Optimizing the separation characteristics of the waterinjection hydrocyclone using mathematical modelling

Purpose. Although the hydrocyclone separator has many advantages, it still has some limitations which decrease its separation efficiency in many mineral processing applications because of fine particles which are miss separated to the coarse product in the underflow. Water injection in the conical part of the cyclone was recently implemented to solve this problem. The water injection mechanism and the way in which the injected water affects the separation are still not clear and need to be more investigated. Methods. New design of water injection hydrocyclone was tried using a modified conical part with a water injection range consist of five equal distance injection openings open directly on the periphery of the cone part. Findings. This study presents a mechanical mathematical model that simulates the water injection to give a clear indication of the injection mechanism impact on the classification process. It could also predict the dependence of the basic characteristics of the classification on the amount of the injected water and the influence of different operating and design parameters of the hydrocyclone. Originality. The model accounts for the fluid flow, the particle motion, the turbulent particle diffusion, and particle settling. Particle interactions and fine particle entrainment by settling coarse particles are also included in the model. The model was found to predict well the injection effect and agrees with the experimental results. Practical implications. The results showed also that the increase in water injection velocity leads to an increase in both the cut size and the minimal value of the separation curve. It was found also that the hydrocyclone length has an important effect on the injection process, and the separation sharpness is directly proportional to it at higher values of water injection velocity.

Characterization of Electrical Parameters of Copper Phthalocyanine Based Organic Electronic Device in Presence of Fullerene Nanoparticles

Characterization of electrical parameters of Copper Phthalocyanine dye has been done in the present work. In the context of electrical parameters, the Schottky barrier and ideality factor of the organic device has been measured and the effects of fullerene nanoparticles on these parameters have been studied. Analysis of electrical parameters has been done by the current-voltage characteristics of the device. The influence of fullerene nanoparticles lessens the Schottky barrier to 0.71 eV from 0.75 eV. The current flow is assumed to be injection limited as the Schottky barrier is greater than 0.3 eV - 0.4 eV. The Schottky barrier is also estimated by the Norde method. Norde's method shows lessening of barrier height from 0.70 eV to 0.65 eV under the influence of fullerene nanoparticles. The measured ideality factor value reduces from 3.787 to 1.495 in presence of fullerene nanoparticles. The charge injection mechanism at metal-organic contact gets influenced by the interfacial Schottky barrier height. Decrease in both Schottky barrier and ideality factor attribute to the increase in charge flow and it allows a reduction in the device’s transition voltage from 2.5 V to 1.0 V.

A New Current-Shaping Technique Based on a Feedback Injection Mechanism to Reduce VCO Phase Noise

Inductor-capacitor voltage controlled oscillators (LC-VCOs) are the most common type of oscillator used in sensors systems, such as transceivers for wireless sensor networks (WSNs), VCO-based reading circuits, VCO-based radar sensors, etc. This work presents a technique to reduce the LC-VCOs phase noise using a new current-shaping method based on a feedback injection mechanism with only two additional transistors. This technique consists of keeping the negative resistance seen from LC tank constant throughout the oscillation cycle, achieving a significant phase noise reduction with a very low area increase. To test this method an LC-VCO was designed, fabricated and measured on a wafer using 90 nm CMOS technology with 1.2 V supply voltage. The oscillator outputs were buffered using source followers to provide additional isolation from load variations and to boost the output power. The tank was tuned to 1.8 GHz, comprising two 1.15 nH with 1.5 turns inductors with a quality factor (Q) of 14, a 3.27 pF metal-oxide-metal capacitor, and two varactors. The measured phase noise was −112 dBc/Hz at 1 MHz offset. Including the pads, the chip area is 750 × 850 μm2.

Reconfigurable Quantum Photonic Convolutional Neural Network Layer Utilizing Reconfigurable Photonic Gate and Teleportation Mechanism

This article, proposes a reconfigurable quantum photonic convolutional layer (QPCL) based on the reconfigurable photonic gates. The QPCL is used in the classical photonic CNN, where, an array of reconfigurable photonic gates (RPG) are arranged in a systematic way. The designed reconfigurable photonic gate serves as a unit cell for quantum photonic operations such as beam splitting, rotation, displacement, squeezing, and cubic- phase shifting. The designed RPG provides the features namely broadband operation, low insertion loss and compact layout. The entangled states are created based on the normalized pixel value of the input image. The configuration of reconfigurable photonic gate is accomplished using electro-optic P-i-N carrier injection mechanism. As compared to Mach-Zehnder interferometer (MZI) based realization, the proposed silicon reconfigurable photonic gate provides scalable operation and compact footprint. The reconfigurable photonic gate is modeled using 2D finite element beam propagation method (FEBPM). Finally, a compact numerical model is developed which performs Gaussian based continuous-variable (CV) quantum photonic operations and are verified with Xanadu’s strawberryfields quantum photonic simulator and PennyLane deep learning framework. The optimized accuracy (loss) is obtained with the utilization of QPCL layer and the values are 0.7627 (0.9595), this optimum result is obtained using a single QPCL layer with an epoch number of 30. Finally, a comparative analysis is made between quantum CNN and classical photonic CNN, where the quantum CNN resulted in 6.553% high accuracy and 6.988% low loss compared to the classical photonic CNN.

