Continuous-flow reactors for the rapid evolution and validation of kinetic motifs

In this paper we apply the concept of a kinetic motif as a simple way to represent all the time-dependent behaviour in a single-step or multi-step reaction system. Small-scale continuous-flow reactors offer the potential to rapidly collect large amounts of data while accessing conventionally challenging experimental conditions. The scope of the approach is demonstrated on reaction case study examples

Effect of Price Dynamics in the Design of Eco-Industrial Parks: An Agent-based Modelling Approach

Even though eco-industrial parks (EIP) models have proved to transform industrial areas by strengthen the emergence of sustainable EIP, there is a noticeable lack of research addressing the economic returns of the participating companies in the network which fluctuates according to prices offered for the resource exchange over time. In this paper, we develop an agent-based model sometimes refer to as bottom-up approach for the design of EIP in which price fluctuation and demand variability are emergent properties of the interaction among the agents. Agent-based modelling (ABM) is a computational methodology used in social science, biology, and other fields. It represents autonomous entities, each with dynamic behaviour. The agents within the eco-industrial park are the factories, market buyers and market sellers. The computational development was performed in Réseau.py, which was built in Python (a programmable modelling environment) from scratch. Based on the autonomy of each of the agents and their individual objectives, simulations were carried out on a bio-energy based EIP (BBEIP) system in order to study the influence of price fluctuation between the agents. The results show that variability in price is a factor for establishing symbiotic relationship among the symbiotic agents in the EIP

Determination of mass transfer resistances in trickle bed reactors

A methodology for determining the mass transfer resistances of three-phase reactions in trickle bed reactors is presented. The hydrogenation of styrene over Pd/C was used as a case study to demonstrate the methodology. The gas-liquid mass transfer resistance was experimentally approximated by changing the palladium content of the bed while the chemical reaction resistance was calculated by using the observed chemical reaction rate constant which has been experimentally approximated in two different stirred tank reactors by hydrogenating the same compound under the same temperature and using the same solvent and active catalytic metal. The liquid-solid mass transfer resistance was calculated by subtracting the gas-liquid mass transfer resistance and the chemical reaction resistance from the overall resistance. The wetting efficiency of the bed was estimated from the experimental data and it was compared to the literature by using the dimensionless numbers of Re, Fr, Mo, Ga, We and Stk. The specific gas-liquid and liquid-solid mass transfer coefficients found in agreement with the literature

Machine learning potentials for complex aqueous made

Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex systems such as solid–liquid interfaces. Here we present a machine learning framework that enables the efficient development and validation of models for complex aqueous systems. Instead of trying to deliver a globally optimal machine learning potential, we propose to develop models applicable to specific thermodynamic state points in a simple and user-friendly process. After an initial ab initio simulation, a machine learning potential is constructed with minimum human effort through a data-driven active learning protocol. Such models can afterward be applied in exhaustive simulations to provide reliable answers for the scientific question at hand or to systematically explore the thermal performance of ab initio methods. We showcase this methodology on a diverse set of aqueous systems comprising bulk water with different ions in solution, water on a titanium dioxide surface, and water confined in nanotubes and between molybdenum disulfide sheets. Highlighting the accuracy of our approach with respect to the underlying ab initio reference, the resulting models are evaluated in detail with an automated validation protocol that includes structural and dynamical properties and the precision of the force prediction of the models. Finally, we demonstrate the capabilities of our approach for the description of water on the rutile titanium dioxide (110) surface to analyze the structure and mobility of water on this surface. Such machine learning models provide a straightforward and uncomplicated but accurate extension of simulation time and length scales for complex systems

Process Monitoring of Moisture Content and Mass Transfer Rate in a Fluidised Bed with a Low Cost Inline MEMS NIR Sensor

