Additive Mixture Research Articles

Enhanced High-Solids Fed-Batch Enzymatic Hydrolysis of Sugar Cane Bagasse with Accessory Enzymes and Additives at Low Cellulase Loading

High cellulase loading is still a major impediment in the production of fermentative sugars from high-solids enzymatic hydrolysis of lignocellulosic substrates in the enzyme-based “biorefinery” industry. This study attempted a high-solids (20%) enzymatic hydrolysis of lignocellulosic substrate at a very low cellulase loading with mixed use of additives and accessory enzymes by fed-batch mode. To avoid the high initial biomass viscosity, the high-solids enzymatic hydrolysis of lignocellulosic substrates was initiated with a solids content of 8%. Thereafter, 4% of the additional substrates were consecutively fed into the hydrolysis system after 6, 12, and 18 h to reach a final solids content of 20%. Some additive mixtures (40 mg/g substrateTween 80 + 10 mg/g substrate tea saponin +20 mg/g substrate BSA) were observed to enable this fed-batch hydrolysis to increase 30% of the glucose yield after the 48 h. The combination of these additives and accessory enzymes (2.4 mg/g substrate xylanase and 1 mg/g substra...

An investigation on additives for pelletizing highly torrefied biomass

AbstractThe co‐firing of biomass with coal is usually done using white wood pellets. Compared to coal, white wood pellets come with several disadvantages in terms of lower energy density, higher energy required for milling, and less water stability. One possible measure to counteract these disadvantages is torrefaction. As (intensive) torrefaction leads to the destruction of the binding forces in the wood, the addition of a suitable additive for pelletization is required. The utilization of thermoplastics (LDPE, PP, PS, and EVA) as additives for pelletizing highly torrefied wood with an HHV (higher heating value) of 25.1 MJ kg−1 was tested in a laboratory and in pilot plant‐scale pellet mills. In a first step, the behavior of the single thermoplastics mixed with the torrefied biomass was evaluated. The thermoplastics partly led to lubricating effects and partly to retarding effects, and differed in their adhesive behavior. Based on this information, mixtures of thermoplastics were developed and tested. The best results in this study were achieved using an additive mixture containing 5 wt.% LDPE, 1 wt.% EVA, and 5 wt.% PS based on the mass of torrefied biomass. By using this additive mixture and Kahl's pellet mill 33‐390, the production of pellets complying with ISO/TS 17225‐8:2016 was achieved to a large extent. Only the results concerning pellet stability (PDI) did not fully meet the requirements. The pellets produced showed very good water stability and no visible leaching when immersed in water for 72 hours. The HHV of the torrefied biomass was increased due to the addition of high‐calorie additives from 25.1 to 26.8 MJ kg−1. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd

Phase diagrams and crystal-fluid surface tensions in additive and nonadditive two-dimensional binary hard-disk mixtures.

Using density functionals from fundamental measure theory, phase diagrams and crystal-fluid surface tensions in additive and nonadditive (Asakura-Oosawa model) two-dimensional binary hard-disk mixtures are determined for the whole range of size ratios q=smalldiameter/largediameter, assuming random disorder (lattice points or interstitial occupied by large or small disks at random) in the crystal phase. The fluid-crystal transitions are first order due to the assumption of a periodic unit cell in the density-functional calculations. Qualitatively, the shape of the phase diagrams is similar to the case of three-dimensional hard-sphere mixtures. For the nonadditive case, a broadening of the fluid-crystal coexistence region is found for small q, whereas for large q a vapor-fluid transition intervenes. In the additive case, we find a sequence of spindle-type, azeotropic, and eutectic phase diagrams upon lowering q from 1 to 0.6. The transition from azeotropic to eutectic is different from the three-dimensional case. Surface tensions in general become smaller (up to a factor 2) upon addition of a second species and they are rather small. The minimization of the functionals proceeds without restrictions and optimized graphics card routines are used.

