Scale-up Method Research Articles

Synthesis of Laboratory Nylon: A Scale-Up Method for High Molecular Weight Polyamides

Synthesis of Laboratory Nylon: A Scale-Up Method for High Molecular Weight Polyamides

Performance Analysis of NSUM Estimators in Social-Network Topologies

The Network Scale-up Methods (NSUM) are methods to estimate unknown populations based on indirect surveys in which the participants provide information about aggregated data of their acquaintances. This preserves the privacy and may lead to higher participation. During the last thirty years, new NSUM estimators have emerged. However, conditions related to the design of the experiments and the robustness of the estimators have not been studied in depth, especially in a realistic simulation environment. This study aims to compare nine NSUM estimators under relevant conditions in the literature through simulation experiments. We have analyzed how the NSUM is affected by the network topology, transmission and recall errors, the distribution of the unknown subpopulation, the number and sizes of subpopulations, and sample size. This article shows that some NSUM estimators barely used are better and more robust to some conditions, especially when the network is scale-free or under barrier effects. In addition, some methods are very sensitive to recall errors. In terms of the subpopulations configuration, we observe that the number of known subpopulations usually employed is quite large and that the most common NSUM is robust to the number and sizes of the subpopulations.

A Review of Recent Developments in Hybrid Rocket Propulsion and Its Applications

This paper extensively reviews hybrid rocket propulsion-related activities from combustion engine designs to launch tests. Starting with a brief review of rocket propulsion development history, a comparison among the three bi-propellant rocket propulsion approaches, and hybrid rocket engine design guidelines, a very thorough review related to hybrid rocket propulsion and its applications is presented in this paper. In addition to propellant choice, engine design also affects the hybrid rocket performance and, therefore, a variety of engine designs, considering, e.g., fuel geometry, swirl injection, ignition designs, and some innovative flow-channel designs are also explored. Furthermore, many fundamental studies on increasing hybrid rocket engine performances, such as regression rate enhancement, mixing enhancement, and combustion optimization, are also reviewed. Many problems that will be encountered for practical applications are also reviewed and discussed, including the O/F ratio shift, low-frequency instability, and scale-up methods. For hybrid rocket engine applications in the future, advanced capabilities and lightweight design of the hybrid rocket engine, such as throttling capability, thrust vectoring control concept, insulation materials, 3D-printing manufacturing technologies, and flight demonstrations, are also included. Finally, some active hybrid rocket research teams and their plans for flight activities are briefly introduced.

Automated Name Selection for the Network Scale-up Method

To estimate the distribution of the number of acquaintances of the members of a society, the network scale-up method asks survey respondents about the number of people they know with features for which national statistics are available. While many features have been used for this purpose, first names have been suggested to produce particularly low levels of transmission error and recall bias. For this method to be precise, a set of names needs to be selected for the survey that jointly represents the population in relevant variables such as gender or age. This article provides a solution approach to finding the optimal set of names. This can be applied to any population for which a joint distribution of first names and relevant variables is available. We show that our approach successfully provides sets of names closely mirroring the population distributions for six countries with different name statistics.

Scale-up prediction of the head loss of a high concentration, non-Newtonian particulate slurry

The design of a mineral slurry transportation system is difficult because of the non-Newtonian nature of the flow at high slurry concentrations. The behavior of the slurry depends on many physio-chemical properties such as particle density, particle size distribution (PSD), particle shape, chemical composition, pH etc. This work presents a comparative study between three preferred methods of scale-up of the head loss in larger diameter pipelines, namely Bowen’s Method, rheological method and Wilson’s Method. The performance of each method is validated with the pipe loop test data in a 200 DN pipeline. A high concentration (>50% by weight) iron ore concentrate slurry was used for carrying out the above study. This work would be beneficial for engineers involved in the design and maintenance of the slurry pipelines with respect to the choice of the scale-up methods available for estimation of the head loss for a time independent, homogenous, non-Newtonian particulate slurry for both laminar and turbulent regime.

