Mixing Sample Research Articles

Determination of thermal properties of grouting materials for borehole heat exchangers (BHE)

Thermal properties of grouting materials for borehole heat exchangers (BHE) are currently analysed with varying measurement methods and analysis procedures, resulting in difficulties when comparing values of different studies. This study therefore provides the first comprehensive investigation of different analysis procedures by systematically comparing the influence of the measurement method and the sample preparation on the determination of the thermal conductivity and the volumetric heat capacity. Seven dissimilar grouting materials with varying water–solid ratios (W/S) and compositions are analysed. The thermal conductivities of the materials range between 0.9 and 1.8 W m−1 K−1 (transient plane source method, TPS). The volumetric heat capacities range between 3.01 and 3.63 MJ m−3 K−1 (differential scanning calorimetry, DSC). From the findings of this study, a standardised analysis of grouting materials is provided which suggests mixing of the grouting material at a high mixing speed and sample curing under water for 28 days at room temperature. The benefits of calculating the volumetric heat capacities of grouting materials from the specific heat capacities of dry samples measured with the DSC, the water content and the bulk density are demonstrated. Furthermore, an estimation procedure of volumetric heat capacity from the W/S and suspension density with an uncertainty of smaller ± 5% is provided. Finally, this study contributes to consistency and comparability between existing and future studies on the thermal properties of grouting materials.

Adjusted empirical likelihood for probability density functions under strong mixing samples

To obtain a profile empirical likelihood ratio statistic is essentially to address a constrained maximization problem. However, when sample size is small, the optimal function may have no numerical solution, as the convex hull of the sample points may not contain the zero vector 0 as its interior point. The adjusted empirical likelihood (AEL) method introduced by Chen, Variyath, and Abraham (2008) is very useful to solve this problem. The innovation of this article is that we extend the AEL method to probability density functions (p.d.f.) under dependent samples, as there are few literatures using this method under dependent samples. It is shown that the AEL ratio statistic for a p.d.f. is asymptotically χ 2 -type distributed under a mixing sample, which is used to obtain an AEL-based confidence interval for the p.d.f. Our simulations show that the AEL is faster to compute than unadjusted empirical likelihood and the coverage probability based on the AEL method is superior to the other two usual methods, namely the unadjusted empirical likelihood and the normal approximation methods, particularly under small sample sizes.

Measuring the Time-evolution of Nanoscale Materials with Stopped-flow and Small-angle Neutron Scattering.

This paper presents the use of a stopped-flow small-angle neutron-scattering (SANS) sample environment to quickly mix liquid samples and study nanoscale kinetic processes on time scales of seconds to minutes. The stopped-flow sample environment uses commercially available syringe pumps to mix the desired volumes of liquid samples that are then injected through a dynamic mixer into a quartz glass cell in approximately 1 s. Time-resolved SANS data acquisition is synced with the sample mixing to follow the evolution of the nanostructure in solution after mixing. To make the most efficient use of neutron beam time, we use a series of flow selector valves to automatically load, rinse, and dry the cell between measurements, allowing for repeated data collection throughout multiple sample injections. Sample injections are repeated until sufficient neutron scattering statistics are collected. The mixing setup can be programmed to systematically vary conditions to measure the kinetics at different mixing ratios, sample concentrations, additive concentrations, and temperatures. The minimum sample volume required per injection is approximately 150 µL depending on the path length of the quartz cell. Representative results using this stopped-flow sample environment are presented for rapid lipid exchange kinetics in the presence of an additive, cyclodextrin. The vesicles exchange outer-leaflet (exterior) lipids on the order of seconds and fully exchange both interior and exterior lipids within hours. Measuring lipid exchange kinetics requires in situ mixing to capture the faster (seconds) and slower (minutes) processes and extract the kinetic rate constants. The same sample environment can also be used to probe molecular exchange in other types of liquid samples such as lipid nanoparticles, proteins, surfactants, polymers, emulsions, or inorganic nanoparticles. Measuring the nanoscale structural transformations and kinetics of exchanging or reacting systems will provide new insights into processes that evolve at the nanoscale.

Melt- vs. Non-Melt Blending of Complexly Processable Ultra-High Molecular Weight Polyethylene/Cellulose Nanofiber Bionanocomposite.

