Process Flow Research Articles

Continuous flow versatile conversion of furfural to valuable end products catalyzed by commercial Pd/C

The conversion of furfural has gained significant attention in recent years due to its potential for transforming this basic chemical into a wide range of valuable end products, such as alcohols, amines, acids, and biopolymers. This contribution aims to demonstrate the versatility and potential of continuous flow processes combined with commercial Pd/C catalysts for converting furfural into high value-added chemicals, including furfuryl alcohol, tetrahydrofurfuryl alcohol, and furfurylimine. By optimizing reaction conditions, high product yields (60–90%) were achieved, marking the first literature example of continuous flow conversion of furfural into diverse products, such as alcohols and imines. This work advances the production of high-value products using propanol as a hydrogen donor, with high yields and selectivity, employing commercial catalysts in a scalable continuous process.

Research on Intelligent Digital Manufacturing Platform Based on Artificial Intelligence Deep Neural Network

In today’s information age, intelligent manufacturing has become a significant trend of future industrial development. The neural network plays a vital role as the basis of smart manufacturing. This is a kind of intelligent algorithm that can simulate human brain organization, with strong learning ability and computing power, and has achieved remarkable results in the application field; the most typical representative is deep neural network, especially in recent years, an artificial intelligence developed based on deep neural network has entered the application stage, providing a new idea and model for industrial production. Based on this, taking the clothing production process as an example, this paper combined transfer learning and network fine-tuning technology to build a Faster RCNN model based on the ResNet-101 network to realize the positioning and recognition of clothing style map features and create an intelligent generation platform for clothing process flow on this basis.

Streamlining process development and scale-up: Risk assessment to reduce workload in primary protein recovery

Risk assessment is an integral aspect of the Quality-by-Design strategy to identify potential obstacles at every stage of biopharmaceutical production, from process development to tech transfer. We explored flow process chart, root cause analysis, and failure mode and effects analysis, to assess the scale-up of bacterial cell disruption and its influence on centrifugation and filtration steps. The Ishikawa diagram suggests that data on the impact of homogenizer valve design on product release, impurity profile, particle size distribution, viscosity, and dsDNA fragment size are missing which were collected experimentally for this study. Cell lysates from micro-, lab- and pilot scales cell disruption were analyzed for the above-mentioned parameters. Process parameters affecting these output parameters were identified on each individual scale. Cell disruption on the micro scale was performed in a bead mill. High pressure homogenization was used on lab- and pilot scales. Cell disintegration by bead milling delivers homogenates of product and impurity content comparable to those on bench scale but with 3-fold higher viscosity and significantly larger dsDNA fragments, 8.0 instead of 1.0 kbp, respectively. Miniaturized pressure flow curves identified dsDNA fragment sizes as critical for filter performance during clarification. Combining risk assessment, micro scale cell disintegration and bench scale pressure flow curves allows for selective and efficient process development, and scale up for primary recovery steps.

Groundwater contamination forecast using numerical modeling (on example of Qibray site of Chirchiq watershed)

The article presents a forecast of groundwater pollution on the example of the Kibray site of the Chirchik field. Models were developed to predict the entry of pollution into groundwater and to identify flow and transport processes. With the help of these models, the relationship between the quality of groundwater and surface water was established and it was revealed that the formation of operational reserves of the Chirchik field occurs due to artificial resources and attracted resources (surface water from the Chirchik riverbed).

On-orbit spectral characteristics analysis of the greenhouse gases monitoring instrument: Spectral wavelength stability and instrumental line shape stability

