕСКИХ ПАРАМЕТРОВ СТЕНОВОЙ КЕРАМИКИ

Operational frost resistance is one of the main requirements for building materials. The main factors leading to deterioration of the properties of bricks are freeze-thaw cycles. The most reliable way to check building materials for frost resistance is to test products for freeze-thaw cycles. However, the standard method for determining frost resistance is time-consuming, energy-consuming, and requires the use of expensive and difficult-to-use equipment. The engineering industry is interested in reducing the amount of testing time required to assess frost resistance. Researchers have been working for a long time to create express methods for determining the frost resistance of bricks. The article proposes new quantitative criteria for assessing the frost resistance of wall ceramics based on the hydrodynamic parameters of a porous solid. The proposed methodologies for assessing frost resistance make it possible to take into account the textural properties of porous products. As a result of studying the kinetics of water saturation and water yield of ceramic shards, a pattern of the influence of the hysteresis loop area on the frost resistance of wall ceramics was established. Due to their interrelation, regression equations were obtained for the dependence of the hysteresis loop area on the coefficient of water saturation and water yield. Calculation expressions for frost resistance are proposed, where the frost resistance of brick is estimated by the value of the hysteresis loop area or the coefficient of water saturation and water yield.

Influence of average daily gain of heifers on the age of first insemination

The purpose of this study is to establish the influence of average daily gain (ADG) of heifers at different periods of their development on the age of 1st insemination (A1ins) at 12, 13, 14, 15, 16, 17, 18 months and older and milk yield of first-calving cows for 305 days of lactation according to a sample (n=1289) formed from the Seleсs database of one of the breeding plants in the Leningrad region for breeding the Ayrshire breed of dairy cattle. On average for the sample, the correlation coefficient of milk yield with A1ins indicates a negative relationship between these two characteristics (-0.218), a positive correlation of milk yield with live weight of 1st insemination LW1ins (+0.101) with a negative connection with ADG (-0.110). It was revealed that in all age groups of heifers there is a decrease in ADG at the age of 2 months, and the intensity of further development of heifers depends on ADG at the age of 3, 4, 5 months, at a level of over 800 g, contributes to the achievement of A1ins from 12 to 14 months. At the same time ADG at the age of 9—12 months should be at least 800 g. However, even with ADG 800—900 g at the age of 3—5 months, but when these indicators decrease at 9—12 months below 800 g, A1ins increases to 15—16 months. Low ADG at the age of 3—5 months and at the level of 600 - 700 g at the age of 9—12 months increases A1ins to 17 months and older. Thus, for an earlier A1ins and a high level of productivity in the 1st lactation, one should pay attention to the development of heifers at the age of 3—5 months, maintaining the ADG at a high level (more than 800 g) and avoid low weight gain at 9—12 months (less than 800 g).

Performance enhancement of double slope solar still using cylindrical fins: Experimental and numerical analysis

This study explores the enhancement of a double slope solar still (DSSS) by integrating cylindrical fins on the absorber plate to improve heat transfer efficiency and water productivity. The experimental setup, made from galvanized iron sheets and insulated with a wooden box, features a glass cover angled at 34° for optimal solar radiation absorption. Testing was conducted in Gabes, Tunisia, evaluating solar radiation, wind speed, ambient temperature, and water productivity. Measurements were taken from 9:00 a.m. to 6:00 p.m., focusing on distillate yield, temperatures, and heat transfer coefficients. Both experimental and numerical analyses examined the effect of fin diameter on temperature distribution, heat transfer coefficients, and energy efficiency. Results demonstrate that the addition of fins significantly enhances both absorber and water temperatures, with the largest fin diameter (80 mm) achieving a 14.07 % increase. A validated Computational Fluid Dynamics (CFD) model showed a maximum temperature deviation of less than 3.5 °C from experimental data. The study recorded a peak energy efficiency of 71.03 % and a cumulative water productivity of 3252.55 mL/m2.

Oxygen Consumption in Filamentous Pellets of Aspergillus niger: Microelectrode Measurements and Modeling.

Filamentous fungi cultivated as biopellets are well established in biotechnology industries. A distinctive feature of filamentous fungi is that hyphal growth and fungal morphology affect product titers and require tailored process conditions. Within the pellet, mass transfer, substrate consumption, and biomass formation are intricately linked to the local hyphal fraction and pellet size. This study combined oxygen concentration measurements with microelectrode profiling and three-dimensional X-ray microtomography measurements of the same fungal pellets for the first time. This allowed for the precise correlation of micromorphological information with local oxygen concentrations of two Aspergillus niger strains (hyperbranching and regular branching). The generated results showed that the identified oxygen-penetrated outer pellet regions exhibited a depth of 90-290 µm, strain-specific, with the active part percentage in the pellet ranging from 18% to 69%, without any difference between strains. Using a 1D continuum diffusion consumption model, the oxygen concentration in the pellets was computed depending on the local hyphal fraction. The best simulation results were achieved by individually estimating the oxygen-related biomass yield coefficient of the consumption term within each examined pellet, with an average estimated value of 1.95 (± 0.72) kg biomass per kg oxygen. The study lays the foundation for understanding oxygen supply in fungal pellets and optimizing processes and pellet morphologies accordingly.