Lessons learnt from daily oral PrEP delivery to inform national planning for PrEP ring introduction for women in low-income and middle-income countries: a qualitative inquiry of international stakeholders

IntroductionSome African countries plan to introduce and scale-up new long-acting pre-exposure prophylaxis methods (LA-PrEP), like the monthly dapivirine vaginal ring (PrEP ring) and injectable cabotegravir. National costed implementation plans, roadmaps...

Comparing the Robustness of Simple Network Scale-Up Method Estimators.

The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents’ degrees and estimating the prevalence of the hard-to-reach population of interest using respondents’ estimated degrees and the number of people they report knowing in the hard-to-reach group. Each of these two steps involves taking either an average of ratios or a ratio of averages. Using the ratio of averages for each step has so far been the most common approach. However, the authors present theoretical arguments that using the average of ratios at the second, prevalence-estimation step often has lower mean squared error when the random mixing assumption is violated, which seems likely in practice; this estimator was proposed early in NSUM development but has largely been unexplored and unused. Simulation results using an example network data set also support these findings. On the basis of this theoretical and empirical evidence, the authors suggest that future surveys that use a simple estimator may want to use this mixed estimator, and estimation methods based on this estimator may produce new improvements.

Size estimation of key populations and ‘bridge populations’ based on the network scale-up method in Ukraine

IntroductionCorrect estimation of the size of key and bridge populations is crucial for an efficient HIV/AIDS response in resource-limited settings, enabling efficient program planning and resource allocation. The hidden nature of these groups poses challenges to traditional methods, leading to the adoption of innovative approaches like the network scale-up method (NSUM). In this article we present the results of a NSUM study conducted in 2020 in Ukraine, focusing on four key populations and three bridge populations, highlighting challenges and contributions to development of the method.MethodsFrom July to September 2020, we conducted a nationally representative survey in Ukraine via computer-assisted telephone interviews, and applied the known population method and summation method to estimate social networks sizes. Results were weighted based on individual sampling probability and adjusted for social respect and visibility factors to address potential limitations.ResultsOur study achieved a 20% response rate with 10,000 completed interviews. The social network size, using the known population method, was 213 people, and 125 using the summation method. Adjusting for the social respect and visibility, estimated key populations sizes were 295,857 [248,714–343,001] people who inject drugs, 152,267 [109,960–194,573] men who have sex with men, 78,385 [57,146–99,619] sex workers, and 9,963 [7,352–12,571] transgender people, detailed by age and gender. Bridge populations were estimated at 62,162 [50,445–73,879] sexual partners of people who inject drugs, 284,348 [233,113–335,583] clients of sex workers, and 13,697 [7,370–20,026] female partners of men who have sex with men.ConclusionsNSUM proves reliable for estimating key populations size with appropriate corrections. It shows promise for further use in Ukraine, considering limited geographic coverage of the integrated bio-behavioral studies to use multiplier-based methods. However, the validity concerns persist for estimating bridge populations size, emphasizing the need for further method refinement and addressing implementation issues, particularly those related to data collection.

Scale-up of dry impregnation processes for porous spherical catalyst particles in a rotating drum: experiments and simulations

Catalyst impregnation is the first step and one of the most crucial steps for preparing industrial catalysts. The process is typically performed in rotating vessels with a spray-nozzle to distribute the liquid onto porous catalyst supports until the pore volume is reached. The inter-particle variability of the impregnated liquid inside the particles significantly affects the activity and selectivity of the resulting catalyst. Current scale-up practices lead to poor fluid distribution and inhomogeneity in the liquid content. The aim of this work is to understand the dynamic behavior of the particles under the spray nozzle, which is essential for desired content uniformity, and to develop a scale-up model for the dry impregnation process. In this work, we considered four dimensionless numbers in the scaling analysis. The scale-up rules require that the dimensionless numbers are kept constant for different scales. Both DEM simulations and matching experiments of dry impregnation inside the porous particles were performed for different vessel sizes. The water content of the particles was compared for different times and locations, and the relative standard deviation is calculated from the axial water content. Simulation and experimental results show that particles achieve similar content uniformity at the end of impregnation, confirming that the scale-up rules are applicable to all vessel sizes. The dimensionless numbers give very good scale-up performance since curves collapse indicating similarity in the processes. In addition, the scale-up method is validated for different particle sizes in simulations.Graphical abstract

