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mechanically interlocked two-dimensional polymers

Journal of Bio-X Research 2025年第6731期387卷 264-269页

作者： Bardot, Madison I. Weyhrich, Cody W. Shi, Zixiao Traxler, Michael Stern, Charlotte L. Cui, Jinlei Muller, David A. Becker, Matthew L. Dichtel, William R. Department of Chemistry Northwestern University Evanston IL United States Department of Chemistry Duke University Durham NC United States Department of Chemistry and Chemical Biology Cornell University Ithaca NY United States School of Applied and Engineering Physics and Kavli Institute at Cornell for Nanoscale Science Cornell University Ithaca NY United States Thomas Lord Department of Mechanical Engineering and Materials Science Department of Biomedical Engineering Department of Orthopedic Surgery Duke University Durham NC United States

mechanical bonds arise between molecules that contain interlocked subunits, such as one macrocycle threaded through another. Within polymers, these linkages will confer distinctive mechanical properties and other emergent behaviors, but polymerizations that form mechanical bonds efficiently and use simple monomeric building blocks are rare. In this work, we introduce a solid-state polymerization in which one monomer infiltrates crystals of another to form a macrocycle and mechanical bond at each repeat unit of a two-dimensional (2D) polymer. This mechanically interlocked 2D polymer is formed as a layered solid that is readily exfoliated in common organic solvents, enabling spectroscopic characterization and atomic-resolution imaging using advanced electron microscopy techniques. The 2D mechanically interlocked polymer is easily prepared on multigram scales, which, along with its solution processibility, enables the facile fabrication of composite fibers with Ultem that exhibit enhanced stiffness and strength. © 2025 the authors,

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Direct Printing of High-Resolution Metallic Three-Dimensional Microneedle Arrays Via Electrohydrodynamic Jet Printing

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Journal of Micro and Nano Science and engineering 2024年第2期12卷 021001页

作者： Wardell, Karson Yao, Yao Jiang, Qingrui Ding, Shinghua Wang, Yi Han, Yiwei Department of Mechanical Engineering University of Mississippi Oxford MS 38677 Department of Industrial and Systems Engineering University of Missouri Columbia MO 65211 Department of Chemical and Biomedical Engineering University of Missouri Columbia MO 65211

Three-dimensional (3D) microneedle arrays (MAs) have shown remarkable performances for a wide range of biomedical applications. Achieving advanced customizable 3D MAs for personalized research and treatment remain a formidable challenge. In this paper, we have developed a high-resolution electrohydrodynamic (EHD) 3D printing process for fabricating customizable 3D MAs with economical and biocompatible molten alloy. The critical printing parameters (i.e., voltage and pressure) on the printing process for both two-dimensional (2D) and 3D features are characterized, and an optimal set of printing parameters was obtained for printing 3D MAs. We have also studied the effect of the tip-nozzle separation speed on the final tip dimension, which will directly influence MAs' insertion performance and functions. With the optimal process parameters, we successfully EHD printed customizable 3D MAs with varying spacing distances and shank heights. A 3 × 3 customized 3D MAs configuration with various heights ranging from 0.8 mm to 1 mm and a spacing distance as small as 350μm were successfully fabricated, in which the diameter of each individual microneedle was as small as 100μm. A series of tests were conducted to evaluate the printed 3D MAs. The experimental results demonstrated that the printed 3D MAs exhibit good mechanical strength for implanting and good electrical properties for electrophysiological sensing and stimulation. All results show the potential applications of the EHD printing technique in fabricating cost-effective, customizable, high-performance MAs for biomedical applications.

