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Machine Learning and Physics-Driven Modelling and Simulation of Multiphase systems

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SSRN 2024年

作者： Basha, Nausheen Arcucci, Rossella Angeli, Panagiota Anastasiou, Charitos Abadie, Thomas Casas, César Quilodrán Chen, Jianhua Cheng, Sibo Chagot, Loïc Galvanin, Federico Heaney, Claire E. Hossein, Fria Hu, Jinwei Kovalchuk, Nina Kalli, Maria Kahouadji, Lyes Kerhouant, Morgan Lavino, Alessio Liang, Fuyue Nathanael, Konstantia Magri, Luca Lettieri, Paola Materazzi, Massimiliano Erigo, Matteo Pico, Paula Pain, Christopher C. Shams, Mosayeb Simmons, Mark Traverso, Tullio Valdes, Juan Pablo Wolffs, Zef Zhu, Kewei Zhuang, Yilin Matar, Omar K. Department of Chemical Engineering Imperial College London United Kingdom Department of Earth Science & Engineering Imperial College London United Kingdom Department of Chemical Engineering University College London United Kingdom School of Chemical Engineering University of Birmingham United Kingdom Data Science Institute Department of Computing Imperial College London United Kingdom State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing China Centre for AI-Physics Modelling Imperial-X White City Campus Imperial College London United Kingdom The Alan Turing Institute British Library 96 Euston Road LondonNW1 2DB United Kingdom Department of Aeronautics Imperial College London United Kingdom Institute of Physics University of Amsterdam Science Park Amsterdam904 Netherlands Nikhef Science Park Amsterdam105 Netherlands Department of Computer Science University of York United Kingdom

We highlight the work of a multi-university collaborative programme, PREMIERE (PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE systems), which is at the intersection of multi-physics and machine learning, aiming to enhance predictive capabilities in complex multiphase flow systems across diverse length and time scales. Our contributions encompass a variety of approaches, including the Design of Experiments for nanoparticle synthesis optimisation, Generalised Latent Assimilation models for drop coalescence prediction, Bayesian regularised artificial neural networks, eXtreme Gradient Boosting for microdroplet formation prediction, and a sub-sampling based adversarial neural network for predicting slug flow behaviour in two-phase pipe flows. Additionally, we introduce a generalised latent assimilation technique, Long Short-Term Memory networks for sequence forecasting mixing performance in stirred and static mixers, active learning via Bayesian optimisation to recover coalescence model parameters for high current density electrolysers, Gaussian process regression for drop size distribution predictions for sprays, and acoustic emission signal inversion using gradient boosting machines to characterise particle size distribution in fluidised beds. We also offer perspectives on the development of a shape optimisation framework that leverages the use of a multi-fidelity multiphase emulator. The results presented have applications in chemical synthesis, microfluidics, product manufacturing, and green hydrogen generation. © 2024, The Authors. All rights reserved.

关键词： Forecasting

Low-Temperature Synthesis of Weakly Confined Carbyne inside Single-Walled Carbon Nanotubes

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arXiv

arXiv 2024年

作者： Zhang, Bo-Wen Qiu, Xi-Yang Ma, Yicheng Hu, Qingmei Fitó-Parera, Aina Kohata, Ikuma Feng, Ya Zheng, Yongjia Zhang, Chiyu Matsuo, Yutaka Wang, YuHuang Chiashi, Shohei Otsuka, Keigo Xiang, Rong Levshov, Dmitry I. Cambré, Sofie Wenseleers, Wim Rotkin, Slava V. Maruyama, Shigeo Department of Mechanical Engineering The University of Tokyo Tokyo113-8656 Japan State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Theory and Spectroscopy of Molecules and Materials Department of Physics University of Antwerp Antwerp2610 Belgium Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education School of Energy and Power Engineering Dalian University of Technology Liaoning 116024 China Department of Chemistry and Biochemistry Chemical Physics Program Maryland Nano Center University of Maryland College ParkMD20742 United States Department of Chemical Systems Engineering Graduate School of Engineering Nagoya University Nagoya464-8603 Japan Institute of Materials Innovation Institutes for Future Society Nagoya University Nagoya464-8603 Japan Theory and Spectroscopy of Molecules and Materials Department of Chemistry University of Antwerp Antwerp2610 Belgium Nanostructured and Organic Optical and Electronic Materials Department of Physics University of Antwerp Antwerp2610 Belgium Materials Research Institute Department of Engineering Science & Mechanics The Pennsylvania State University University ParkPA16802 United States

