Ultrasound-assisted microfluidic cell separation: A study on microparticles for enhanced cancer diagnosis

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(1)

Published: Jan. 1, 2025

Cancer continues to pose significant challenges globally, especially in developed countries, largely due delayed diagnosis and limited therapeutic options. Early detection of circulating tumor cells (CTCs) peripheral blood has emerged as a critical factor enhancing treatment efficacy, despite the inherent difficulty controllable target cell separation. To address this challenge, study introduces an innovative acoustofluidic system designed for separation CTCs from red cells. Leveraging principles standing surface acoustic waves (SSAWs) novel microfluidic channel design, promises advancements CTC isolation efficiency. The integration Multiphysics Finite Element Method multivariate surrogate modeling, which contribute generate datasets that predict performance proposed micro-electro-mechanical explaining migration phenomena. These mathematical models serve foundation applying two machine learning algorithms, differential evolution, multi-objective particle swarm optimization. integrated intelligent framework balances interplay variables, sheath flow rates, peak-to-peak voltage (Vpp). SSAW interaction times trajectory patterns are analyzed through controlled generation pressures within microchannel, efficiency while reducing energy consumption maximizing recovery rates. Precision manipulation is achieved by combining with optimized curved microchannel geometry developing dualized active zone improved control mechanisms movement. A 35% increase occurs when increases 10 V 15 constant IDT (interdigital transducer) aperture. Additionally, 72% observed aperture 10° 40° under voltage. Optimal 200 mm/s flowrate, voltage, 0.32 MPa pressure, resulting 100% rate. Furthermore, increasing reduces distance 30 μm, maximum lateral displacement 45 μm at 120 mm/s. By integrating computational simulations, experimental verifications, research unveils transformative potential miniaturized diagnostic platforms cancer therapeutics. This approach laboratory-on-chip technology paves way personalized medicine, real-time molecular analysis, point-of-care diagnostics.

Language: Английский

---

Machine learning and metaheuristics in microfluidic transport characterization and optimization: CFD and experimental study integrated with predictive modelling

The Canadian Journal of Chemical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 8, 2024

Abstract This study presents a comprehensive numerical and experimental analysis on microfluidic cell lysis through computational fluid dynamics (CFD), data‐driven modelling, multi‐objective optimization. The proposed intelligent framework integrates artificial intelligence CFD for data generation extraction, alongside machine learning studies transport phenomena characterization in the process. explores compound effects of various inflow Reynolds numbers geometrical parameters, including obstacle configurations microchannel thickness. It shows substantial flow patterns mixing varied designs. A surrogate model, developed via central composite design, exhibits high accuracy assessing system functionality (). height implemented baffles from its lower value to upper bound resulted more than 42% 14% increase index at low numbers, respectively, with minimal impact pressure drop. introduces modelling coupled optimization by desirability function (DF), non‐dominated sorting genetic algorithm (NSGA‐II), differential evolution (DE). In processes, algorithms outperform desirability‐based methods, DE surpasses NSGA‐II. An optimum micromixing reducing length over 50% above 97% achieved, fabricated, investigations conducted validate Through precise control variables exploitation microtransfer phenomena, it is possible enhance efficiency selectivity lysis. not only improves diagnostic information but also opens up new avenues personalized medicine therapeutic development.

Language: Английский

---

Combining multi-sensor signal fusion with signal decomposition for data augmentation in circuit breaker state recognition

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 126544 - 126544

Published: Jan. 1, 2025

Language: Английский

---

Biomimetic Intelligent Thermal Management Materials: From Nature‐Inspired Design to Machine‐Learning‐Driven Discovery

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 16, 2025

Abstract The development of biomimetic intelligent thermal management materials (BITMs) is essential for tackling challenges in electronics and aerospace applications. These possess not only exceptional conductivity but also environmental compatibility. However, developing such necessitates overcoming intricate challenges, as precise control over the material structure optimization material's properties stability. This review comprehensively overviews research progress BITMs, emphasizing synergy between design principles artificial‐intelligence‐driven methodologies to enhance their performance. unique nature‐inspired structures are explored valuable insights provided into adaptive strategies, which can be further enhanced through data analytics machine learning (ML). offers outlines future prospects advanced BITMs by integrating ML principles.