关键词： Printing Microneedles Pressure Resolution (Optics) Electrohydrodynamics

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Advancements,Challenges,and Future Perspectives of MXenes in Biomedicine

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SmartMat 2025年第2期6卷 50-93页

作者： Thi Nhat Linh Phan Thi Xuan Nguyen Thi Thuy Truong Thi Kim Ngan Duong Vu Hoang Minh Doan Truong Tien Vo Mrinmoy Misra Jaeyeop Choi Umapada Pal Junghwan Oh Sudip Mondal Industry 4.0 Convergence Bionics Engineering Department of Biomedical EngineeringPukyong National UniversityBusanRepublic of Korea Smart Gym-Based Translational Research Center for Active Senior's Healthcare Pukyong National UniversityBusanRepublic of Korea Mechatronics Engineering Department School of AutomobileMechanical and MechatronicsManipal UniversityJaipurIndia Institute of Physics Autonomous University of PueblaPueblaMexico Ohlabs Corp. BusanRepublic of Korea Digital Healthcare Research Center Pukyong National UniversityBusanRepublic of Korea

MXenes,a unique class of two-dimensional(2D)transition metal carbides,nitrides,and carbonitrides,have garnered significant interest due to their exceptional chemical,mechanical,and electrical *** recent studies predominantly focus on MXenes'applications in catalysis,energy storage and harvesting,photocatalysis,and lightweight materials,their potential in biomedicine is comparatively *** review aims to bridge this gap by providing a comprehensive and up-to-date overview of MXenes in biomedical applications,specifically highlighting advanced uses such as photothermal therapy and photodynamic therapy for cancer treatment,as well as their roles in biomedical imaging and as contrast agents for tumor *** examine the synthesis and chemical modifications of MXenes,including functionalization,etching,and exfoliation techniques that enable tailored properties for *** article highlights MXenes'advantages,including high surface area,tunable surface chemistry,and biocompatibility,while also addressing challenges and future research directions to unlock their full biomedical *** focused exploration of MXenes in cutting-edge biomedicine sets this review apart,highlighting its significance in advancing MXenes'role in modern biomedical research.

关键词： bioimaging biomedical applications cancer treatment MXenes photodynamic therapy(PDT) photothermal therapy(PTT)

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Hydrodynamic Performance of Euplectella aspergillum:Simulating Real Life Conditions in the Abyss

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Communications in Computational Physics 2023年第1期33卷 273-282页

作者： Giacomo Falcucci Giorgio Amati Pierluigi Fanelli Sauro Succi Maurizio Porfiri Department of Enterprise Engineering“Mario Lucertini” University of Rome“Tor Vergata”RomeItaly Department of Physics Harvard UniversityCambridgeMAUSA High Performance Computing Department CINECA Rome SectionRomeItaly DEIM School of EngineeringUniversity of TusciaViterboItaly Italian Institute of Technology Center for Life Nano-and Neuro-ScienceRomeItaly National Research Council of Italy–Institute for Applied Computing(IAC) RomeItaly Department of Biomedical Engineering Tandon School of EngineeringNew York UniversityNew YorkNYUSA Department of Mechanical and Aerospace Engineering Tandon School of EngineeringNew York UniversityNew YorkNYUSA Center for Urban Science and Progress Tandon School of EngineeringNew York UniversityNew YorkNYUSA

We detail some of the understudied aspects of the flow inside and around the Hexactinellid Sponge Euplectella *** leveraging the flexibility of the Lattice Boltzmann Method,High Performance Computing simulations are performed to dissect the complex conditions corresponding to the actual environment at the bottom of the ocean,at depths between 100 and 1,000 *** large-scale simulations unveil potential clues on the evolutionary adaptations of these deep-sea sponges in response to the surrounding fluid flow,and they open the path to future investigations at the interface between physics,engineering and biology.