Carbyne, a one-dimensional (1D) carbon allotrope with alternating triple and single bonds, has the highest known mechanical strength but is unstable to bending, limiting synthesis to short linear chains. Encapsulation within carbon nanotubes (CNTs) stabilizes carbyne, forming confined carbyne (CC), thus enabling further research concerning attractive 1D physics and materials properties of carbyne. While CC has been synthesized in multi-walled CNTs (MWCNTs) using the arc-discharge method and in double-walled CNTs (DWCNTs) via high-temperature high-vacuum (HTHV) method, synthesis in single-walled CNTs (SWCNTs) has been challenging due to their fragility under such conditions. In this work, we report a low-temperature method to synthesize CC inside SWCNTs (CC@SWCNT). By annealing SWCNTs containing ammonium deoxycholate (ADC) at 400°C, ADC is converted into CC without damaging the SWCNTs. Raman spectroscopy revealed a strong CC phonon (CC-mode) peak at 1860–1870 cm-1, much stronger than the SWCNT G-band peak, confirming a high fraction of CC in the resulting material. The Raman mapping result showed the uniformity of the CC-mode signal across the entire film sample, proving the high efficiency of this method in synthesizing CC in every SWCNT of appropriate size. Notably, the CC-mode peaks of CC@SWCNT (above 1860 cm-1) are higher than those reported in previous CC@CNT samples (mostly -1). This is attributed to larger SWCNT diameters (>0.95 nm) used in this study, compared to the typical 0.6–0.8 nm range. Larger diameters result in reduced confinement, allowing carbyne to closely resemble free-standing carbyne while remaining stabilized. This low-temperature synthesis of long-chain, nearly freestanding carbyne within large-diameter SWCNTs offers new opportunities for exploring 1D physics and the unique properties of carbyne for potential applications. © 2024, CC BY-NC-ND.

关键词： Single-walled carbon nanotubes (SWCN)

Visualizing light-induced dynamic structural transformations of Au clusters-based photocatalyst via in situ TEM

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Nano Research 2021年第8期14卷 2805-2809页

作者： Bo Weng Youhong Jiang Hong-Gang Liao Maarten B.J.Roeffaers Feili Lai Haowei Huang Zichao Tang State Key Laboratory for Physical Chemistry of Solid Surfaces Collaborative Innovation Center of Chemistry for Energy MaterialsCollege of Chemistry and Chemical Engineering Xiamen UniversityXiamen 361005China cMACS Department of Microbial and Molecular SystemsKU LeuvenCelestijnenlaan 200F3001 LeuvenBelgium Department of Chemistry KU LeuvenCelestijnenlaan 200F3001 LeuvenBelgium

Ultrasmall gold(Au)clusters have been regarded as one of the prototypes materials for solar energy conversion due to their unique strong molecular-like light absorption ***,the light-induced aggregation of Au clusters into nanoparticles is one of the most important factors that restricts its application in *** Au clusters aggregation has been widely demonstrated,the underlying mechanism for cluster fusion is still unclear due to the lack of experimental ***,we report the direct observation of Au clusters on TiO_(2) nanosheets aggregating when used as visible light photocatalysts for the reduction of *** in situ high-resolution transmission electron microscopy(TEM),the coexistence of two fusion mechanisms of Au clusters on TiO_(2) under ultraviolet-visible(UV-Vis)light irradiation in air is identified,i.e.,the migration and coalescence(MC)and Ostwald ripening(OR).Additionally,the correlation between the photostability of Au clusters and reaction atmospheres has been investigated,among which Au clusters have higher stability in an inert N_(2) atmosphere or vacuum than the oxidizing atmospheres(i.e.,air and O_(2)).These results indicate the inherent stability of Au cluster during photocatalysis,and instability comes from the consuming of ligand *** work not only discloses the underlying mechanism of Au cluster sintering but also provides guidelines for enhancing metal clusters-based photocatalysts stability.

关键词： photocatalysis dynamic structural transformation Au clusters in situ TEM

Joint Task Offloading and Uav Trajectory Optimization in Dynamic Edge Computing systems: A Deep Reinforcement Learning Approach

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SSRN 2025年

作者： Wang, Yitian Wang, Hui Ding, Jingfang Yu, Haibin School of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China

This paper addresses latency challenges in cloud-based task offloading caused by geographical server-user disparities by integrating Unmanned Aerial Vehicles (UAVs) with Mobile Edge Computing (MEC). We propose a dynamic UAV-assisted framework that optimizes real-time parameter adjustments to minimize system latency. Key challenges include joint task offloading, UAV trajectory optimization, and User Equipment (UE) occlusion detection under mobility constraints. To resolve these, we transform the problem into a Markov Decision Process (MDP) and develop an enhanced Adaptive Delayed Deep Deterministic Policy Gradient (AD3PG) algorithm, which improves upon DDPG by incorporating delayed updates and neural network tuning. The algorithm dynamically optimizes three critical aspects: UAV-UE connectivity establishment, occlusion-aware dual noise power configuration, and adaptive task offloading ratios. Extensive simulations demonstrate AD3PG’s superiority over baseline methods such as DDPG and Twin-Delayed DDPG (TD3) in reducing total system latency by 13.2–35.3% under dynamic scenarios. These results validate the framework’s efficacy for latency-sensitive applications in UAV-MEC systems. © 2025, The Authors. All rights reserved.