Language: Английский

---

Intelligent design of nerve guidance conduits: An artificial intelligence‐driven fluid structure interaction study on modelling and optimization of nerve growth

The Canadian Journal of Chemical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 18, 2024

Abstract Nerve guidance conduits (NGCs) have been shown to be effective in promoting nerve regeneration a variety of clinical applications, including defects resulting from trauma or surgery. By providing conducive environment for growth, NGCs can help restore function nerve‐damaged patients. Challenges include limited repair length, difficulty replicating natural nerve, and rapid substance degradation affecting neurotrophic factor delivery. Considering these issues with mass transfer fluid structure interaction (FSI) emphasizes the need enhancing efficiency. To facilitate growth deliver appropriate amount factors, designed specific topological, mechanical, biological properties. Additionally, considerations must given functional FSI design. An intelligent NGC design is proposed as an evaluation‐optimization AI‐based method. It found that parameters significantly impact physical properties being optimized, hydraulic pressure, porosity, diffusivity, water absorption, maximum stress. The mathematical surrogate model obtained data‐based modelling used artificial intelligence (AI) optimization algorithms, differential evolution (DE), non‐dominated sorting genetic algorithm II (NSGA‐II). revealed both DE NSGA algorithms generate nearly identical solutions, ensuring robustness ML optimization. Our results show thickness 750 μm more than 170% augmentation porosity. Moreover, at constant ovality, increasing channel 39.2% accurate forecasting characteristics on regarding factors enables hopeful outlook future treatment injuries advanced tissue engineering.

Language: Английский

---

A Miniaturized, Fuel-Free, Self-Propelled, Bio-Inspired Soft Actuator for Copper Ion Removal

Micromachines, Journal Year: 2024, Volume and Issue: 15(10), P. 1208 - 1208

Published: Sept. 29, 2024

We present a novel miniaturized, gear-shaped, fuel-free actuator capable of autonomously propelling itself in an aquatic environment to absorb heavy metals, such as copper ions. While hydrogel-based absorbents are promising solutions for cationic pollutant remediation, their stationary nature limits effectiveness areas where contaminants unevenly distributed. To address this, we developed bio-inspired soft that mimics natural propulsion mechanisms. The Marangoni effect, driven by its inherent chemical properties, demonstrated self-propelled motion without requiring external fuel. proof-of-concept generated plane lasting up 2 h and swept over area approximately 400 times bigger than size. By harnessing the optical properties hydrogel, efficiently removed quantitatively analyzed ions through colorimetric method. This innovative integration movement efficient ion absorption underscores potential advancing miniaturized devices environmental paving way more active removal systems challenging environments.

Language: Английский

---

Machine learning for predicting the PCM melting process in a rectangular enclosure energy storage

Published: Dec. 1, 2024

Language: Английский

---

Machine Learning and Genetic Algorithms in the Microfluidic Design of Highly Efficient Micromixers

Industrial & Engineering Chemistry Research, Journal Year: 2024, Volume and Issue: 63(43), P. 18626 - 18638

Published: Oct. 21, 2024

Microscale reactions are often used to determine the reactivity and byproducts of combinatorial between diverse chemicals. Despite significant work in designing microfluidic mixers, there still questions regarding achieving high mixing efficiency low-pressure drop at low Reynolds numbers. Microchannels with complex shapes have potential give speeds, but their design construction difficult, channel clogging due shape complexity restricts practical usage. In this study, we developed an approach create a highly effective micromixer using simple geometrical concepts barriers. We explored optimal geometries microchannels obstacles by employing machine learning conjunction number (Re) obtain maximum minimum pressure drop. Approximately 1000 different designs were simulated analyzed train model, focusing on index then utilized genetic algorithm optimize key parameters such as height obstacles, dent angle angular offset two barriers radius curvature micromixer, number. The optimization revealed that 190 μm obstacle height, 67° angle, 1102 radius, 53° distance resulted lowest To validate proposed design, fabricated standard soft lithography techniques.

Language: Английский

---

Determining Thermal Conductivity Coefficient of Nanofluid by Beam Displacement Method

IntechOpen eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 28, 2024

Accurate measurement of thermal properties fluids and nanofluids is essential for optimizing performance necessitating advanced techniques. Traditional methods, including transient steady-state techniques, have limitations such as longer testing times larger sample sizes. Optical like beam displacement laser interferometry, provide non-invasive, high-resolution measurements temperature fields conductivity. The method an optical technique that relies on the deviation a caused by changes in refractive index due to variations. Other likes interferometry enhance accuracy efficiency reducing reliance thermocouples capturing real-time data. methods reliable data applications various industrial engineering contexts. This chapter discusses different measuring functionality nano-fluids with focus non-invasive methods.

Language: Английский

---

Hydrogel impeller formation via vacuum degassing photopolymerization for micromixers

Sensors and Actuators A Physical, Journal Year: 2024, Volume and Issue: unknown, P. 116072 - 116072

Published: Nov. 1, 2024

Language: Английский

---