Purpose The current trend for continuous drug product manufacturing requires new, affordable process analytical techniques (PAT) to ensure control of processing. This work evaluates whether property models based on spectral data from recent Fabry–Pérot Interferometer based NIR sensors can generate a high-resolution moisture signal suitable for process control. Methods Spectral data and offline moisture content were recorded for 14 fluid bed dryer batches of pharmaceutical granules. A PLS moisture model was constructed resulting in a high resolution moisture signal, used to demonstrate (i) endpoint determination and (ii) evaluation of mass transfer performance. Results The sensors appear robust with respect to vibration and ambient temperature changes, and the accuracy of water content predictions (±13 % ) is similar to those reported for high specification NIR sensors. Fusion of temperature and moisture content signal allowed monitoring of water transport rates in the fluidised bed and highlighted the importance water transport within the solid phase at low moisture levels. The NIR data was also successfully used with PCA-based MSPC models for endpoint detection. Conclusions The spectral quality of the small form factor NIR sensor and its robustness is clearly sufficient for the construction and application of PLS models as well as PCA-based MSPC moisture models. The resulting high resolution moisture content signal was successfully used for endpoint detection and monitoring the mass transfer rate

Developing Crisis Training Software for Local Governments – From User Needs to Generic Requirements

In this paper we analyze and present the generic requirements identified for a software aiming at supporting crisis management training in local governments. The generic requirements are divided into overall requirements, requirements connected to the trainer’s role and requirements connected to the trainee’s role. Moreover, the requirements are mapped to problems as well as opportunities. Finally, we present examples of elaborations of the addressed requirements based on software design considerations. In our work we applied a design science approach and the artifact presented in this paper is a list of generic requirement. The presented requirements and the systems development process used, provide guidelines for systems analysts and developers in future systems development projects aiming at constructing new software for crisis management training

An Examination of Morphometric Variations in a Neotropical Toad Population (Proceratophrys cristiceps, Amphibia, Anura, Cycloramphidae)

The species Proceratophrys cristiceps belongs to the genus Proceratophrys within the family Cycloramphidae. These amphibians are found exclusively in South America in the morphoclimatic domain of the semi-arid depression zones in northeastern Brazil known as the Caatinga. We examined intrapopulational variation using univariate and multivariate statistics with traditional and geometric morphometrics, which supported the existence of two morphotypes of this species. Our results indicated significant degrees of variation in skeletal characteristics between some natural populations of this species. Careful analyses of variability levels are fundamental to avoid taxonomic errors, principally in populations that demonstrate characteristics intimately associated with their area of occurrence, as is the case of Proceratophrys cristiceps

Opportunities for process intensification technologies in nuclear effluent treatment: A review of precipitators, adsorbers and separators

This paper reviews the technologies and opportunities for process intensification (PI) in nuclear effluent treatment. PI is an area that has already created many innovations within the chemicals industry, and offers a growing field of research and development potential for nuclear operations. Technologies are considered here to be those ultimately resulting in step-change improvements to a number of operational aspects; such as smaller unit footprints, enhanced heat and mass transfer, reduction in secondary wastes, improved process safety and synergy, or direct integration with other downstream processes. Herein, we conduct a rigorous evaluation and scoping assessment of unit designs for the treatment of nuclear liquid effluents and solid-liquid waste management. Specific focus is given to precipitation, adsorption and separation operations, where over 250 articles are detailed, and prospects for technology transfer are discussed. In general, there is a trade-off in PI designs between operational simplicity (which may be more easily adopted in nuclear treatments) and more mechanically complex strategies that may, however, attain suitable scale-up requirements. Analysed options vary from those that would be radically different for industry, to those where applications are increasingly common in other process areas, with the advantages and limitations of all being discussed

Reference values for exhaled nitric oxide (reveno) study

BACKGROUND: Despite the widespread use of fractional exhaled nitric oxide (FE(NO)) as a biomarker of airways inflammation, there are no published papers describing normal FE(NO )values in a large group of healthy adults. OBJECTIVE: The aim of this study was to establish adult FE(NO )reference values according to the international guidelines. METHODS: FE(NO )was measured in 204 healthy, non-smoking adults with normal spirometry values using the on-line single-breath technique, and the results were analysed chemiluminescently. RESULTS: The main result of the study was the significant difference in FE(NO )values between men and women, thus indicating that gender-based reference FE(NO )values are necessary. The FE(NO )levels obtained at expiratory flows of 50 ml/s ranged from 2.6 to 28.8 ppb in men, and from 1.6 to 21.5 ppb in women. CONCLUSION: We propose reference FE(NO )values for healthy adult men and women that could be used for clinical and research purposes