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Tremendous efforts have been devoted to the modeling of droplet deposition on smooth and patterned surfaces with ordered structures. However, systematic work focusing on randomly rough surfaces, which are the most common bare substrate surfaces, can be hardly identified. A phase field modeling method together with a unique analysis approach has been developed in this work to characterize single droplet deposition on randomly rough surfaces. It is interesting to observe that the droplet shape evolves quite differently on a randomly rough surface, as compared to a patterned surface, even if two surfaces have the same roughness. Parametric studies have been carried out to explore how the morphological metrics of randomly rough surfaces, which include the Wenzel roughness parameter (W r ) and the root-mean-square roughness (R r ), can affect droplet impact dynamics. The quantitative relationships derived from this study can eventually shed light on droplet shape on-aim control during the deposition process, which is of great practical importance in many applications.

An effective rate approach (ERA) is proposed to achieve a fast and reliable prediction of dryer outlet conditions for a given single-stage spray drying system operated under a range of scenarios. This approach is improved from existing methods based on simple mass and energy balances due to the incorporation of a reliable drying rate model, which is the reaction engineering approach for the material of interest. It allows quick solution procedure without the need to solve the partial differential equations that govern the heat and mass transfer in the spray drying process. By following a generic procedure, this technique has been exercised on the experimental results from running a monodisperse droplet spray dryer, that is, a well-established experimental platform for model validation. The proposed ERA has been shown to be rather promising. It could become a powerful approach for proactive control and optimization for existing spray drying facilities. V C 2015 American Institute of Chemical Engineers AIChE J, 61: [4140][4141][4142][4143][4144][4145][4146][4147][4148][4149][4150][4151] 2015 Keywords: spray drying, predictive modeling, effective rate approach, reaction engineering approach, proactive quality control IntroductionSpray drying is an effective process for large-scale powder production. Although this technique has been widely used in a variety of industries for many years, proactive control of powder product formation remains a challenge. [1][2][3][4][5] It is well known that the dryer inlet conditions that include the feed solution composition and operational settings all have significant influences on droplet formation through atomization, the airdroplet flow pattern, the air-droplet mass, and heat exchange in the drying chamber, and hence the dryer outlet conditions (i.e., the size, shape, moisture content, and morphology of the particles). 6,7 The quantitative relationships between dryer inlet and outlet conditions, however, remain unclear.Over the past decades, new dryer designs and optimized operations have been pursued by many research groups to deepen our scientific understanding of the spray drying process and to improve our control over powder formation dynamics. Counter-current spray drying towers are suitable for thermally stable products such as detergents and ceramics as the hot gas comes in contact with dry particles just before the particles exit the tower. Cocurrent spray dryers are the best choice for heat sensitive products like milk powders, where thermal degradation and aroma retention are of concern. Hot gas comes in contact with the droplets at the top where the droplets have maximum moisture content and are at the wet bulb temperature. 8,9 With this configuration, the driest particles are eventually coupled with the lowest temperatures Correspondence concerning this article should be addressed to J. Xiao at jie. xiao@suda.edu.cn or X. D. Chen at xdc@xmu.edu.cn; xdchen@suda.edu.cn. 4140AIChE Journal December 2015 Vol. 61, No. 12 (i.e., the outlet temperatures). A single-stream ...

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In light of environmental issues, lignocellulosic empty fruit bunch (EFB) biomass is promoted as a carbon–neutral, environmentally friendly, and renewable alternative feedstock. A comprehensive environmental assessment of EFB biorefineries is critical for determining their sustainability in parallel with the bioeconomy policy. Nonetheless, no life cycle assessment (LCA) has been performed on co-producing food and biochemicals (furfural and glucose) derived from EFB biomass. This research is the first to evaluate the environmental performance of the furfural and glucose co-production processes from EFB biomass. Environmental analysis is conducted using a prospective gate-to-gate LCA for four impact categories, including global warming potential (GWP), acidification (ADP), eutrophication (EP), and human toxicity (HT). Aspen Plus is used to simulate the co-production process of furfural and glucose as well as generate mass and energy balances for LCA inventory data usage. The findings suggest that the environmental footprint in respect of GWP, ADP, EP, and HT is 4846.85 kg CO 2 equivalent per ton EFB, 7.24 kg SO 2 equivalent per ton EFB, 1.52 kg PO 4 equivalent per ton EFB, and 2.62E-05 kg 1,4-DB equivalent per ton EFB, respectively. The normalized overall impact scores for GWP, ADP, EP, and HT are 1.16E-10, 2.28E-11, 6.12E-10, and 2.18E-17 years/ton of EFB, respectively. In summary, the proposed integrated plant is not only economically profitable but also environmentally sustainable. In the attempt to enhance the Malaysian economic sector based on the EFB, this study has the potential to serve as an indicator of the environmental sustainability of the palm oil industry. Graphical abstract Supplementary Information The online version contains supplementary material available at 10.1007/s10668-022-02633-8.

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