Potential of Bagasse as Raw Material for Lignosulfonate Surfactant

Anionic surfactants are generally used in surfactant injections because they are good, resistant in storage and stable. Furthermore, Commercially, anions are produced in the form of carboxylates, sulfates, sulfonates, phosphates, or phosphonates. The surfactants used in the process of implementing Enhanced Oil Recovery (EOR) are generally petroleum-based, such as Petroleum Sulfonate. Therefore, an increase in oil price, leads to an increase in the price of surfactant and the operational costs becomes relatively expensive. Lignosulfonate is a type of anionic surfactant which is made with lignin as raw material. This lignin is found in many plants, including wood stalks, plant leaves, peanut shells, corn cobs, bagasse, empty bunches of oil palm and wheat straw. Based on the results of previous studies, 25% of lignin component was discovered in bagasse. This may be a consideration that there is enough lignin in bagasse to be used as raw material in the production of lignosulfonate vegetable surfactants. Furthermore, lignin from bagasse is used because bagasse is easy to obtain, cheap and an environmental friendly vegetable waste. Currently, bagasse is only used as fuel in steam boilers and papermaking, cement and brick reinforcement, a source of animal feed, bioethanol, activated charcoal as adsorbent and compost fertilizer. This is a consideration to optimize the use of bagasse to become lignosulfonate as an alternative for surfactants in the petroleum sector. The purpose of this study is to show that lignin from bagasse has the potential of becoming a lignosulfonate surfactant. There are several studies that have processed bagasse into sodium lignosulfonate. The component test on the results showed that the surfactant component of sodium lignosulfonate from bagasse was almost the same as the commercial standard lignosulfonate component. Furthermore, the results of the HLB (Hydrophilic–Lipophilic Balance) value test show that the sodium lignosulfonate surfactant from bagasse can function as an emulsion form which is a required parameter for the surfactant injection mechanism. Based on the discussion of the study results, bagasse has the potential as a raw material to be processed into lignosulfonates.

Design, Fabrication, and Characterization of Thermal and Optical Properties of Nano-Composite Self-Cleaning Smart Window

Polymer-based smart windows have recently received attention due to their capabilities in energy consumption reduction. A smart window provides desired optical properties when heated/cooled by using solar energy when the ambient temperature requires regulation. The main issue here is the design and fabrication of such a smart element which is the main axis of the current research. The window in the proposed design operates in such a way that the percentage of light transmission depends on the presence of nanofluid between the two walls and refractive index conformity between the fluid and the polymeric walls; Therefore the percentage of light transmission will be at its minimum value (45%) in the absence of fluid and it will be at the maximum value (80%) at the presence of fluid. The fundamental steps of the present design includes design, fabrication, and characterization of the materials. In this regard experiments to determine the mechanical, physical, structural, optical, and thermal properties of components have been performed after considering, designing, and manufacturing various samples. The results show that the proposed smart offers acceptable performance with a fast switching rate and even more than other similar smart glasses due to the usage of discharge/injection mechanism. In overall, the product can be used as a smart transparent element in various structures such as buildings and even vehicles to regulate energy consumption and/or block the view for security purposes.

Disparity of time-contrast curves generated by various types of power injectors used in magnetic resonance imaging

The profiles of time-contrast (TC) -curves from popular MRI injectors derived at the injection site of the attached tube-line system were compared. Variations of TC-profiles were previously reported to potentially influence image quality in time critical MRI measurements. TC-curves from five injectors obtained during commonly used injection protocols were assessed according to representative quality criteria: (1) correlation strength between a fitted boxcar function and the TC-curve (cBCF) and (2) difference between true and expected injection time (dBIT). Additionally, the impact from technical injector properties: pump type, line volume, maximum injection power and type of contrast medium (CM) on the TC-profiles was evaluated. Injectors using a piston-syrinx (PS) mechanism for CM-injection performed significantly better than those working with a peristaltic roller pump (RP) technique. Besides injection mechanism, line filling volume showed a strong influence on the final TC-curves, where larger filling volumes induced worse cBCF- and dBIT-results. Therefore, to achieve an optimal bolus in clinical MRI use of a PS-injector seems recommendable. Besides their pump mechanism, RP-injectors appeared additionally hampered by their high volume line systems, pointing out an unfavourable coinicidence of these technical features in RP-injectors. This should be considered, particularly, in comparative or time-critical MRI-studies.