4D bioprinting is the next-generation additive manufacturing-based fabrication platform employed to construct intricate, adaptive, and dynamic soft and hard tissue structures as well as biomedical devices. It is achieved by using stimuli-responsive materials, especially shape memory polymers (SMPs) and hydrogels, which possess desirable biomechanical characteristics. In the last few years, numerous efforts have been made by 4D printing community to develop novel stimuli-responsive polymeric materials by considering their biomedical perspective. This review presents an up-to-date overview of 4D bioprinting technology incorporating bioprinting materials, functionalities of biomaterials as well as the focused approach towards different tissue engineering and regenerative medicine (TERM) applications. It includes bone, cardiac, neural, cartilage, drug delivery systems, and other high-value biomedical devices. This review also addresses current limitations and challenges in 4D bioprinting technology to provide a basis for foreseeable advancements for TERM applications that could be helpful for their successful utilization in clinical settings. Abbreviations
Injection molding is one of the most widely employed manufacturing processes for the mass production of polymer products, owing to its high efficiency, reproducibility, and versatility [...]
In the past decade, organ-on-chip (OoC) systems have gained significant attention as advanced platforms for replicating the physiological microenvironments of various organs. These microfluidic devices allow in vitro cell cultures at the microscale, integrating biophysical and biochemical cues that traditional cell culture models cannot reproduce. A critical aspect of their functionality is sterilization, which is necessary to eliminate bacterial contamination. However, conventional sterilization methods often fail to remove bacterial endotoxins, such as lipopolysaccharides (LPS) from Gram-negative bacteria. These endotoxins are potent pyrogens that can induce fever and profoundly alter cellular behavior, thereby compromising the reliability and accuracy of OoC models. This issue is particularly challenging for OoC systems fabricated with hydrophobic materials like polydimethylsiloxane (PDMS), which readily adsorb endotoxins.In this study, we developed an analytical method to quantify endotoxin levels in PDMS-based microfluidic devices using a Limulus Amoebocyte Lysate (LAL) assay. We tested two groups of devices: those made with PDMS from a batch opened for over a year (“1-year-old PDMS”), and others made with PDMS from a batch opened for just one month (“1-month-old PDMS”). We also compared contamination levels after 1 h and 1 week post-sealing by oxygen plasma treatment. Storage time (period from sealing to testing for endotoxin) displayed critical for contamination level, revealing that oxygen plasma treatment is effective in reducing endotoxin from PDMS surfaces. This result was also confirmed by FTIR analysis.Our findings emphasize the critical need for rigorous contamination control in the manufacturing of OoC systems to ensure they are not only sterile but also endotoxin-free. Achieving this dual standard is essential for maintaining the reliability and performance of these innovative platforms in biomedical research and therapeutic development.
Magnetoactive elastomer is a functional material whose properties are controlled by the parameters of the external magnetic field. A modifier that creates ordered structures with controlled nanoscale morphology is capable of intensifying the ability of a material to transfer charge.The modifier was obtained by dissociating C60 fullerene in eugenol at an elevated temperature in a water bath for 6 h. The fullerene content in the samples was 3.5 g/L. The preparation of 3 groups of modifier solutions to study their properties took 60 days. Two groups included solutions obtained through diffuse dissolution, one group - with an additional mechanical action. A study of rheological, optical and electrical conductivity properties was carried out to assess changes in the structure of the solutions. During the studies, thixotropic deposition of the air capsule was noted in some samples. To describe the hydraulic size of deposited objects, a nonlinear dependence is formulated. Spectral analysis of the solutions revealed differences in the optical properties of the samples obtained by various methods. The optical activity of those that have not been subjected to an additional impact is increasing over time. This causes a change in the solution structure and the conformation of the complexes of the solvent molecular structure and C60. Ultimately, this leads to noticeable changes in electrical conductivity properties. The change in the resistivity values of some samples relative to the solvent is associated with the influence of the formed structural aggregation of fullerene molecules, as well as with several types of polarization interactions. Classification of the influence of conformational and electronic characteristics of solvent molecules made it possible to systematize the factors influencing the solvent dissolving ability. The formation of non-centrosymmetric structures in solutions in the form of fractal aggregates of dissociated fullerene was noted. The approach to describing the model for the formation of a cluster structure is based on the principle of increasing the fractional dimension during the dissociation process. Aggregation, limited by diffusion processes, proceeds to limit the reaction rate; at the final stage, spatial limitation dominates.Studying the molecular dynamics of aggregates formation in various solutions allows improved understanding the principles of a fractal structure formation. The results obtained will be used in the development of conductive functional polymers with controlled properties.