The major hurdle in melt-processing of ultra-high molecular weight polyethylene (UHMWPE) nanocomposite lies on the high melt viscosity of the UHMWPE, which may contribute to poor dispersion and distribution of the nanofiller. In this study, UHMWPE/cellulose nanofiber (UHMWPE/CNF) bionanocomposites were prepared by two different blending methods: (i) melt blending at 150 °C in a triple screw kneading extruder, and (ii) non-melt blending by ethanol mixing at room temperature. Results showed that melt-processing of UHMWPE without CNF (MB-UHMWPE/0) exhibited an increment in yield strength and Young’s modulus by 15% and 25%, respectively, compared to the Neat-UHMWPE. Tensile strength was however reduced by almost half. Ethanol mixed sample without CNF (EM-UHMWPE/0) on the other hand showed slight decrement in all mechanical properties tested. At 0.5% CNF inclusion, the mechanical properties of melt-blended bionanocomposites (MB-UHMWPE/0.5) were improved as compared to Neat-UHMWPE. It was also found that the yield strength, elongation at break, Young’s modulus, toughness and crystallinity of MB-UHMWPE/0.5 were higher by 28%, 61%, 47%, 45% and 11%, respectively, as compared to the ethanol mixing sample (EM-UHMWPE/0.5). Despite the reduction in tensile strength of MB-UHMWPE/0.5, the value i.e., 28.4 ± 1.0 MPa surpassed the minimum requirement of standard specification for fabricated UHMWPE in surgical implant application. Overall, melt-blending processing is more suitable for the preparation of UHMWPE/CNF bionanocomposites as exhibited by their characteristics presented herein. A better mechanical interlocking between UHMWPE and CNF at high temperature mixing with kneading was evident through FE-SEM observation, explains the higher mechanical properties of MB-UHMWPE/0.5 as compared to EM-UHMWPE/0.5.

In-a-syringe surfactant-assisted dispersive liquid-liquid microextraction of polycyclic aromatic hydrocarbons in supramolecular solvent from tea infusion

In this work, an automated surfactant-assisted dispersive liquid-liquid microextraction approach based on in-a-syringe concept was developed for the first time. The procedure assumed mixing aqueous sample phase and hydrophilic emulsion containing hexanoic acid and sodium hexanoate in a syringe of flow system. Sodium hexanoate acted as an emulsifier in dispersive liquid-liquid microextraction process and it was required for the formation of supramolecular solvent phase. After spontaneous separation of phases in the syringe, the upper supramolecular solvent phase containing target analytes was withdrawn and analyzed. The procedure was applied to the determination of 13 polycyclic aromatic hydrocarbons in tea infusion by high performance liquid chromatography with fluorescence detection. It was shown that the supramolecular solvent provided effective extraction of polycyclic aromatic hydrocarbons and fast phase separation in the syringe without centrifugation. The enrichment factors were in the range of 38–46. The automated microextraction procedure lasted 4 min including syringe cleaning. Under optimal experimental conditions the linear detection ranges were found to be 0.05–50.00 μg L−1 with limits of detection calculated from a blank test, based on 3σ, 0.02–0.04 μg L−1. Recovery values in the range of 85–105% were achieved for tea infusion with a reproducibility expressed as RSD less than 4.1%.

Codigestion of Food Waste with Used Lipids as Substrate Material to Produce Biogas

Anaerobic co-digestion of food wastes process is represents an active technique to enhance the production of biogas as one of the clean energy sources. The effects of adding lipids as substrate material to the food waste mixture for producing biogas by anaerobic co-digestion are experimentally investigated and evaluated at various mixing ratios in the present work. The influence of lipids and food waste (potatoes, tomato, Carrots, Cellulose) mixing ratios, digestion time and other factors on production of the biogas and CH4, CO2 and H2S percent are investigated experimentally. Seven samples of substrate mixtures (used edible oil, waste food, cow dung and water) with various mixing ratios were tested during 32 days as digestion period to investigate the influence of lipids percent compared to food waste on biogas yield. The results show that, average biogas production was in range of 100-160 ml per day and the maximum percent of Ch4 and CO2 were 52% and 46% respectively for the produced biogas. Increasing the lipids percent in the substrates mixture could enhanced the biogas and CH4 production. The mixing sample containing 70% lipids and 30% food waste percent was produced significantly higher biogas and CH4 yields compared to the other mixing samples. Best digestion time of the food waste-lipid mixtures was observed in range of 12-16 days for the tested samples. The maximum cumulative biogas was 5120 ml which was produced by substrate mixture (70% lipid and 30% solid waste) during digestion time 32 days.