ESPECIALLY THE MATHEMATICAL DESCRIPTION OF RANDOM SIGNALS WITH THREE LEVELS OF QUANTIZATION

The article describes the method of mathematical description of an additive mixture signal with noise when using the three‑level quantization. Method is based on the presentation of the implementation of the signal after quantization in the form of a random discrete 3D vector. It is proposed that statistical calculation technique characteristics of three‑level signals. The technique allows visualizing the probability distribution law of radar signals of different shapes on the background noise and calculating its numeric parameters. Knowledge of the law of probability distributions, assuming that the only inlet noise and distribution law of probability signal with noise allows to calculate the detection quality indicators to build a detector performance. Three‑level quantization allows to considerably simplify the technical implementation of electronic signal processing device with acceptable energy loss.

Structure factors in a two-dimensional binary colloidal hard sphere system

ABSTRACTHard disks are one of the simplest interacting many-body model system in two dimensions (2D). Here, we present a comprehensive set of measurements of the static structure factors for quasi-2D monodisperse fluids and two different binary colloidal hard sphere mixtures: a small size ratio (SSR) system with a negligibly small negative non-additivity and a large size ratio system with a significantly larger non-additivity. We compare the experimental results for the monodisperse and SSR systems to those calculated using density functional theory (DFT) for additive mixtures. Furthermore, we determine the zero-wavevector limits of the static structure factors for the monodisperse and binary hard sphere fluids directly from an analysis of number and concentration fluctuations. For the monodisperse case, this leads to the isothermal compressibility, which agrees very well with DFT, and is consistent with the scaled particle theory equation of state for hard disks. For the binary fluids, the partial static structure factors are used to calculate the Bhatia–Thornton structure factors, and we find qualitative agreement with DFT for the SSR mixture. Finally, the zero-wavevector limits of the Bhatia–Thornton structure factors are determined and directly related to the thermodynamic factor, the dilatation factor and the isothermal compressibility.

Molecular Dynamics Simulation of Water-Based Fracturing Fluids in Kaolinite Slit Pores

The adsorption behavior inside kaolinite mesopores of aqueous solutions of various salts and additives is investigated using Molecular Dynamics simulations. In particular, we examine the various combinations of water + salt, water + additive, and water + salt + additive mixtures, where the salts are NaCl, CsCl, SrCl2, and RaCl2 and the additives are methanol and citric acid. Citric acid is modeled in two forms, namely, fully protonated (H3A) and fully deprotonated (A3–), the latter being prevalent in neutral pH conditions, in accordance with the kaolinite structure employed. The force fields used for the individual system components include CLAYFF for the kaolinite mesopores, SPC/E for water, parameters optimized for the SPC/E water model based on hydration free energies (HFE) for ions, and general Amber force field (GAFF) for the additives. The spatial distributions along the kaolinite pore are delineated and reveal the preferential adsorption behavior of the various species with respect to the gibbsite ...

Digital Signal Extraction by Means of Nonlinear Stochastic Filtration

The results of noise immunity analysis for digital communication systems using methods of nonlinear filtering are given. Nonlinear filtration is based on stochastic resonance effect. The stochastic resonance is given to a phenomenon that is manifest in nonlinear systems where by generally feeble input information (such as a weak signal) can be amplified and optimized by the assistance of noise. The stochastic resonance has been observed in a large variety of systems, including bistable ring lasers, semiconductor devices, chemical reactions, and mechanoreceptor cells in the tail fan of a crayfish. Numeral simulation of response at affecting input of the system on additive mixture of harmonic signal and white Gaussian noise are given. Amplitude spectrum of this output signal has been investigated. Results of the output signal-to-noise ratio calculation of the stochastic filter for the additive sum of a harmonic signal and white Gaussian noise for different values of the input noise dispersion are given. It is shown that the output signal-to-noise ratio of the system will peak at a certain value of noise intensity under a action of the input signal and noise. It is shown that the stochastic resonance effect provides separation of a digital signal from the white Gaussian noise. The comparative analysis of noise immunity of the matched filter and nonlinear stochastic filter for input square pulses are given. The effects of signal distortions in nonlinear processing with a stochastic filter are considered. Calculations of the coefficient of nonlinear distortions of a rectangular pulse are performed. It is shown that nonlinear distortions lead to a decrease in the signal-to-noise ratio at the output of the filter.