Polymers and polymer manufacture, Engineering (General). Civil engineering (General)
Jinyoung Kim, Kyeongmin Hong, Yong-Seok Choi
et al.
In this study, we investigate the multiaxial mechanical behavior of thermosetting epoxy polymers and explore the asymmetry between tension and compression in their yield surfaces at the molecular level using molecular dynamics simulations, complemented by experimental validation through polymer synthesis. After constructing an atomistic-scale amorphous epoxy system based on molecular dynamics simulations, we derived equivalent stress–strain curves and yield surfaces as functions of the degree of crosslinking through biaxial deformation analysis. The results show that increasing the degree of crosslinking leads to an increase in equivalent stress in all loading directions, resulting in an expansion of the yield surface. Notably, a more accelerated expansion of the yield surface in the biaxial compression direction was observed at higher degrees of crosslinking, which is attributed to a deformation mechanism that more effectively accommodates stress in this loading direction. This unique deformation behavior is attributed to high non-bonded stress arising from reduced polymer chain mobility by crosslinking effect. To experimentally validate the deformation mechanisms, epoxy polymer samples were synthesized, and uniaxial tensile and plane-strain compression (PSC) tests were conducted to obtain stress–strain profiles and yield surfaces according to different degrees of cure. These results provide fundamental insights into the distinct mechanical properties of polymer materials, such as the asymmetry of the yield surface, by revealing their behavior at the molecular level.
We study the effects of polymer additives on pseudoturbulence induced by a swarm of bubbles rising in a quiescent fluid. We find that, beyond a critical polymer concentration, the energy spectra of velocity fluctuations in bubble-induced turbulence decay more steeply with respect to the wavenumber $k$. This new scaling is significantly steeper than the classical $k^{-3}$ scaling observed for bubbles in Newtonian fluids; it is independent of the gas volume fraction in the inertial limit and occurs within the length scales between the bubble wake length and the bubble diameter. Furthermore, we provide strong evidence that the presence of polymers enhances the coherence of the flow, highlighting the significant role of polymer additives in modifying the characteristics of pseudoturbulence.
A solvable model of directed polymer with matrix-valued disorder is introduced in arXiv:2203.14868. The disorder is made of $d\times d$ inverse-Wishart random matrices, so that the model nicely generalizes the well-studied log-gamma polymer, recovered when $d=1$. Much of the features of the log-gamma polymer seem to have analogues for higher $d$, although the integrability needs to be better understood. In this paper, we introduce stationary inverse-Wishart polymer models on a quadrant or a strip of $\mathbb Z^2$. In each setting, we identify stationary measures, characterized explicitly in terms of random walks with inverse-Wishart increments in special cases, or more complicated two-layer Gibbs measures for generic choices of boundary parameters. We also make conjectures about asymptotics of the free energy, and explain important differences between matrix-valued polymer models and their scalar counterpart, due to non-commutativity.
The advancement of polymer informatics has been significantly propelled by the integration of machine learning (ML) techniques, enabling the rapid prediction of polymer properties and expediting the discovery of high-performance polymeric materials. However, the field lacks a standardized workflow that encompasses prediction accuracy, uncertainty quantification, ML interpretability, and polymer synthesizability. In this study, we introduce POINT$^{2}$ (POlymer INformatics Training and Testing), a comprehensive benchmark database and protocol designed to address these critical challenges. Leveraging the existing labeled datasets and the unlabeled PI1M dataset, a collection of approximately one million virtual polymers generated via a recurrent neural network trained on the realistic polymers, we develop an ensemble of ML models, including Quantile Random Forests, Multilayer Perceptrons with dropout, Graph Neural Networks, and pretrained large language models. These models are coupled with diverse polymer representations such as Morgan, MACCS, RDKit, Topological, Atom Pair fingerprints, and graph-based descriptors to achieve property predictions, uncertainty estimations, model interpretability, and template-based polymerization synthesizability across a spectrum of properties, including gas permeability, thermal conductivity, glass transition temperature, melting temperature, fractional free volume, and density. The POINT$^{2}$ database can serve as a valuable resource for the polymer informatics community for polymer discovery and optimization.