Recursive Kernel Density Estimation for Time Series

We consider the recursive estimation of the probability density function of continuous random variables from a strongly mixing random sample. We revisit here earlier research on this subject by considering a more general class of recursive estimators, including the usual ones. We derive the quadratic mean error of the considered class of estimators. Moreover, we establish a central limit theorem by using Lindeberg's method resulting in a simplification of the existing assumptions on the sequence of smooth parameters and the mixing coefficient. This is the main contribution of this paper. Finally, the feasibility of the proposed estimator is illustrated throughout an empirical study.

Forced SHS Compaction of Ti–B Blends: Influence of Mixing Conditions and Sample Mass

We explored the influence of mixing (milling) conditions and sample mass on forced SHS compaction of equiatomic Ti–B blends. An increase in mill/ball ratio was found not only give start to mechanochemical synthesis but also affected the processes of combustion and product patterning. The mass of green compacts did not affect combustion temperature. Our results may turn interesting to those engaged in combustion synthesis of new materials.

Phenol removal from synthetic wastewater with powdered activated carbon: Isotherms, kinetics and thermodynamics

Phenol is the 11th most toxic 126 chemical substance and causes cancer by accumulating in the food chain. Adsorption of phenol is an effective and also environmentally friendly method for its removal. In this study, phenol removal by using powdered activated carbon (PAC) was optimized and modeled for various isotherms at constant mixing rate (150 rpm) and sample volume (100 mL); adsorbent dose (0.01-2 g), contact time (1-180 min), and initial phenol concentration (50-1000 mg L-1). Moreover, adsorption studies were carried out at different temperatures for kinetic and thermodynamic calculations. In this study, optimum adsorbent dose and contact time of PAC were determined as 0.3 g 100 mL-1 (3 g L-1) and 10 minute, respectively. It can be concluded that it provides discharge standards for a wastewater containing 100 mg L-1 phenol. It was observed that the adsorption capacity decreased with increasing temperature and the adsorption process fits well with Langmuir isotherm. It has been concluded that the adsorption of phenol with PAC is an exothermic reaction. As a result of the kinetic studies, it was found to be suitable for the Pseudo Second Order (R2 0.9999-1.0000). ∆S, ∆H and ∆G were calculated as -0.02 J mol-1 K-1, -14.15 kJ mol-1 and between -8.16 and -7.76 kJ mol-1, respectively.

Performance of apricot stone to remove dyes from aqueous solutions – Equilibrium, kinetics, isotherms modeling and thermodynamic studies

This study investigates the potential use of activated carbon prepared from Apricot stone with H3PO4 activation as an adsorbent and its ability to removal dyes from aqueous solutions. The quantitative kinetics and equilibrium adsorption parameters for activated carbon ASAC were studied by UV visible absorption spectroscopy. ASAC with a specific surface area (88.04 m2/g) respectively are characterized by the Brunauer-Emmett-Teller (BET) method and the point of zero charge pHpzc.The infrared spectra of (ASM) were recorded with Fourier transform Bomen-Michelson type spectrometer by mixing (AS) sample (∼2% wt.) with KBr of spectroscopic in a range of 4000–400 cm−1. The adsorptive properties of the adsorbent with dyes are conducted at variable process parameters such as initial pH, adsorbent dosage, initial dye ion concentration, contact time and temperature were investigated in their respective range and their optimum conditions were ascertained using batch mode operation to find the optimal conditions for a maximum adsorption. The equilibrium adsorption data for dyes onto ASAC is analyzed by the Langmuir, Freundlich, Elovich, and Temkin models. The results indicate that the Langmuir model provides the best correlation. Kinetic parameters; rate constants, equilibrium adsorption capacities and determination coefficients, for each kinetic and isotherm model were calculated and discussed. The pseudo-second order model fit the kinetic data better than the pseudo-first order model and the intraparticle diffusion and film diffusion mechanisms jointly influenced the adsorption process but the latter was the rate-controlling step.The adsorption isotherms at different temperatures have been used for the determination of thermodynamic parameters such as Free Energy (ΔGo), Enthalpy (ΔHo), Entropy (ΔSo) and Activation Energy (Ea) of adsorption. The negative ΔGo and positive ΔHo values indicate that the overall adsorption is spontaneous and endothermic in nature.