Optimization of combustion characteristics of palm kernel-based biofuel for grate furnace

Grate firing is one of the main competing technologies in biomass combustion for steam and electricity generation. Ash generated in the furnace during combustion process would greatly reduce the boiler thermal performance and may lead to unscheduled shutdown. The focus of this study is to optimize the combustion characteristics of the mixture of palm kernel shell (PKS) and selected additives (Al2O3, MgO and CaO) to develop a fuel mixture of low ash yield and higher heating value (HHV). D-Optimal Design under Cross Methodology of Design Expert (6.08) was employed to mix the components alongside various particle sizes. The mixed samples were ashed in a muffle furnace (848 K) to a constant weight and their HHV were determined using Ballistic Bomb Calorimeter. Combustion test based on optimized PKS additive mixture was conducted with a 5 kW grate furnace from which the effects of varying the ratio of primary to secondary air flow rate on temperatures and flue gas compositions from the furnace were measured. The ash obtained after combustion process was characterized using X-ray diffraction (XRD) for the purpose of identifying the mineral phase compounds that are present in PKS and PKS-additive ash. The optimum composition obtained for the process was 2.5, 0.0, 5.0, 92.5% and 5.50 mm for additives (Al2O3, MgO, CaO), PKS and particle size, respectively. The composition resulted in lowest ash yield (0.56%) and HHV (20.64 kJ/g). The coefficient of determination (R2) (0.7951 and 0.7344) and least-square errors (0.19 and 0.024) of the prediction model indicated a close fitness to the experiment results obtained for ash yield and HHV. Primary to secondary air ratio of (40:60) recorded maximum temperature (1058 K), minimum level of CO (285 ppm) and 6% oxygen. XRD results showed excellent interaction between PKS and additives. The appearance of potassium-alumino silicate (KAlSiO4) in the PKS-additive ash prevented the release of potassium chloride which has the ability to increase ash deposition and corrosion.

STUDY ON THE CLARIFYING ADDITIVES FOR HIGH DENSITY POLYETHYLENE

Bis-3,4- dimethyldibenzylidene sorbitol (DMDBS); bis-p-methylbenzylidene sorbitol (MDBS) and the mixture of DMDBS/MDBS (50/50) were studied through optical, thermal, mechanical properties and surface morphology. With the same amount of additive (DMDBS/MDBS mixture and DMDBS) in the material, the results are similar. On the other hand, using an additive mix reduces the cost of production due to MDBS. Furthermore, the additive mixture is used without producing odours. Therefore, the mixture of DMDBS/MDBS (50/50) is chosen.

Ethanol addictively enhances the in vitro cardiotoxicity of cocaine through oxidative damage, energetic deregulation, and apoptosis.

Cocaine (COC) is frequently consumed in polydrug abuse settings, and ethanol (EtOH) is the most prominent co-abused substance. Clinical data and experimental evidence suggest that the co-administration of COC with EtOH can be more cardiotoxic than EtOH or COC alone, but information on the molecular pathways involved is scarce. Since these data are crucial to potentiate the identification of therapeutic targets to treat intoxications, we sought to (i) elucidate the type of interaction that occurs between both substances, and (ii) assess the mechanisms implicated in the cardiotoxic effects elicited by COC combined with EtOH. For this purpose, H9c2 cardiomyocytes were exposed to COC (104µM-6.5mM) and EtOH (977µM-4M), individually or combined at a molar ratio based on blood concentrations of intoxicated abusers (COC 1: EtOH 9; 206µM-110mM). After 24h, cell metabolic viability was recorded by the MTT assay and mixture toxicity expectations were calculated using the independent action (IA) and concentration addition (CA) models. EtOH (EC50 305.26mM) proved to act additively with COC (EC50 2.60mM) to significantly increase the drug in vitro cardiotoxicity, even when both substances were combined at individually non-cytotoxic concentrations. Experimental mixture testing (EC50 19.18 ± 3.36mM) demonstrated that the cardiotoxicity was fairly similar to that predicted by IA (EC50 22.95mM) and CA (EC50 21.75mM), supporting additivity. Concentration-dependent increases of intracellular ROS/RNS and GSSG, depletion of GSH and ATP, along with mitochondrial hyperpolarization and activation of intrinsic, extrinsic, and common apoptosis pathways were observed both for single and combined exposures. In general, the mixture exhibited a toxicological profile that mechanistically did not deviate from the single drugs, suggesting that interventions such asantioxidant administration might aid in the clinical treatment of this type of polydrug intoxication. In a clinical perspective, the observed additive mixture effect may reflect the increased hazards at which users of this combination are exposed to in recreational settings.