The Greenhouse Gases Monitoring Instrument (GMI) is a carbon satellite payload developed based on the principle of spatial heterodyne spectroscopy technology, which is specifically designed for the global analysis of greenhouse gases (CO2 and CH4) “sources” and “sinks”. Due to the low concentration and minimal gradient variations of CO2 and CH4 in the atmosphere, higher precision is required for their retrieval. Vibrations during satellite launch and harsh space environments during on-orbit operation may cause changes in the performance of various payload components, resulting in decreased quality of spectrum products and retrieval precision. This paper proposes a set of on-orbit spectral characteristic evaluation methods tailored for the GMI to monitor the quality of its spectrum. It also develops an adaptive blind pixel detection and correction algorithm specifically for the GMI and optimizes the interferogram processing flow algorithm. On-orbit spectral calibration is performed, and methods to evaluate spectral characteristic parameters have been established. The analysis focuses on the variations of the spectral characteristics in the CO2-1 bands (1.575 μm) of the GMI during one-year of on-orbit calibration spectrum. The initial spectral wavenumber offset is 0.133 cm−1 after entering orbit, and the average spectral wavenumber offset is 0.0313 cm−1 during stable operation. During the one-year period, the maximum variation in the instrumental line shape function of the GMI is 0.006 cm−1. The observed spectrum obtained in nadir observation mode, underwent to accuracy verification. The results demonstrate consistency between the spectral peak wavenumbers and the relative trend changes of the observed and theoretical spectrum, with an average relative residual of 0.987%.

Automated Optimization of a Multistep, Multiphase Continuous Flow Process for Pharmaceutical Synthesis.

Flow synthesis is becoming increasingly relevant as a sustainable and safe alternative to traditional batch processes, as reaction conditions that are not usually achievable in batch chemistry can be exploited (for example, higher temperatures and pressures). Telescoped continuous reactions have the potential to reduce waste by decreasing the number of separate unit operations (e.g., crystallization, filtration, washing, and drying), increase safety due to limiting operator interaction with potentially harmful materials that can be reacted in subsequent steps, minimize supply chain disruption, and reduce the need to store large inventories of intermediates as they can be synthesized on demand. Optimization of these flow processes leads to further efficiency when exploring new reactions, as with a higher yield comes higher purity, reduced waste, and a greener synthesis. This project explored a two-step process consisting of a three-phase heterogeneously catalyzed hydrogenation followed by a homogeneous amidation reaction. The steps were optimized individually and as a multistep telescoped process for yield using remote automated control via a Bayesian optimization algorithm and HPLC analysis to assess the performance of a reaction for a given set of experimental conditions. 2-MeTHF was selected as a green solvent throughout the process, and the heterogeneous step provided good atom economy due to the use of pure hydrogen gas as a reagent. This research highlights the benefits of using multistage automated optimization in the development of pharmaceutical syntheses. The combination of telescoping and optimization with automation allows for swift investigation of synthetic processes in a minimum number of experiments, leading to a reduction in the number of experiments performed and a large reduction in process mass intensity values.

Composite dyadic models for spatio-temporal data.

Mechanistic statistical models are commonly used to study the flow of biological processes. For example, in landscape genetics, the aim is to infer spatial mechanisms that govern gene flow in populations. Existing statistical approaches in landscape genetics do not account for temporal dependence in the data and may be computationally prohibitive. We infer mechanisms with a Bayesian hierarchical dyadic model that scales well with large data sets and that accounts for spatial and temporal dependence. We construct a fully connected network comprising spatio-temporal data for the dyadic model and use normalized composite likelihoods to account for the dependence structure in space and time. We develop a dyadic model to account for physical mechanisms commonly found in physical-statistical models and apply our methods to ancient human DNA data to infer the mechanisms that affected human movement in Bronze Age Europe.

Analysis and study of transient characteristics of hydrogen circulation pump under different stopping modes

The internal flow field of the hydrogen circulation pump becomes more complex and flow process becomes more intense during the stopping process, strong vibration is generated to the pump and the working life of the pump is shortened. Therefore, the pressure pulsation at the inlet and outlet section, the radial force characteristics of the active rotor and the transient flow mechanism of the internal flow under different stopping modes are studied in this paper. The results show that the intake pressure and exhaust flow change greatly in exponential stopping mode, while the pressure pulsation amplitude decreases with the increase of stopping time in linear stopping mode. In addition, the radial force value of the active rotor in the exponential stopping mode is significantly smaller than that in the linear stopping mode, and the direction of the radial force Fx and Fy point to the negative direction of their respective axes.