Nowcasting Temporal Trends Using Indirect Surveys

Indirect surveys, in which respondents provide information about other people they know, have been proposed for estimating (nowcasting) the size of a hidden population where privacy is important or the hidden population is hard to reach. Examples include estimating casualties in an earthquake, conditions among female sex workers, and the prevalence of drug use and infectious diseases. The Network Scale-up Method (NSUM) is the classical approach to developing estimates from indirect surveys, but it was designed for one-shot surveys. Further, it requires certain assumptions and asking for or estimating the number of individuals in each respondent's network. In recent years, surveys have been increasingly deployed online and can collect data continuously (e.g., COVID-19 surveys on Facebook during much of the pandemic). Conventional NSUM can be applied to these scenarios by analyzing the data independently at each point in time, but this misses the opportunity of leveraging the temporal dimension. We propose to use the responses from indirect surveys collected over time and develop analytical tools (i) to prove that indirect surveys can provide better estimates for the trends of the hidden population over time, as compared to direct surveys and (ii) to identify appropriate temporal aggregations to improve the estimates. We demonstrate through extensive simulations that our approach outperforms traditional NSUM and direct surveying methods. We also empirically demonstrate the superiority of our approach on a real indirect survey dataset of COVID-19 cases.

Readily scalable and controllable micro-structured catalyst with encapsulated Pd@Silicate-1 towards sustainable catalytic emission control

Hierarchical micro-structured catalyst has been proved to be crucial for modular, compact reactor design towards sustainable catalytic processes, including catalytic emission control. However, turning it to reality is hindered by controllability and scalability in high-efficient, cost-effective preparation, particularly when combined with state-of-the-art encapsulated catalysts. Herein, in-situ hydrothermal coating method is developed to achieve tunable incorporation of Pd@S-1 catalyst into micro-structured confined space, and the trade-off between catalyst loading and confined micro-structures’ availability towards the best performance is revealed, e.g. 10 ∼ 50 °C lower T50 with balanced control. Moreover, systematic experiments and CFD simulations prove that (1) flow-through flow pattern, rather than flow-over, in confined space enables better catalyst utilization and performance (>10 °C lower T50), thus optimal micro-structure design is proposed; (3) a loosely bundled scale-up method is the best. This study provides deep insights into understanding and utilizing hierarchical structured catalysts, particularly with confined micro-structures.

Direct reduction of iron-ore with hydrogen in fluidized beds: A coarse-grained CFD-DEM-IBM study

Hydrogen metallurgy technology uses hydrogen as the reducing agent instead of carbon reduction, which is one of the important ways to reduce carbon dioxide emissions and ensure the green and sustainable development of iron and steel industry. Due to the advantages of high gas-solid contact efficiency and outstanding mass and heat transfer, direct reduction of iron ore in fluidized beds has attracted much attention. Based on the three-layer unreacted shrinking core model and considering the diversity of particle structure during the reaction process, a multi-reaction path (multi-resistance network) model was established. In this study, a coarse-grained CFD-DEM-IBM solver based on hybrid CPU–GPU computing is developed to simulate the direct reduction process of two kinds of iron ore with hydrogen in fluidized beds, where the developed unreacted shrinking core model is used to model the reduction reactions, a coarse-grained model and multiple GPUs enable the significant acceleration of particle computation, and the immersed boundary method (IBM) enables the use of simple mesh even in complex geometries of reactors. The predicted results of particle reduction degree are in good agreement with the experimental values, which proves the correctness of the CFD-DEM-IBM solver. In addition, the effects of reaction kinetic parameters and operating temperature on particle reduction degree are also investigated. Present study provides a method for digital design, optimization and scale-up of ironmaking reactors.