STUDY OF THE EFFECTS OF GYMPSUM, POZZOLANIC ADDITIVE MIXTURES AND THEIR FINENESS ON THE STRENGTH OF PCB50 FICO CEMENT

In the study, raw materials including clinker, gypsum, pozzolan were separately milled on a ball mill (the ball mill size: φ500 mm × L500 mm, productivity: 5 kg / grinding time) to achieve the desired blaine fineness. A mixture is mixed at the calculated ratio includes of 90 % fineness clinker, 5 % fineness gypsum and 5 % fineness pozzolan (In it, pozzolanic additive is mixed at different fineness levels). The effects of the mixture of gypsum and fineness pozzolanic additive as well as the fineness of pozzolanic additive to strength of PCB50 Fico cement were investigated. The study shows that, pozzolanic additive have reduced the strength of cement. But, when pozzolanic additive is mixed with gypsum, this additive mixture has increased the strength of the cement at the late time (at the age of 28 days). The fineness of pozzolan has little effected on the early strength of cement.

Structural-dynamical transition in the Wahnstr\xf6m mixture

.In trajectory space, dynamical heterogeneities in glass-forming liquids correspond to the emergence of a dynamical phase transition between an active phase poor in local structure and an inactive phase which is rich in local structure. We support this scenario with the study of a model additive mixture of Lennard-Jones particles, quantifying how the choice of the relevant structural and dynamical observable affects the transition in trajectory space. We find that the low mobility, structure-rich phase is dominated by icosahedral order. Applying a non-equilibrium rheological protocol, we connect local order to the emergence of mechanical rigidity.Graphical abstract

Establishment and verification of prediction models of creep instability points of asphalt mixtures at high temperatures

This study established and verified prediction models of the creep instability points of two densely graded asphalt mixtures at high temperatures. First, AC-13 and AC-20 asphalt mixtures were selected and prepared. Their compressive strength values under different confining pressures and shear strength parameters were obtained through triaxial compression tests at 60 °C. Second, multiple repeated pressure values, which were less than the compressive strength values under the same confining pressure, were applied in dynamic triaxial creep tests at 60 °C, and the rheological numbers (FN) corresponding to the creep instability points of the asphalt mixtures were obtained. Third, prediction models of the different asphalt mixtures were established by analyzing the change law of FN under different confining and cyclic loading pressures. Finally, the FN values of the different additive mixtures were forecasted using the models. The reliability of the prediction results was successfully verified by the test results. The predicted FN values of the two asphalt mixtures were consistent with the experimental results at 60 °C. The proposed prediction models and the model establishment method can be of great significance in investigating the properties of asphalt mixtures at high temperatures and asphalt pavement rutting.