Lijie Ding, Chi-Huan Tung, Jan-Michael Y. Carrillo
et al.
We develop Monte Carlo simulations for uniformly charged polymers and machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, which can be obtained from small-angle scattering experiments. The polymer is modeled as a chain of fixed-length bonds, where the connected bonds are subject to bending energy, and there is also a screened Coulomb potential for charge interaction between all joints. The bending energy is determined by the intrinsic bending stiffness, and the charge interaction depends on the interaction strength and screening length. All three contribute to the stiffness of the polymer chain and lead to longer and larger polymer conformations. The screening length also introduces a second length scale for the polymer besides the bending persistence length. To obtain the inverse mapping from the structure factor to these polymer conformation and energy-related parameters, we generate a large data set of structure factors by running simulations for a wide range of polymer energy parameters. We use principal component analysis to investigate the intra-polymer structure factors and determine the feasibility of the inversion using the nearest neighbor distance. We employ Gaussian process regression to achieve the inverse mapping and extract the characteristic parameters of polymers from the structure factor with low relative error.
Abstract Polyvinyl chloride (PVC) is one of the most important commercial plastics but it is thermally unstable at processing temperatures. Therefore, heat stabilizers are widely used to safeguard by improving resistance of PVC products at high temperature. But most of them are a highly toxic that can cause severe health issues in humans and harmful to the environment. In the present study mixed of calcium/zinc stearate heat stabilizer and green Expandable graphite (EG) is prepared via hydrothermal treatment using additives of nontoxic, environmental protection. The characteristics of the thermal stability of poly vinyl chloride can be investigated by Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) will be used to examine structure of the heat stabilizers, A universal testing equipment will be used to determine the mechanical properties and thermal gravimetric analysis (TGA). From TGA results the weight loss was 43.49% at 342°C for sample with Ca/Zn‐ stearate, while wt loss is 55.87% at 260°C for sample with EG which increase thermal stability. Differential scanning calorimetry affirmed the enhancement of PVC's thermal stability, showing a shift in the glass transition temperature an increase of 67°C. Mechanical tests indicated that samples with EG exhibited higher tensile strength and elongation at break, emphasizing the positive impact on PVC's mechanical properties. The burning test highlighted thermal stability of EG‐containing samples, retaining color and structure even after exposure to 180°C heat. This innovative approach not only enhances thermal stability but also aligns with eco‐friendly principles, making it a promising solution for improving PVC properties. Highlights Ca/Zn‐ stearate, expandable graphite developed by a safe hydrothermal process. Comprehensive analysis indicates improved thermal stability. Safe stabilization of eco‐friendly calcium/zinc, expandable graphite. Effective solution: Eco‐friendly, improved PVC properties. Expandable graphite improved mechanical properties of PVC.
Conjugated polymer fibers can be used to manufacture various soft fibrous optoelectronic devices, significantly advancing wearable devices and smart textiles. Recently, conjugated polymer-based fibrous electronic devices have been widely used in energy conversion, electrochemical sensing, and human-machine interaction. However, the insufficient mechanical properties of conjugated polymer fibers, the difficulty in solution processing semiconductors with rigid main chains, and the challenges in large-scale continuous production have limited their further development in the wearable field. We regulated the pi - pi stacking interactions in conjugated polymer molecules below their critical liquid crystal concentration by applying fluid shear stress. We implemented secondary orientation, leading to the continuous fabrication of anisotropic semiconductor fibers. This strategy enables conjugated polymers with rigid backbones to synergistically enhance the mechanical and semiconductor properties of fibers through liquid crystal spinning. Furthermore, conjugated polymer fibers, exhibiting excellent electrochemical performance and high mechanical strength (600 MPa) that essentially meet the requirements for industrialized preparation, maintain stability under extreme temperatures, radiation, and chemical reagents. Lastly, we have demonstrated logic circuits using semiconductor fiber organic electrochemical transistors, showcasing its application potential in the field of wearable fabric-style logic processing. These findings confirm the importance of the liquid crystalline state and solution control in optimizing the performance of conjugated polymer fibers, thus paving the way for developing a new generation of soft fiber semiconductor devices.