关键词： Lattice Boltzmann method fluid-structure interaction sponge hydrodynamics high performance computing complex boundary conditions

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Hydrodynamic interactions between rough surfaces

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Physical Review Fluids 2024年第3期9卷 L032301-L032301页

作者： Ehud Yariv Rodolfo Brandão David K. Wood Hannah Szafraniec John M. Higgins Parisa Bazazi Philip Pearce Howard A. Stone Department of Mechanical and Aerospace Engineering Princeton University Princeton New Jersey 08544 USA Department of Mathematics Technion — Israel Institute of Technology Haifa 32000 Israel Department of Biomedical Engineering University of Minnesota Minneapolis Minnesota 55455 USA Center for Systems Biology and Department of Pathology Massachusetts General Hospital and Department of Systems Biology Harvard Medical School Boston Massachusetts 02114 USA Colorado School of Mines Golden Colorado 80401 USA Department of Mathematics University College London London WC1H 0AY United Kingdom

In the study of particle suspensions, away from the jamming threshold, it is common to interpret the effective viscosity in terms of the volume fraction, neglecting roughness effects. Here we show that particle roughness can significantly modify viscous dissipation in configurations that represent fixed volume-fraction conditions. We derive a hydrodynamic model for the forced interaction of a two-dimensional particle, where roughness is represented by a periodic corrugation, with an adjacent wall. In particular, we address the limit of small nominal particle-wall separation, with the corrugation amplitude comparable with said separation. A lubrication analysis provides the rectilinear and angular velocities of the particle as functions of the instantaneous angular configuration. The particle may either translate while rotating or become “locked” in a specific phase and translate without rotation. The time-averaged rectilinear velocity, which is the object of interest, is a purely geometric quantity, obtained without the need to address any time dynamics.

关键词： Fluid-particle interactions Suspensions

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The Role of Porosity in Improving the Biomechanical Performance of Total Knee Arthroplasty: A Finite Element Perspective

The Role of Porosity in Improving the Biomechanical Performa...

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Iranian Conference of biomedical engineering (ICBME)

作者： Farid Rashidi Mohadese Rajaeirad Mohsen Bahrami Soroush Sadeghnejad Department of Mechanical Engineering Amirkabir University of Technology Tehran Iran Department of Biomedical Engineering Faculty of Engineering University of Isfahan Isfahan Iran

ISBN: (数字)9798331529710

ISBN: (纸本)9798331529727

Total Knee Arthroplasty (TKA) aims to relieve knee dysfunction caused by osteoarthritis or injury, but its success is hindered by implant failure. This study examines the impact of implant porosity on the biomechanical performance of TKA implants. We utilized Finite Element Analysis (FEA) to evaluate the biomechanical performance of porous TKA implants under realistic loading conditions. A 3D patient-specific model of a knee joint was created from CT scans of a 35-year-old male. The commercial TKA CR model (Sigma ${ }^{\circledR}$ FixedBearing Knees - DePuy Synthes) was designed using CATIA software. The bone models were assigned inhomogeneous material properties based on Hounsfield units from CT images. The FEA model included 66680 nodes and 399427 elements for bone tissues and 30996 nodes, 9890 linear hexahedral, and 129860 linear tetrahedral elements for implant components. The results revealed that implant porosity significantly affects stress distribution. Implants with $\mathbf{2 5 \%}$ porosity demonstrated optimal stress distribution, reducing von Mises stress in both femoral and tibial components. Higher porosity levels (e.g., 60%) risked implant failure due to reduced compressive yield strength. Porosity in TKA implants enhances biomechanical performance by improving stress distribution and reducing stress shielding. A $\mathbf{2 5 \%}$ porosity level is optimal, balancing biomechanical benefits and structural integrity, potentially leading to better patient outcomes and longer implant lifespans.