The kinetics of a two-stage completely stirred tank reactor for treating tofu wastewater by anaerobic digestion

ABSTRACT Tofu wastewater is an inevitable by-product of the bean curd production process. In this study, we used a two-stage continuous stirred tank reactor (CSTR) to treat tofu wastewater. The kinetic analysis of two CSTR reactors was conducted utilizing the material accounting model, microbial accounting model, and first-order kinetic model. The results demonstrated that the methane production coefficient of reactor 1 was 0.00573 LCH4·mg−1 greater than that of reactor 2, which is 0.00533 L CH4·mg−1. The first-order kinetic constants of reactor 1 were poorer than those of reactor 2, and their values are 0.15700 d−1 and 0.11574 d−1, respectively. The microbial yield coefficients of reactors 1 and 2 were 0.009648 and 0.060704, respectively. Under different organic loading rates, the average microbial concentrations were 25.24000 and 2.706667 mg·L−1 for reactors 1 and 2, respectively. The operational performance of the two-stage CSTR anaerobic digestion system was evaluated in order to design a novel and unique method as well as provide a new perspective for enhancing the performance of anaerobic digestion.

Balancing Water Yield and Water Use Efficiency Between Planted and Natural Forests: A Global Analysis.

Climate warming is projected to affect hydrological cycle in forest ecosystems and makes the forest-water relationship more controversial. Currently, planted forests are gaining more public attention due to their role in carbon sequestration and wood production relative to natural forests. However, little is known about how the global patterns and drivers of water yield and water-use efficiency (WUE) differ between planted and natural forests. Here, we conduct a global analysis to compare water yield and WUE in planted and natural forests using 946 observations from 112 published studies. The results showed that global average water yield coefficient was 0.29 for planted forests and 0.34 for natural forests. Planted forests exhibited lower water yield coefficient (p < 0.05) in three climatic regions (arid, dry subhumid, and humid regions), but higher (p < 0.01) WUE only in arid region, compared with natural forests. Both water yield coefficient and WUE in planted forests were significantly lower (p < 0.05) than that in natural forests for stand characteristic groups (stand density, average tree height, leaf area index [LAI], and basal area). Additionally, stand density within the ranging between 1000 to 2000 stem ha-1 can maximize the water yield and WUE in planted and natural forests. Water yield coefficient in planted forests was primarily controlled by the factors related to tree growth (i.e., tree height, DBH), while that of natural forest mainly affected by stand structure (i.e., LAI, stand density, DBH). WUE in planted forest was more sensitive to climate than in natural forests. This work highlights the critical role of natural forests in water supply and the importance of tree species selection and stand management (e.g., stand density adjustment) in plantations in future forest restoration policies and climate change mitigation.

Elucidating the Supramolecular Interaction of Positively Supercharged Fluorescent Protein with Anionic Phthalocyanines.

Developing bioinspired materials to convert sunlight into electricity efficiently is paramount for sustainable energy production. Fluorescent proteins are promising candidates as photoactive materials due to their high fluorescence quantum yield and absorption extinction coefficients in aqueous media. However, developing artificial bioinspired photosynthetic systems requires a detailed understanding of molecular interactions and energy transfer mechanisms in the required operating conditions. Here, the supramolecular self-assembly and photophysical properties of fluorescent proteins complexed with organic dyes are investigated in aqueous media. Supercharged mGreenLantern protein, mutated to have a charge of +22, is complexed together with anionic zinc phthalocyanines having 4 or 16 carboxylate groups. The structural characterization reveals a strong electrostatic interaction between the moieties, accompanied by partial conformational distortion of the protein structure, yet without compromising the mGreenLantern chromophore integrity as suggested by the lack of emission features related to the neutral form of the chromophore. The self-assembled biohybrid shows a total quenching of protein fluorescence, in favor of an energy transfer process from the protein to the phthalocyanine, as demonstrated by fluorescence lifetime and ultrafast transient absorption measurements. These results provide insight into the rich photophysics of fluorescent protein-dye complexes, anticipating their applicability as water-based photoactive materials.