Numerical study of multi-phase flow in ultrashort pulse laser processing

Ultrashort pulse laser processing is highly valued due to its enormous potential for high micromachining quality while it comprises complicated physical mechanisms especially when the pulse width falls in the regime about 10 ps. This study presents a complete mathematical modeling on multi-phase phenomena in ultrashort pulse laser processing, such as melting, vaporization, and solidification. The volume of fluid (VOF) technique is used to capture the interface during phase transition. Based on this hybrid model, the transport of energy and mass are investigated to study the influence of laser parameters on the formation of laser ablation hole. This work develops the incompressible multiphase laser ablation solver based on PIMPLE algorithm. The calculation results are validated by different references under different laser processing parameters which emphasize the importance of mechanism on thermal ablation and hydrodynamics in picosecond laser processing. More calculation results about the trends in hole depth over pulse laser width, laser fluence, and the number of pulses show the intricate influence of laser parameters.

Coupled Modeling of Sea Surface Launch Flow and Multi-Body Motion

To simulate the launching process of missile complex flow, movement, and constraint states, a multifield coupling model is put forward based on a computational fluid dynamics (CFD) method. In this coupled model, a CFD method is used to solve the three-dimensional compressible transient flow, and the six-degree motion of the launching platform is considered, and the virtual contact method is used to deal with the constraint states of the guideway and the slider. The active force and moment are applied to the launching platform to simulate its rolling, pitching, and heaving motions under the 5-level waves. Collision detection is carried out through the minimum clearance distance between the slider and the guideway, and the contact force is handled by a modified Herz collision model. In the problem of launching a missile from the water surface, the change characteristics of the flow field, the load response characteristics, and the relative motion laws of the missile and the launching platform during the catapulting process are investigated. The results show that the motion laws of the projectile and the launch tube in the constrained direction are the same, and the established coupling model is able to simulate the launch separation process of the missile in the constrained state. In addition, the effect of wind load on the missile ejection process is analyzed using the coupled model.

Novel Correlations for flow and heat transfer processes in S-CO2 Brayton cycle with different roughness by experimental and simulation methods

This study comprehensively examines heat transfer performance of supercritical carbon dioxide (S-CO2) in horizontal tubes under actual operating conditions of precooler, regenerator and heater, with a focus on the impact of tube roughness. By employing both experimental and numerical methods, it aims to bridge the gap in current research regarding S-CO2 heat exchanger performance that incorporates the effect of roughness. The results indicate that roughness height can suppress the influence of buoyancy effects. As roughness height increases from 1.5 μm to 100 μm, average temperature difference of heater at an outlet temperature of 1000 K decreases from 134.9 K to 61.1 K. Although roughness height can significantly enhance heat transfer, yet the rate of this enhancement diminishes when the roughness height surpasses 50 μm. To address the need for accurate heat transfer and flow correlations considering roughness, high-precision correlations are proposed and validated. The correlations of precooler, regenerator and heater exhibit average absolute deviations of within 8 %, 10 % and 12 %, respectively. The proposed correlations not only enrich theoretical framework of related fields but also provide a solid foundation for optimizing the design and operation of S-CO2 Brayton cycle, enabling more efficient energy conversion and reduced carbon emissions.

A 1000FPS@360,000pixels mixed-signal sensing with computing macro featuring analog compression and maximum parallelism for objective detection tasks

Ubiquitous vision sensors continuously collect data from the environment, imposing a significant processing burden. Especially, high-frame-rate convolution processing for large-scale pixel arrays presents substantial challenges. This paper proposes a mixed-signal sensing with computing macro featuring analog compression and maximum parallelism for high-frame-rate object detection tasks. A customized neural network (NN) architecture is designed specifically for object detection. Key circuitry modules, including signal readout, dark current offset, normalization, first-layer convolution, and pooling, are implemented in the analog domain, leading to high-quality information extraction and substantial data compression. Maximum parallelism in the first-layer convolution is realized in our proposed processing flow, ensuring high-frame-rate convolution for large-scale pixel arrays. Additionally, the subsequent NN layers are efficiently deployed on SRAM-based in-memory digital computing. The macro was designed using a 55-nm foundry process. Results show that our macro can achieve 1000 fps@360,000 pixels with a 63.8 TOPS throughput under 4/8-bit hybrid precision, outperforming the state-of-the-art in frame rate by 2–10 times.