Abstract Biocompatible and bioactive composite scaffolds are essential in bone tissue regeneration because of their bioactivity and multilevel porous assemblies. There is a high demand for three-dimensional (3D) scaffolds to treat bone regeneration defects, trauma, and congenital skeletal abnormalities in the current scenario. The main objective of this review is to collect all the possible information concerning synthetic and natural polymer-Bioglass (BG)-based scaffold materials and systematically present them to summarize the importance and need for these materials. The importance of the bone tissue engineering field has been highlighted. Given the current challenges, a comprehensive description of materials fabrication and patterns in scaffold structures is required. This review also includes the most crucial aspect of this study: why are polymeric materials mixed with BG materials? Individually, both BG and polymeric materials lack specific essential characteristics to enhance the scope of these materials. However, preparing the composites of both ensures the researchers that composites of polymers and BG have improved properties that make them versatile materials for bone tissue engineering applications. This study deals with the individual drawbacks of the inorganic BGs, synthetic polymers, and the deficiencies of natural polymers. This study has also included a brief description of various scaffold fabricating techniques. Finally, this study revealed that by manufacturing and developing novel composite materials-scaffolds bearing the capability to repair, heal, and regenerate accidentally damaged or badly injured bones, many occasional problems can be solved in vivo and in vitro. Moreover, this review demonstrated that natural polymeric materials present many advantages over synthetic bone grafts. Yet, synthetic biomaterials have one additional attractive feature, as they have the flexibility to be designed according to the desired demands. These features make them the best choice for a wide range of bone tissue engineering projects for orthopedic surgeons. Graphical Abstract
Aurelio Bifulco, Angelo Casciello, Claudio Imparato
et al.
In this work, the fire behavior of a sol-gel in-situ hybrid Mg(OH)2-epoxy nanocomposite was investigated and an artificial neural network-based system built on a fully connected feed-forward artificial neural network was developed to predict its heat release capacity. The nanocomposite containing only ∼5 wt% loading of Mg(OH)2 promoted a remarkable decrease in heat release capacity (∼34%) measured by pyrolysis combustion flow calorimetry and in peak of heat release rate (∼37%), and heat release rate (∼29%), as assessed by cone calorimetry, as well as a significant decrease of total smoke release and smoke extinction area about 22 and 5%, respectively, indicating the suitability of Mg(OH)2 as an effective smoke suppressant. The proposed machine learning approach may be used as a promising alternative for a cost- and time-saving prediction of the fire performances of novel flame retardant polymer-based nanocomposites.
Novel dense membranes were fabricated by blending poly(ether-b-amid), Pebax 1657, as the matrix and a poly(amidoamine) dendritic polymer (PAMAM), as the modifier, to evaluate CO2/CH4 gases separation. The study investigated the effects of PAMAM loading, operating pressure, and temperature on gas permeability and CO2/CH4 pair-gas ideal selectivity. All the membranes were characterized using various analytical techniques, including ATR-FTIR, XRD, SEM, FESEM, DSC, AFM, Tensile Analysis, density, Aging, Stability pure gas permeation, and gas solubility tests. FTIR results confirmed the interaction of PEO and PA segments with PAMAM increased polymer crystallinity, which is in agreement with DSC, XRD, and Tensile Analysis results. The membrane containing 3 wt% PAMAM showed the highest FFV which along with facilitated transport of CO2 by PAMAM, resulted in the highest CO2 permeability equal to 56.9 Barrer at 2 bar and 30 °C (more than 30% higher than the neat Pebax membrane at the same condition). Furthermore, the addition of 1 wt% PAMAM to Pebax increased the CO2/CH4 selectivity to 22.8 at 8 bar and 30 °C (more than 78% higher than the neat Pebax membrane at the same condition). Increasing PAMAM loading and applied pressure resulted in the enhancement of gases solubility, and a better ideal selectivity was obtained, correspondingly, Also higher solubility of CO2 compared with CH4 was confirmed by solubility measurements. It was revealed that gas permeability in the membranes was primarily governed by gas solubility rather than diffusivity. The results demonstrate that the modifying Pebax membrane by PAMAM enhances the separation performance with a negligible change against aging and good stability, which confirms potential applications of Pebax/PAMAM membranes in gas separation processes.