Portfolio Agriculture: A Model for Resilient Regional Agricultural Planning

Food security is threatened by climate change worldwide; consequently, agriculture and farming livelihoods must adapt to new and unpredictable conditions. These conditions vary along spatial scales, and since agricultural yields are sensitive to microclimate conditions, a locally tailored data-driven approach may be helpful. Furthermore, limited agricultural resources like water and labor increasingly constrain food production. This research proposes a regional portfolio model for identifying crop choices and regional portfolio compositions that align with known and forecasted microclimate variation in temperature and humidity. The model will enable farmers to assess tradeoffs between the financial returns and agricultural production risks. The goal of this work is to provide new insights into agricultural planning in the face of climate risk and limited access to water and labor resources. Three steps are taken. Firstly, regional agricultural land is divided into farming subunits, with each representing a terroir characterized by temperature and humidity. Then a simulated yield coefficient is used to assess the effect of microclimate variables on the yield of the different crops in the portfolio of each subunit. Secondly, farming resource allocation, represented by water and labor, across crops and farming subunits is optimized to maximize the yield and associated financial return from farming across the agricultural region. Finally, a resilient agricultural planning model is developed based on the assumed data for regional microclimate and agricultural resources. The results of this research can be used by regional farmers as a reference for selecting crop portfolios and resource allocations to maximize overall profit.

Design and Architecture Definition for Advanced 3D Fan-Out Wafer-Level Packaging

Advanced 2.5D/3D wafer-level fan-out packaging technologies have been studied widely in literature and industry in recent years. Miniaturization, reduction in manufacturing costs, improvement in performance, and lower power consumption using packaging technologies drive increase in interconnect density and pitch scaling. Heterogeneous systems in package used in advanced packaging often include a combination of silicon, epoxy underfill or mold compounds, and organic or inorganic passivation or redistribution layers. This heterogeneity poses challenges with manufacturability, process selection, package architecture, and test vehicle design. The coefficient of thermal expansion mismatch, wafer warpage, and wafer yield are some of the critical process challenges. Delamination of silicon side wall or passivation to epoxy underfill or mold compound, joint fatigue are critical reliability challenges. This article explores various processes and reliability challenges with 3D wafer-level fan-out packaging and provides package design and architecture guidelines to overcome these failure modes. Stacked die-to-wafer test vehicles have been used for data collection. Different assembly materials, processes, and tooling have been evaluated to define comprehensive design rules.

Parametric adjustment of two different kinetic models with constant and variable yield coefficients. Butanol production from glycerol fermentation by Clostridium pasteurianum

The study of bioreactors, for their design and operation, is crucial for optimizing fermentation processes. This can be achieved through computational simulations based on unstructured kinetic models. Generally, unstructured kinetic models are established with yields associated with the concentrations of biomass, substrate, and product of constant type. It has been reported that variable polynomial yields can better describe these processes. Therefore, this work proposes the study of a glycerol fermentation system to produce butanol in the presence of Clostridium pasteurianum. Parametric identification of two unstructured kinetic models (Moser-Boulton and Moser-Levespiel) was performed. Three mass balances were proposed for a batch-operated reactor (biomass, glycerol, and butanol). Constant and variable yields of first, second, and third order were considered. Finally, the simulated data were validated using correlation coefficients with the corresponding experimental data.

Kinetics of cellulase-free endo xylanase hyper-synthesis by Aspergillus Niger using wheat bran as a potential solid substrate

The present study deals with the production of cellulase-free endoxylanase by Aspergillus niger ISL-9 using wheat bran as a solid substrate. Endoxylanase was produced under a solid-state fermentation. Various growth parameters were optimized for the improved production of the enzyme. The Substrate level of 15 g was optimized as it provided the fungus with balanced aeration and nutrition. Among the six moisture contents investigated, Moisture Content 5 (MC5) was optimized (g/l: malt extract, 10; (NH4)2HPO4, 2.5; urea, 1.0) and 10 mL of MC5 was found to give the highest production of endoxylanase. The pH and time of incubation were optimized to 6.2 and 48 h respectively. The Inoculum size of 2 mL (1.4 × 106 spores/mL) gave the maximum enzyme production. After optimization of these growth parameters, a significantly high endoxylanase activity of 21.87 U/g was achieved. Very negligible Carboxymethylcellulase (CMCase) activity was observed indicating the production of cellulase-free endoxylanase. The notable finding is that the endoxylanase activity was increased by 1.4-fold under optimized conditions (p ≤ 0.05). The overall comparison of kinetic parameters for enhanced production of endoxylanase by A. niger ISL-9 under Solid State Fermentation (SSF) was also studied. Different kinetic variables which included specific growth rate, product yield coefficients, volumetric rates and specific rates were observed at 48, 72 and 96 h incubation time and were compared for MC1 and MC5. Among the kinetic parameters, the most significant result was obtained with volumetric rate constant for product formation (Qp) that was found to be optimum (1.89 U/h) at 72 h incubation period and a high value of Qp i.e.1.68 U/h was also observed at 48 h incubation period. Thus, the study demonstrates a cost-effective and environmentally sustainable process for xylanase production and exhibits scope towards successful industrial applications.