Plasmonic image reproduction with solid-state superionic stamping (S4)

Traditional top-down approaches for producing metallic nanostructures, despite being capable of producing arbitrary 2-D shapes, often use vacuum-based deep sub-micron lithographic fabrication technologies. This makes their use for single-use devices like chemical and bio-sensing substrates difficult to economically justify. Here, the authors demonstrate a manufacturing pathway that only uses such techniques to produce a master. This reusable master, coupled with a unique and facile electrochemical imprinting process, Solid-State Superionic Stamping (S4), is used to produce several replicated metallic nanostructures, thus demonstrating an economically feasible manufacturing pathway for single-use, nano-enabled devices.This paper uses plasmonic image reproduction as an easy-to-visualize proxy for single-use devices such as plasmonic sensors and Surface Enhanced Raman Spectroscopy (SERS) substrates that require nanopatterned metallic structures. It demonstrates a process for replicating a picture by a set of metallic structures that plasmonically produce the desired colors locally. It uses a digitizing computational tool, direct-write Two-Photon Lithography (TPL) and a dry-etch process to rapidly produce a silicon master. This master is used to hot emboss nano-patterns in superionic glass blanks that, in turn, are used for electrochemical imprinting with S4 to reproduce the patterns on Ag substrates. The different steps in this process flow are described along with their role and effectiveness in contributing to a high-fidelity plasmonic image reproduction.

Slot coating of time-dependent structured materials: Effects of thixotropy on the flow dynamics and operating limits

Some of the most common liquid-like formulations rooted in the coating industry consist of rheologically complex structured materials such as inks, paints, and slurries. Yet, the impact of time-dependent structuring effects due to thixotropy on thin film coating applications remains elusive and still unclear. Here, we present a computational study of the effects of thixotropy on slot coating of time-dependent structured materials. By coupling a recent fluidity-based constitutive model for thixotropic materials with a well-established finite element/elliptic mesh generation method for free surface flows, we assess the role of thixotropy by comparing the predictions from the thixotropic model with those from a simple Generalized Newtonian Fluid model that uses the same flow curve for the material steady-state equilibrium viscosity. We find that thixotropy can indeed have a major impact on slot coating applications, potentially bringing strong implications not only to the flow dynamics but also to the operating limits of the process. In conclusion, the results and discussions we present in this study underscore the importance of accounting for thixotropy to genuinely model and fundamentally understand the behavior of time-dependent structured materials with complex rheology in processing flows like those ubiquitous across the broad fields of coating science and engineering.

Mechanism and kinetics of efficient removal of as from a high arsenic-bearing ZnSO4 solution using ultrasound enhanced oxygen

The traditional lime method for arsenic (As) removal from high arsenic-bearing ZnSO4 solution has disadvantages such as high cost, large amount of wet residue, significant secondary hazards, and long process flow. This study developed a new technology for efficient As removal using ultrasound enhanced oxygen. The effects of zinc roasting dust (ZRD) addition, reaction temperature, oxygen flow rate, and ultrasound power on As removal efficiency were investigated. Under the optimal conditions, the removal rate of As reached 97.90 %. The1O2, O2∙- and •OH radicals generated during the ultrasound-enhanced oxygen process significantly enhance the oxidation efficiency of As(III) and Fe2+. Ultrasound can also refine particle size and improve the removal efficiency of As. Compared with traditional lime method, the reaction time and wet residue amount have been reduced by 40 % and 70.37 %, respectively. Field emission scanning electron microscopy (FE-SEM-EDS), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) analyses indicate that As in ZnSO4 solution was primarily removed through by Fe(OH)3 colloidal adsorption and amorphous FeAsO4. Kinetic analysis revealed that the neutralization and As removal process using ZRD under ultrasound and oxygen action conforms to the internal diffusion control model. Ultrasound-enhanced oxygen As removal can reduce the reaction activation energy from 26.94 to 21.02 kJ/mol, effectively lowering the reaction barrier for As removal and demonstrating faster reaction rates under ultrasound conditions. Ultrasound-enhanced oxygen removal of As from high arsenic-bearing ZnSO4 solution provides an efficient and low-cost potential solution for enterprises.