关键词： Biomechanics Three-dimensional displays Biological system modeling Computed tomography Implants Bones Finite element analysis Knee replacement Stress Load modeling

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Phasor-FSTM:a new paradigm for multicolor super-resolution imaging of living cells based on fluorescence modulation and lifetime multiplexing

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Light(Science & Applications) 2025年第1期14卷 258-270页

作者： Luwei Wang Yue Chen Jiaqing Guo Xiaoyu Weng Wei Yan Jun Song Tong Ye Junle Qu Center for Biomedical Optics and Photonics&College of Physics and Optoelectronic Engineering Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong ProvinceShenzhen UniversityShenzhen518060China The Photonics Center of Shenzhen University Shenzhen UniversityShenzhen518060China Department of Bioengineering CU-MUSC Bioengineering ProgramClemson UniversityCharlestonSouth Carolina29634USA

Multicolor microscopy and super-resolution optical microscopy are two widely used techniques that greatly enhance the ability to distinguish and resolve structures in cellular *** methods have individually transformed cellular imaging by allowing detailed visualization of cellular and subcellular structures,as well as organelle ***,integrating multicolor and super-resolution microscopy into a single method remains challenging due to issues like spectral overlap,crosstalk,photobleaching,phototoxicity,and technical *** challenges arise from the conflicting requirements of using different fluorophores for multicolor labeling and fluorophores with specific properties for super-resolution *** propose a novel multicolor super-resolution imaging method called phasor-based fluorescence spatiotemporal modulation(Phasor-FSTM).This method uses time-resolved detection to acquire spatiotemporal data from encoded photons,employs phasor analysis to simultaneously separate multiple components,and applies fluorescence modulation to create super-resolution ***-FSTM enables the identification of multiple structural components with greater spatial accuracy on an enhanced laser scanning confocal microscope using a single-wavelength *** demonstrate the capabilities of Phasor-FSTM,we performed two-color to four-color super-resolution imaging at a resolution of~λ/5 and observed the interactions of organelles in live cells during continuous imaging for a duration of over 20 *** method stands out for its simplicity and adaptability,seamlessly fitting into existing laser scanning microscopes without requiring multiple laser lines for excitation,which also provides a new avenue for other super-resolution imaging technologies based on different principles to build multi-color imaging systems with the requirement of a lower budget.

关键词： resolution lifetime simplicity

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Thermogravimetric Analysis and Tensile Testing of PEEK structures Fabricated via Extrusion and 3D Printing

Thermogravimetric Analysis and Tensile Testing of PEEK struc...

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International Conference on Biosignals, Images and Instrumentation (ICBSII)

作者： Ravi Tiwari Somnath Bhattacharya Sanjeev Kumar M Marieswaran Mechanical Engineering Department National Institute of Technology Raipur India Department of Biomedical Engineering National Institute of Technology Raipur India

ISBN: (数字)9798331513863

ISBN: (纸本)9798331513870

Polyether ether Ketone (PEEK) is a thermoplastic polymer with superior chemical resistance, thermal stability, flame retardancy and mechanical properties. It is also known for its biocompatibility. The mechanical properties of PEEK are in the similar range as that of human bone making it preferable over metals for orthopaedic implant fabrication. PEEK is also FDA-approved material for orthopaedic applications. Additive manufacturing has emerged as a efficient method to fabricate complex and customizable structures. The process of extrusion of PEEK into a filament aids in additive manufacturing and hence extrusion of PEEK and 3D printing has to optimized for obtaining desired properties. This work reports the extrusion of PEEK filament from pellets and fabrication by 3D printing. The thermal and mechanical properties of extruded filament and 3D-printed dog bone samples were evaluated respectively. The filament of 1.75 mm diameter was produced by extruding PEEK pellets in an extruder with 4-zone heaters at temperatures above the melting point of PEEK. The extruded filament in a spool was immediately used to 3D print the dog bone geometry (as per ASTM D638 Type 1) using the fused filament fabrication (FFF) using appropriate printing parameters. Tensile testing of dog bone samples showed Ultimate Tensile Strength of $44.93 \pm 0.41$ MPa and Young’s Modulus of $1.50 \pm 0.07 \text{GPa}$. Thermogravimetric Analysis (TGA) was also performed (as per ASTM E 1131) on the extruded filament, evaluating the thermal decomposition of PEEK. TGA characterization aids in understanding the mechanism of decomposition of the substance based on mass loss as a function of temperature for a given heating rate. TGA showed that extruded filament was thermally stable up to $600^{\circ} \text{C}$ above which the mass started to decompose rapidly till $800^{\circ} \text{C}$. To summarize, PEEK was successfully extruded and 3D printed. The tensile and thermal properties were evaluated and report