关键词： Drones

Stochastic Limit Cycle for Self-Induced Stochastic Resonance

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Stochastic Limit Cycle for Self-Induced Stochastic Resonance

第八届国际振动工程会议

作者： Jinjie Zhu Department of Systems and Control Engineering Tokyo Institute of Technology School of Mechanical Engineering Nanjing University of Science and Technology

Noise is inevitable in all kinds of theoretical and practical systems. Despite of the detrimental effect of noise as is usually considered, it could induce various intriguing phenomena, such as stochastic resonance and coherence resonance. Self-induced stochastic resonance, which is one of the interesting resonance behaviors for multiple timescale system, exhibits almost coherent oscillations for noise present on the fast subsystem. It can be explained by large deviation theory for the limit of vanishing noise and large timescale separation. However, for finite noise strength and timescale separation, there will be some deviations which may influence the identification of the mean period of the stochastic limit *** this manuscript, we derive the formula for the calculation of the critical transition position which shows great agreement with the results of Monte Carlo simulation.

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A Novel Peptide-Based Fluorometric and Colorimetric Probe for Cascade Detection of Copper(Ii) and Glyphosate: Applications in Real Sample, Cells Imaging, Test Strips and Smartphone-Assisted Recognition

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SSRN 2024年

作者： Wang, Peng Zheng, Maoyue Zhou, Miao Wang, Yiwen Shang, Shiyu He, Qian An, Yong Chemical Synthesis and Pollution Control Key Laboratory of Sichuan Province College of Chemistry and Chemical Engineering China West Normal University Shida Road 1# Nanchong637009 China The First School of Clinical Medicine Gansu University of Chinese Medicine Gansu Lanzhou730030 China Sichuan Engineering Research Center for Molecular Targeted Diagnostic & Therapeutic Drugs Department of Chemistry Xihua University PR Chengdu610039 China

A new dual-signals peptide-based probe (FAHF) by conjugating 5-carboxy fluorescein (5-FAM) fluorophore with a tripeptide backbone (Ala-His-Phe-NH2) was successfully synthesized. According to design, FAHF exhibited favorable properties for sensing Cu2+ by fluorescence quenching and colorimetric color change among various metal ions, such as good water solubility, excellent selectivity, wide pH range and high quantum yield. In addition, the binding constant of FAHF-Cu2+ was 1.2 × 1010 M-2 and the detection limit (LOD) of Cu2+ was attained 51.1 nM. The fluorescence titration, Job’s plot and high resolution mass spectrometry (ESI-HRMS) analysis indicated that a 2:1 complex formation between FAHF and Cu2+. Notably, the resulting FAHF-Cu2+ complex displayed "turn-on" fluorescence and colorimetric response upon addition of glyphosate based on displacement approach, and could realize naked eye recognition with color changed under 365 nm UV light and visible light. FAHF-Cu2+ complex exhibited a good linear relationship at ultra-low concentrations glyphosate with a detection limit of 46.8 nM. Furthermore, fluorescence imaging applications demonstrated that FAHF was successfully applied for cascade detection of Cu2+ and glyphosate in living Hacat cells based on low toxicity. Moreover, FAHF was successfully used to determine Cu2+ and glyphosate in two water samples with satisfactory results. More importantly, the test strips with FAHF was fabricated for identifying Cu2+ and glyphosate under 365 nm UV light and visible light, and the RGB channel in smartphone was used to convert different solution colors into digital values, which was successfully used for semi-quantitative recognition of Cu2+ and glyphosate. © 2024, The Authors. All rights reserved.