Numerical simulation of the effects of pulsed injection on combustion and flow processes in a supersonic combustor

This paper describes two-dimensional numerical simulations of pulsed injection to a hydrogen-fueled air-breathing ramjet using the Reynolds-averaged Navier–Stokes method. We analyze the effects of sinusoidal pulsed injection on the start-up ignition time, start-up ignition range, combustion efficiency, and flow field evolution of the ramjet and compare the performance with that of steady injection. The results show that pulsed injection shortens the ignition time and optimizes the ignition equivalence ratio of hydrogen. Pulsed injection also improves the combustion efficiency of hydrogen, increasing the thrust of the engine by 7.79% compared with steady injection under the same equivalence ratio. We find that pulsed injection can cause oscillations in the ramjet combustion flow field, and show that the oscillation frequency is affected by the pulsed injection frequency.

A conceptual framework for the successful implementation of rapid improvement events

Rapid Improvement Events (RIE) are the most common application of Lean principles and practices in the Higher Education (HE) environment to remove waste and improve the flow of university processes. But not all RIE are successful. The literature was reviewed to identify how the steps taken before, during, and after the execution of an RIE may influence its outcomes. Findings highlight several potential errors that may contribute to the failed implementation of RIE and broader concerns about the applicability of Lean in HE.

On Theoretical Aspect of Photons Emission From Quark-Gluon Interaction Upon Hard Collision

Abstract This work applies a quantum chromodynamics theory QCD to photon emission from heavy quark-gluon scattering in the strong interaction quark-gluon to study and calculate photon flow in hard interaction processes. The photon flow from the dense quark-gluon interaction was calculated using critical temperature, quantum chromodynamic coupling and fugacity at chemical potential μq (500 MeV) for the anti-top with gluon interaction in t ¯ g → s ¯ γ system. The photon flow spectrum in hard collisions is described under the first leading order approximation for QCD theory at finite chemical potential and critical temperature using various photon energy values dependent on the fugacity of quark and gluon. Photon flux calculation provided valuable insights into QGP conditions. The coupling strength αc (T) calculation is a strongly decreasing function of critical temperature ranging 107MeV ≤ Tc ≤ 145MeV and also find appreciable increasing as a result of increasing temperature of system ranging 180MeV ≤ T ≤ 360MeV. The photon flow produced in the t ¯ g → s ¯ γ system was observed in the low range of photon energy with two critical temperatures. The total photon emission strongly decreases marginally as a function of the increase in photon energy. The photon flow emission was found to have appreciable enhancement at the anti-top quark interaction with gluon and it increases highly as a result of the increased temperature of the system and reaches to maximum near 360 MeV at minimum strength coupling in the energy of the photon 1GeV≤E≤2 GeV.

Experiment study on vortex evolution process and vorticity distribution in wave boundary layer flow over a rippled bed

Experiment study on vortex evolution process and vorticity distribution in wave boundary layer flow over a rippled bed

Vector-Time-Resolved In-plume Plasma Current Density Flux Measurement in a Pulsed Plasma Thruster

Plasma plumes are the end products ejected from electric propulsion after complex ionization and acceleration processes. The physics behind the plasma plumes has attracted significant interest due to their interactions with the critical components of satellites and an increased understanding of the relevant processes. Recently, in the front view from a pulsed plasma thruster (PPT), we observed an unclosed vortex structure in the plasma plume, which led us to reconsider the propagation process and the current flux directions inside a plasma plume. To study this plume structure in depth, a highly sensitive Rogowski coil is used here to obtain the current density of the plume over the operating period of a PPT in 3 perpendicular directions. Vector-time-resolved current flux maps were obtained through experimental measurements and the peak current densities were found to reach 50000 mA/cm2 to 250000 mA/cm2. From successive 3-D current flux maps, the complete process of current flow inside a transient plasma plume is observed. The vortex plume structure was found to form during the initial discharge period. The plasma in-plume current is shown to be involved by discharge circuit. After the main discharge is completed, the plasma plume tends to circuit-independent and in self-equilibrium.