In Situ Compositing CsPbBr3 with Exfoliated Layered-Perovskite CsCa2Ta3O10: Interfacial Interaction and Enhanced Stability.

Cesium lead halide (CsPbX3, X = Cl, Br, I) perovskite quantum dots (QDs) have been intriguing optoelectronic materials for applications in various devices owing to their superior electronic and optical properties. However, poor resistance to humidity and light irradiation impedes their promotion. Herein, bulk perovskite-type layered CsCa2Ta3O10 is exfoliated into two-dimensional (2D) negatively charged Ca2Ta3O10- (CTO) nanosheets as seeds to in situ synthesize and composite CsPbBr3. The as-synthesized CsPbBr3/CTO nanocomposites possess improved green emission with apparently prolonged decay time with reference to bare CsPbBr3 QDs. The decay time can retrieve to a normal state when the nanocomposites are treated with some water. It is found that the CTO acts as a defect to trap the bound exciton of the loaded CsPbBr3. Protons from water can preferably replace Cs+ at the interface of the nanocomposites, resulting in the separation of the nanosheets and CsPbBr3 and retrieving the decay time. X-ray photoelectron spectroscopy results also indicate the strong interaction between CsPbBr3 and CTO with reference to the physical mixing sample of bare CsPbBr3 QDs and CTO nanosheets. The decoration of ultrathin 2D charge-bearing oxide nanosheets on the QDs benefits significant improvements in humidity resistance and photostability performance in light-emitting diode devices. This research offers a distinct strategy to modify the surface of perovskite QDs.

HPLC-MS/MS determination of non-steroidal anti-inflammatory drugs in bovine milk based on simultaneous deep eutectic solvents formation and its solidification

A simple, rapid, eco-friendly and effective microextraction procedure for separation and preconcentration of nonsteroidal anti-inflammatory drugs (NSAIDs) from bovine milk samples based on in situ deep eutectic solvents formation between menthol and NSAIDs and its solidification was developed. The procedure involved alkaline hydrolysis of sample matrix, mixing aqueous sample phase with molten menthol to obtain deep eutectic solvents and analytes extraction followed by organic phase (extract) separation based on its solidification. The conditions of in situ deep eutectic solvents formation were optimized and used for the HPLC-MS/MS determination of diclofenac, flurbiprofen, ketoprofen and mefenamic acid in bovine milk samples. The developed approach allowed to exclude matrixes effects and increase enrichment factors of target analytes. The LODs, calculated from the blank tests based on 3σ, were 0.01, 0.01, 0.01 and 0.03 μg kg−1, for diclofenac, flurbiprofen, ketoprofen and mefenamic acid, respectively. The procedure was successfully applied to the analysis of real samples.

A 3D printed centrifugal microfluidic platform for spilled oil enrichment and detection based on solid phase extraction (SPE)

Portable devices for real time monitoring of oil pollution in coastal water can be very useful in environmental protections. This is particularly true after the disastrous BP oil spill in Gulf of Mexico and huge amount of residual oil drifted to the costal water system. Fluorescence detection method is one of the most popular method adopted to determine the existence and concentration of the oil in water. When polycyclic aromatic hydrocarbons (PAHs) in crude oil is excited by ultra-violet (UV) light, fluorescent light with wavelengths from 400 nm to 650 nm is emitted. To realize the detection of trace oil pollution in water, solid phase extraction (SPE) is widely used to enrich the PAHs in the sample for enhanced detection sensitivity. However, conventional methods to enrich and detect PAHs usually need to be conducted in the lab because professional equipment are required and the operations are complicated and time consuming. This paper reports a novel centrifugal microfluidic platform for automatically detecting trace oil pollution in test sample. Mechanical valves were used to control the flow of the reagents and water sample in the device. The prototype of the proposed system was fabricated using 3D printing technology and tested with 10 ppm standard oil-water mixing sample. Different stationary sorbents were tested and compared. The experimental results had proved that the detection sensitivity of the water-oil mixture sample can be significantly enhanced after it was enriched using the centrifugal microfluidic platform. The study has proved the functionality of the 3D printed centrifugal microfluidic platform and demonstrated it can potentially be used as a portable, real time, in-situ detection for oil detection device.