Sppmix: Poisson point process modeling using normal mixture models

This paper describes the package sppmix for the statistical environment R. The sppmix package implements classes and methods for modeling spatial point patterns using inhomogeneous Poisson point processes, where the intensity surface is assumed to be a multiple of a finite additive mixture of normal components and the number of components is a finite, fixed or random integer. Extensions to the marked inhomogeneous Poisson point processes case are also presented. We provide an extensive suite of R functions that can be used to simulate, visualize and model point patterns, estimate the parameters of the models, assess convergence of the algorithms and perform model selection and checking in the proposed modeling context. In addition, several approaches have been implemented in order to handle the standard label switching issue which arises in any modeling approach involving mixture models. We adapt a hierarchical Bayesian framework in order to model the intensity surfaces and have implemented two major algorithms in order to estimate the parameters of the mixture models involved: the data augmentation and the birth–death Markov chain Monte Carlo (DAMCMC and BDMCMC). We used C++ (via the Rcpp package) in order to implement the most computationally intensive algorithms.

Mixture effects in samples of multiple contaminants – An inter-laboratory study with manifold bioassays

Chemicals in the environment occur in mixtures rather than as individual entities. Environmental quality monitoring thus faces the challenge to comprehensively assess a multitude of contaminants and potential adverse effects. Effect-based methods have been suggested as complements to chemical analytical characterisation of complex pollution patterns. The regularly observed discrepancy between chemical and biological assessments of adverse effects due to contaminants in the field may be either due to unidentified contaminants or result from interactions of compounds in mixtures. Here, we present an interlaboratory study where individual compounds and their mixtures were investigated by extensive concentration-effect analysis using 19 different bioassays. The assay panel consisted of 5 whole organism assays measuring apical effects and 14 cell- and organism-based bioassays with more specific effect observations. Twelve organic water pollutants of diverse structure and unique known modes of action were studied individually and as mixtures mirroring exposure scenarios in freshwaters. We compared the observed mixture effects against component-based mixture effect predictions derived from additivity expectations (assumption of non-interaction). Most of the assays detected the mixture response of the active components as predicted even against a background of other inactive contaminants. When none of the mixture components showed any activity by themselves then the mixture also was without effects. The mixture effects observed using apical endpoints fell in the middle of a prediction window defined by the additivity predictions for concentration addition and independent action, reflecting well the diversity of the anticipated modes of action. In one case, an unexpectedly reduced solubility of one of the mixture components led to mixture responses that fell short of the predictions of both additivity mixture models. The majority of the specific cell- and organism-based endpoints produced mixture responses in agreement with the additivity expectation of concentration addition. Exceptionally, expected (additive) mixture response did not occur due to masking effects such as general toxicity from other compounds. Generally, deviations from an additivity expectation could be explained due to experimental factors, specific limitations of the effect endpoint or masking side effects such as cytotoxicity in in vitro assays. The majority of bioassays were able to quantitatively detect the predicted non-interactive, additive combined effect of the specifically bioactive compounds against a background of complex mixture of other chemicals in the sample. This supports the use of a combination of chemical and bioanalytical monitoring tools for the identification of chemicals that drive a specific mixture effect. Furthermore, we demonstrated that a panel of bioassays can provide a diverse profile of effect responses to a complex contaminated sample. This could be extended towards representing mixture adverse outcome pathways. Our findings support the ongoing development of bioanalytical tools for (i) compiling comprehensive effect-based batteries for water quality assessment, (ii) designing tailored surveillance methods to safeguard specific water uses, and (iii) devising strategies for effect-based diagnosis of complex contamination.

Dynamic pH determination at high pressure of aqueous additive mixtures in contact with dense CO2

A system consisting of a high-pressure tolerant microfluidic glass chip, high-speed absorbance imaging, and image processing has been developed to study rapid dynamic events like pH change in a multiphase flow. The system gives both kinetic and quantitative equilibrated information. By tracking the interactions of aqueous additive mixtures and liquid CO2, at 80 bar and 24 °C, under flow, measurement at a given P, T condition is done in 0.25 s. The acidification rate to steady state was found to be mass transport limited, occurring in less than 1 s. For 30 mM of the additives ammonium acetate and ammonium formate, equilibrium pH of 4.5 and 4.1, respectively, was seen. These additives are of key importance in common mobile phases used in SFC.

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC50) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures.