Efficient and Scalable Enantioselective Synthesis of a Key Intermediate for Rimegepant: An Oral CGRP Receptor Antagonist

Rimegepant is a calcitonin gene-related peptide antagonist used for acute treatment and prevention of migraine. We herein attempt to explore an efficient and practiced method for scale-up, regio- and enantioselective synthesis of (R)-9-hydroxy-6,7,8,9-tetrahydro-5H-cyclohepta[b]pyridin-5-one (1), a key intermediate of rimegepant. In this work, a Ru-catalyzed asymmetric transfer hydrogenation (ATH) reaction was a key step. The optimization of the reaction conditions involved exploring the reaction parameters including catalysts, bases, and solvents. The results suggested that the Ru-catalyzed ATH process using formic acid as the hydrogen donor could be operated under mild conditions at a low catalyst loading (0.5 mol%), affording a high yield (92.1% yield with 99.8% purity) and gratifying enantioselectivity (99.9% ee) of the target product (1). This work first reported the Ru-catalyzed ATH process in the synthesis of key intermediates of rimegepant. The optimized ATH process was easy to implement and cost-effective, making it particularly suitable for manufacturing scale production.

A high-efficient electrocatalyst for oxygen evolution and methanol oxidation reactions prepared by a facile and scale-up method

Developing the facile, universal and scale-up method to prepare electrocatalyst for oxygen evolution reaction (OER) and methanol oxidation reaction (MOR) is crucial for the high-efficient hydrogen production through water splitting. Herein, we load the CeO2 nanoparticles on the various metal foams by a very simple and scalable impregnation method. Taking iron-nickel foam (INF) as an example, we can obtain a high-efficient OER and MOR electrocatalyst of CeO2 @INF-0.6. CeO2 @INF-0.6 shows the superior electrocatalytic activities toward both OER and MOR with the oxidation potentials of 1.52 V and 1.47 V at 100 mA cm−2, respectively. This can be ascribed to the CeO2 @INF-0.6 with strong adsorption and fast conversion ability of OH- in the alkaline electrolyte. CeO2 @INF-0.6 also has good stability and selectivity in MOR-assisted alkaline water splitting, and the Faraday efficiency of formate is up to 99.2% at 1.42 V (vs. RHE). In addition, the Na+ and Cl- ions with high concentrations almost have the negligible effects on the OER and MOR activities of our CeO2 @INF-0.6 in the alkaline solution. This indicates that using CeO2 @INF-0.6 as anode for seawater electrolysis not only can greatly reduce the energy consumption, but produce the value-added anode product of formate.

Challenges in flotation scale-up: The impact of flotation kinetics and froth transport

At present, data from industrial flotation operations is still limited and more tests and in-depth studies are required to improve the experimental procedures, measurement devices and analysis, to validate and interpret scale-up factors from batch to plant flotation operations.The new methodologies have contributed to improve predictions of flotation metallurgical performance using more refined scale-up methods, for example, analyzing the scale-up factor by size and liberation classes. These will allow for selecting the best equipment for each mineral and flotation stage (rougher, cleaner and scavenger).In this work, the effect of the pulp zone hydrodynamics affecting the collection residence time and flotation kinetics, and the froth transport, on the overall scale-up factors (typically around 1.8–2.3) was evaluated per particle size classes in the range of 22.5 to 300 µm. Two effects were found that partially explain the scale-up factor in the pulp zone, such as the pulp mixing regime (4–16%) depending on the cells number, and the solids segregation (2–7%) that decreases the residence time of larger particles. However, the most important contribution was the froth transport characteristics that determines the froth recovery which accounted for 48–58% of the scale-up factor, also increasing with particle size. In addition, it was found that the remaining percentage of the overall scale-up factor, around 31%, includes the uncertainty in the collection residence time estimation, which is lower than the effective pulp residence time, and the larger residence time of bubbles in industrial cells. Both effects hinder the identification of the actual flotation rate in the pulp zone.

Self-Standing Porous Aromatic Framework Electrodes for Efficient Electrochemical Uranium Extraction.