From the peat bog to the estuarine mixing zone: Common features and variances in riverine dissolved organic matter determined by non-targeted analysis

Abstract Land-derived dissolved organic matter (DOM) is able to transport iron and other trace metals from natural organic matter (NOM)-rich areas like peat bogs via rivers to the open ocean and therefore plays a pivotal role in the iron supply of coastal marine organisms. Iron is distributed over all DOM size-fractions and predominantly found in large clusters in river waters, but a shift towards lower molecular weight is observed on the way to the mixing zone. As the involved ligands are still largely unknown, a workflow was established targeting low molecular weight DOM constituents between 100 and 700 Da to provide an additional tool for DOM characterization employing the high performance of time-of-flight mass spectrometry (TOFMS) in the low mass range. An estuarine mixing zone sample from the Halladale River with high iron content, a natural organic matter-(NOM) rich creek water sample from Craggie Burn, which is a tributary of the Halladale River (Scotland, UK), and a NOM sample from the Suwannee River (Georgia, USA) were investigated by reversed phase and hydrophilic interaction liquid chromatography combined with electrospray-ionization time-of-flight mass spectrometry. Non-targeted evaluation of the accurate mass data employing state-of-the-art feature detection and alignment tools was performed. Several compounds could be identified utilizing authentic standards clearly demonstrating that the employed workflow is able to provide valid information about low molecular weight constituents of DOM. It was shown that the three investigated samples share a significant proportion of the annotated molecular formulas though they vary in seawater content and origin, especially in the protein type region of the van Krevelen plot. Those compounds seem to be resistant to salting out or further degradation. Moreover, the lignin and tannin type region is largely overlapping in the Craggie Burn and the Suwannee River samples, but almost completely absent in the Halladale River sample. Therefore, our findings support the view that land-derived lignin and tannin structures can transport iron to the estuary, where they are degraded and ligand exchange takes place.

In situ synthesis of C-TiO2/g-C3N4 heterojunction nanocomposite as highly visible light active photocatalyst originated from effective interfacial charge transfer

In this paper, a simple one-pot hydrothermal strategy was adopted to prepare C-TiO2/g-C3N4 nanocomposite. Simultaneously, the photocatalytic performance of the C-TiO2/g-C3N4 nanocomposite like tunable ratio was evaluated by the degradation of methyl orange (MO) under visible light irradiation. The prepared nanocomposite with the mass ratio of 27:8 (C-TiO2/g-C3N4(0.08)) possessed the highest photocatalytic activity, about 5.1, 3.8 and 2.3 times higher than that of C-TiO2, g-C3N4, and the Mixing sample, respectively. The excellent photocatalytic performance was attributed to the improvement of light harvesting and charge separation caused by construction of heterojunction. In addition, interfacial charge transfer through CTi bond and NTi bond also played a crucial role in inhibiting the recombination of electron-hole pairs and increasing the concentrations of holes and electrons, separately, which was confirmed by XPS analysis, photocurrent response experiment, electrochemical impedance spectroscopy measurements, PL spectra and Time-resolved PL spectra. Besides, the importance of active species during the reaction process was explored, and the generation of h+, O2−, OH in the photocatalytic process was also demonstrated. Among this, O2− played an important role. This finding about chemically bonded C-TiO2/g-C3N4 nanocomposite provided a good guidance for the fabrication of new heterogeneous photocatalysts and facilitated their applications in environmental protection, water splitting and so on.