Effect of corn and soybean oil derived additives on polymer-modified HMA and WMA master curve construction and dynamic modulus performance

In previous work, Isosorbide Distillation Bottoms (IDB), and other isosorbide and soybean based materials with similar properties were shown to act as antistrips in a polymer modified warm mix asphalt (WMA) at a 0.75% dosage level both through visual observations and statistical analysis of Hamburg Wheel Tracking Device (HWTD) test results. Because of this evidence, there is an interest in how specimens produced with isosorbide and soybean bio-derived chemical additives would perform in the dynamic modulus test, as this is the main input used in AASHTOWare Pavement ME in the prediction of rutting performance. The main objective of this research is to compare and contrast dynamic modulus performance of two isosorbide, two soybean bio-derived chemical additive mixtures against each other and controls compacted at both hot mix asphalt (HMA) and WMA compaction temperatures. Master curve modeling with a proposed new (PN) model based on the Yang and You model and Booij and Thoone model for phase angle (δ) master curve construction led to the conclusion that proper placement of coefficients makes it possible to maintain precision and accuracy in the determination of E∗ master curves while co-determining δ master curves. From the master curve results, it was observed that some of the corn and soybean bio-derived chemical additives may be affecting the viscous behavior at intermediate and high test temperatures. Results from statistical analysis were inconclusive, and thus it is felt that further work must be done comparing HMA and WMA produced specimens in the HWTD test.

Effects of oxygenate additive mixture on the performance and emission characteristics of a biodiesel fuelled compression ignition engine

An experimental investigation was conducted to discover the effects of oxygenate mixture as additives in Jatropha biodiesel on the performance and emission characteristics of a direct injection compression ignition engine. The experiments were conducted in an instrumented single cylinder air cooled four stroke direct injection diesel engine (running at constant speed of 1500 rpm and injection timing of 26° bTDC), AC alternator and an electric loading device. Four oxygenate additives, namely, Dimethyl carbonate (C3H6O3), Ethylene glycol (C2H6O2), Propylene glycol (C3H8O2) and 2-Butoxyethanol (C6H14O2) were selected, and nine different combinational oxygenate test fuels were prepared attaining ratios of 1, 2 and 4% volume of oxygenates with biodiesel. Reduction in CO by 60%, Unburned HC by 11% and smoke emissions by 27% were observed for the test fuels without conciliating the brake thermal efficiency improvement by 6%, while NO emission increased marginally by 4%.

ANALISA PENGARUH PENAMBAHAN ZAT ADITIF ALAMI PADA BENSIN TERHADAP EMISI GAS BUANG UNTUK SEPEDA MOTOR 4 LANGKAH

ABSTRAK
 
 Dampak dari perkembangan teknologi otomotif mengakibatkan kebutuhan bahan bakar juga semakin meningkat. Dalam hal ini zat aditif digunakan untuk memberikan peningkatan sifat dasar dan nilai angka oktan tinggi untuk dapat meningkatkan kinerja mesin. Variabel penelitian meliputi variabel bebas yaitu prosentase campuran zat aditif dan premium sedangkan variabel terikat berupa emisi gas buang. Data yang diperoleh akan diplotkan pada grafik. dan akan dijadikan acuan untuk menilai besarnya pengaruh pemakaian zat aditif terhadap emisi gas buang yang dihasilkan. Dengan penambahan zat aditif akan memperbaiki proses pembakaran yang akan menurunkan kadar CO, CO2, HC, meningkatkan konsumsi oksigen (O2) dan akan menghilangkan senyawa NOx. Dari hasil penelitian yang dilakukan di dapat bahwa penurunan senyawa emisi gas buang yang signifikan terjadi pada Kadar CO yang di hasilkan oleh bensin yang telah di campur zat aditif konsentrasi (0.2 g :100 ml) pada putaran 1.000 rpm adalah 0.60% dengan penurunan sebesar 0.09%. Nilai penurunan yang terjadi pada putaran 1.000 rpm pembakaran menjadi lebih baik karena panas yang di hasilkan lebih stabil.