Electrochemical uranium extraction from seawater provides a new opportunity for a sustainable supply of nuclear fuel. However, there is still room for studying flexible electrode materials in this field. Herein, we construct amidoxime group modified porous aromatic frameworks (PAF-144-AO) on flexible carbon cloths in situ using an easy to scale-up electropolymerization method followed by postdecoration to fabricate the self-standing, binder-free, metal-free electrodes (PAF-E). Based on the architectural design, adsorption sites (amidoxime groups) and catalytic sites (carbazole groups) are integrated into PAF-144-AO. Under the action of an alternating electric field, uranyl ions are selectively captured by PAN-E and subsequently transformed into Na2O(UO3·H2O)x precipitates in the presence of Na+ via reversible electron transfer, with an extraction capacity of 12.6 mg g-1 over 24 days from natural seawater. This adsorption-electrocatalysis mechanism is also demonstrated at the molecular level by ex situ spectroscopy. Our work offers an effective approach to designing flexible porous organic polymer electrodes, which hold great potential in the field of electrochemical uranium extraction from seawater.

A streamlined, automated workflow to screen and triage large numbers of baculoviruses for protein expression

The baculovirus expression system is a powerful and widely used method to generate large quantities of recombinant protein. However, challenges exist in workflows utilizing either liquid baculovirus stocks or the Titerless Infected-Cells Preservation and Scale-Up (TIPS) method, including the time and effort to generate baculoviruses, screen for protein expression and store large numbers of baculovirus stocks. To mitigate these challenges, we have developed a streamlined, hybrid workflow which utilizes high titer liquid virus stocks for rapid plate-based protein expression screening, followed by a TIPS-based scale-up for larger protein production efforts. Additionally, we have automated each step in this screening workflow using a custom robotic system. With these process improvements, we have significantly reduced the time, effort and resources required to manage large baculovirus generation and expression screening campaigns.

Electrospinning of High-Performance Nanofibres: State of the Art and Insights into the Path Forward

Nanofibrous membranes have gained interest for their small pore size, light weight, and excellent filtration. When produced from high-performance polymers, nanofibrous membranes also benefit from excellent mechanical properties, thermal resistance, and chemical resistance. Electrospinning is a common method of producing high-performance nanofibres. However, there are still major challenges with the dissolution and electrospinning of these polymers, as well as in the performance of the resulting nanofibres, which is often less than what would be expected from a conventional high-performance fibre. This review assesses the state of progress in the electrospinning of five high-performance fibres: meta-aramid (m-aramid), para-aramid (p-aramid), polyamide-imide (PAI), polybenzoxazole (PBO), and polybenzimidazole (PBI). Polymers that can be readily dissolved in organic solvents, such as m-aramid, PAI, and PBI, have been more widely researched for electrospinning compared to those that can only be spun from precursors or dissolved in non-volatile solvents. Major focuses within the literature include optimizing the electrospinning process and improving the mechanical performance of the nanofibres. This review demonstrates a clear need for more standardized characterization methods and consideration for the longevity of the nanofibrous membranes. Future research should also focus on scale-up methods of electrospinning so that the benefits of nanofibres made from high-performance polymers can be leveraged by the industry.

A computational-fluid-dynamics study on scaling up a single flat membrane reactor for on-site hydrogen production

The accessibility of hydrogen stations has been problematic for remote areas, although the demand for fuel-cell electric vehicles has risen. We propose a 50-Nm3/h on-site hydrogen production system using the accessible liquid-fuel infrastructure. The system integrates a pressurized steam reformer and a catalytic membrane reactor to produce high-purity hydrogen. This study focuses on scaling up our membrane reactor for enhanced hydrogen permeation while maintaining acceptable similarity and performance to make the system compact and effective. We compare three scale-up methods, which keep the inlet Reynolds number, gas hour space velocity, and Damköhler-Peclet number constant, respectively. After selecting the third case for its best similarity, we increase the scale to eight and conclude that any scale beyond four is not ideal for our specific membrane reactor. By increasing the scale to four, we reduce the number of reactors for the 50 Nm3/h target by 91% while achieving a hydrogen recovery of 91%. Future studies can refer to the scale-up process that maintains the reactor similarity and high performance in this work for choosing an appropriate scale for membrane reactors.

Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh

This study aimed to estimate the prevalence of illegal kidney sales in Kalai Upazila, Bangladesh, using the Network Scale-Up Method (NSUM), an ego-centric network survey-based technique used to estimate the...