关键词： Fabrication Temperature Thermal decomposition Dogs Three-dimensional printing Bones mechanical factors Thermal analysis Thermal stability Testing

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Identification and Analysis of Alzheimer's Disease using DenseNet Architecture with Minimum Path Length Between Input and Output Layers 2

Identification and Analysis of Alzheimer's Disease using Den...

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2nd International Conference on Smart Technologies, Communication and Robotics, STCR 2022

作者： Deepa, D. Raj, M. Sundar Gowthami, S. Hemalatha, K. Poongodi, C. Thangavel, P. Bannari Amman Institute of Technology Department of Biomedical Engineering Sathyamangalam India Bannari Amman Institue of Technology Department of Electronics and Communication Engineering Sathyamangalam India Kongu Engineering College Department of Mechanical Engineering Perundurai India

ISBN: (纸本)9781665460477

Alzheimer's Disease is a neurological brain disorder that damages the cells in brain and reduce the ability of the brain from the regular activities. It is a representation of the most common form of adult-onset dementias. Earlier detection of Alzheimer's disease can be more helpful in predetermining the symptomatic conditions of patients suffering with this problem. By diagnosing the consequences of this disease, with the help of medical scan images, it would be more useful in classifying the patients whether they are suffering from this deadly disease. Machine Learning tends to be more beneficial in diagnosing diseases and implementation of this technique, to Magnetic Resonance Imaging (MRI) inputs in identification of Alzheimer's disease, resulted in faster prediction of the disease and in the contribution of the evolution of the disease. Carrying out this technique, it is possible to diagnose and predict the individual dementia of adults by screening data of Alzheimer's disease and inducing Machine Learning classifiers. This work focuses on building an evolving framework to detect Alzheimer's disease efficiently with the help of neuroimaging technologies and prediction at a very earlier stage by using the data stacked up for Alzheimer's disease patients. © 2022 IEEE.

关键词： Magnetic resonance imaging

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Machine Learning Approach for Thermal Characteristics and Improvement of Heat Transfer of Nanofluids—A Review 1st

Machine Learning Approach for Thermal Characteristics and Im...

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1st International Conference on Machine Intelligence for Research and Innovations, MAiTRI 2023

作者： Patel, Harishchandra Kumar Singh, Dwesh Prakash Verma, Om Kadian, Sachin Department of Mechanical Engineering Dr. B.R Ambedkar National Institute of Technology Jalandhar India Department of Instrumentation and Control Engineering Dr. B.R Ambedkar National Institute of Technology Jalandhar India Joint Department of Biomedical Engineering at the University of North Carolina and North Carolina State University RaleighNC United States

ISBN: (纸本)9789819981342

Machine learning (ML) provides an array of methodologies for understanding many challenging obstacles in multiple domains, mostly the discipline of heat transfer and thermal systems. In nanofluid investigations about thermophysical attribute prediction and thermo-hydrodynamic performance testing, machine learning methods would be particularly helpful. The goal of the current review is to examine the advantages and uses of various machine learning algorithms applied in nanofluid-based vapour compression refrigeration systems and to highlight recent advancements in this field. The rapid development of nanofluids is being driven by a record amount of data from experiments, field observations, and extensive simulations at multiple space and time scales. There are many ways to collect data-related information from machine learning that can be used to comprehend the use of nanofluids. The importance of ML in assessing the thermophysical characteristics of nanofluid is in-depth highlighted. The forecasting of thermophysical characteristics and heat transfer rate using data-driven machine learning techniques will be helpful in finding the most important aspects in nanofluid research. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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