Fast Hamiltonian Monte Carlo Using GPU Computing

In recent years, the Hamiltonian Monte Carlo (HMC) algorithm has been found to work more efficiently compared to other popular Markov chain Monte Carlo (MCMC) methods (such as random walk Metropolis–Hastings) in generating samples from a high-dimensional probability distribution. HMC has proven more efficient in terms of mixing rates and effective sample size than previous MCMC techniques, but still may not be sufficiently fast for particularly large problems. The use of GPUs promises to push HMC even further greatly increasing the utility of the algorithm. By expressing the computationally intensive portions of HMC (the evaluations of the probability kernel and its gradient) in terms of linear or element-wise operations, HMC can be made highly amenable to the use of graphics processing units (GPUs). A multinomial regression example demonstrates the promise of GPU-based HMC sampling. Using GPU-based memory objects to perform the entire HMC simulation, most of the latency penalties associated with transferring data from main to GPU memory can be avoided. Thus, the proposed computational framework may appear conceptually very simple, but has the potential to be applied to a wide class of hierarchical models relying on HMC sampling. Models whose posterior density and corresponding gradients can be reduced to linear or element-wise operations are amenable to significant speed ups through the use of GPUs. Analyses of datasets that were previously intractable for fully Bayesian approaches due to the prohibitively high computational cost are now feasible using the proposed framework.

Mass spectrometry-based monitoring of millisecond protein-ligand binding dynamics using an automated microfluidic platform.

Characterizing protein-ligand binding dynamics is crucial for understanding protein function and for developing new therapeutic agents. We present a novel microfluidic platform that features rapid mixing of protein and ligand solutions, variable incubation times, and an integrated electrospray ionization source for mass spectrometry-based monitoring of protein-ligand binding dynamics. This platform offers many advantages, including solution-based binding, label-free detection, automated operation, rapid mixing, and low sample consumption.

Polymer supported graphene–CdS composite catalyst with enhanced photocatalytic hydrogen production from water splitting under visible light

A polymer supported graphene structure was synthesized using organic microspheres as the support of the graphene oxide. Graphene oxide was reduced to graphene and CdS was decorated on the surface of the graphene through a solvothermal process. The photocatalytic hydrogen production reaction was carried out using the composite catalyst under visible light irradiation (λ>400nm). A series of composite catalysts were synthesized with different reaction time. The maximal hydrogen production rate of 175μmolh−1 was obtained from the 3h prepared sample (PSGM/rGO/CdS-3), which is 19.3 times higher than the mechanical mixing sample with the same composition. The quantum efficiency of the PSGM/rGO/CdS-3 sample was 3.99% at 420nm. Graphene served as electron acceptor and hydrogen evolution sites to promote the separation of the photo-induced charge carriers. Quantum size effect was observed from ultraviolet–visible diffuse reflectance spectroscopy and PL measurements. The presence of quantum size effect widened the bandgap of the catalyst and enhanced the photocatalytic hydrogen production rate. The stability of the composite catalyst was tested and demonstrated that this graphene-based composite catalyst was a stable and potential catalyst for photocatalytic hydrogen production.

Confidence intervals for probability density functions under strong mixing samples

It is shown that the empirical likelihood (EL) ratio statistic for a probability density function (p.d.f.) is asymptotically -type distributed under a strong mixing sample, which is used to obtain an EL-based confidence interval (CI) for the p.d.f. Results of a simulation study on the finite sample performance of the CI are reported.

The activity-integrated method for quality assessment of reduning injection by on-line DPPH-CE-DAD.

A sensitive on-line DPPH-CE-DAD method was developed and validated for both screening and determining the concentration of seven antioxidants of Reduning injection. The pH and concentrations of buffer solution, SDS, β-CD and organic modifier were studied for the detection of DPPH and seven antioxidants. By on-line mixing DPPH and sample solution, a DPPH-CE method for testing the antioxidant activity of the complex matrix was successfully established and used to screen the antioxidant components of Reduning injection. Then, antioxidant components including caffeic acid, isochlorogenic acid A, isochlorogenic acid B, isochlorogenic acid C, chlorogenic acid, neochlorogenic acid and cryptochlorogenic acid were quantified by the newly established CE–DAD method. Finally, the total antioxidant activity and the multiple active components were selected as markers to evaluate the quality of Reduning injection. The results demonstrated that the on-line DPPH-CE-DAD method was reagent-saving, rapid and feasible for on-line simultaneous determination of total pharmacological activity and contents of multi-components samples. It was also a powerful method for evaluating the quality control and mechanism of action of TCM injection.