关键词： Fluorescence quenching

Physics-informed machine learning predicting CO 2 capture performances of organic mixtures

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chemical engineering and Processing - Process Intensification 2025年 216卷

作者： Ulderico Di Caprio Florence Vermeire Tom Van Gerven M․Enis Leblebici Process Engineering for Sustainable Systems Department of Chemical Engineering KU Leuven Agoralaan Building B 3590 Diepenbeek Belgium Chemical Reactor Engineering and Safety (CREaS) Department of Chemical Engineering KU Leuven Celestijnenlaan 200F B-3001 Heverlee Belgium Process Engineering for Sustainable Systems Department of Chemical Engineering KU Leuven Celestijnenlaan 200F B-3001 Heverlee Belgium

CO₂ capture through amine absorption is an effective technology for combating global warming. The development of innovative solvents can enhance this process by increasing CO₂ solubility and reducing the size of required absorption columns. However, these solvents often involve both physical and chemical absorption mechanisms, necessitating extensive experimentation to characterise new solvent mixtures, which slows innovation. This study introduces a hybrid physics-informed model to predict CO₂ solubility in absorption mixtures. The model is designed to predict the behaviour of novel mixtures by characterising individual absorption mechanisms and incorporating physics-based insights to evaluate the contributions of each mechanism according to the mixture type. We benchmarked the hybrid model against a data-driven approach, training it on comprehensive literature data across diverse mixture types. The hybrid model demonstrated superior performance with an R² of 0.929 on the test set, outperforming the data-driven model with an R² of 0.611. It also exhibited lower bias across mixture categories, greater robustness in predictions and their physical adherence as highlighted by the executed SHAP analysis. By enabling accurate digital predictions of novel solvent mixtures, this hybrid model promotes process intensification, accelerating the development of more sustainable CO₂ capture technologies and contributing to a greener future.

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Polyamide Nanofiltration Membranes with Enhanced Janus Surface Charge Via Large Aqueous Monomer

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SSRN 2024年

作者： Shi, Yimeng Wen, He Wang, Jing Dai, Ziwen Yang, Zhao Yu, Wenbo Liang, Sha Yang, Jiakuan Yuan, Shushan Van der Bruggen, Bart Hubei Provincial Research Center of Water Quality Safety and Water Pollution Control Engineering Technology Huazhong University of Science and Technology Hubei Wuhan430074 China Hubei Provincial Engineering Laboratory for Solid Waste Treatment Disposal and Recycling Hubei Wuhan430074 China Hubei Three Gorges Laboratory Yichang443007 China Department of Chemical Engineering KU Leuven Celestijnenlaan 200F HeverleeB-3001 Belgium

The charge properties of polyamide membranes play a crucial role in the selective ionic and molecular sieving processes. These polyamide membranes fabricated through interfacial polymerization normally exhibit a front surface enriched with carboxyl groups and a rear surface enriched with amine groups, rendering it with a Janus surface charge. However, this disparity in charge properties between the two surfaces has not been thoroughly investigated, despite its importance in understanding the membrane formation mechanism. In this study, polyethylenimine (PEI, Mw=70000 Da) and piperazine (PIP, Mw=86 Da), with distinct molecular size, were employed as aqueous monomers to react with trimesoyl chloride (TMC) at a support-free water hexane interface to synthesize polyamide nanofiltration membranes. The charge differences in the rear and front surface of PEI/TMC and PIP/TMC nanofiltration membrane was fully explored. The PEI/TMC membrane demonstrated a great charge disparity between the two surfaces with a negatively charged (isoelectric point=5.62) front surface and a positively charged (isoelectric point=9.59) rear surface. As a result, the rear surface exhibits a higher MgCl2 rejection (95.6%) than the front surface (88.9%). In contrast, the PIP/TMC membrane exhibited a similar negative charge and salt rejections on both surfaces. This indicates the Janus surface charge of the polyamide nanofiltration membranes could be enhanced via using large aqueous monomer. Moreover, the rear surface of PEI/TMC membrane exhibited a great anti-fouling performance to positively charged lysozyme (FDR=51.1%, FRR=88.8%), while the front surface showed a high resistance to negatively charged humic acid (HA) (FDR=27.3%, FRR=90.8%). This work provides valuable insights into the mechanisms of an interfacial polymerization process and proposes a new approach for the surface charge regulation of nanofiltration membranes. © 2024, The Authors. All rights reserved.

关键词： Monomers

Frequency response data based LPV controller synthesis applied to a control moment gyroscope

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arXiv

arXiv 2021年

作者： Bloemers, Tom Tóth, Roland Oomen, Tom The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Control Systems Technology Department of Mechanical Engineering Eindhoven University of Technology The Systems and Control Laboratory Institute for Computer Science and Control Kende u. 13-17 BudapestH-1111 Hungary

control of systems with operating condition-dependent dynamics, including control moment gyroscopes, often requires operating condition-dependent controllers to achieve high control performance. The aim of this paper is to develop a frequency response data-driven linear parameter-varying control design approach for single-input single-output systems, which allows improved performance for a control moment gyroscope. A stability theory using closed-loop frequency response function data is developed, which is subsequently used in a synthesis procedure that guarantees local stability and performance. Experimental results on a control moment gyroscope demonstrate the performance improvements. Copyright © 2021, The Authors. All rights reserved.

关键词： controllers