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This study aims to explore the evolving field of physics-informed neural networks (PINNs) through an analysis of 996 records retrieved from the Web of Science (WoS) database from 2019 to 2022.

WoS database was analyzed for PINNs using an inhouse python code. The author’s collaborations, most contributing institutes, countries and journals were identified. The trends and application categories were also analyzed.

The papers were classified into seven key domains: Fluid Dynamics and computational fluid dynamics (CFD); Mechanics and Material Science; Electromagnetism and Wave Propagation; Biomedical Engineering and Biophysics; Quantum Mechanics and Physics; Renewable Energy and Power Systems; and Astrophysics and Cosmology. Fluid Dynamics and CFD emerged as the primary focus, accounting for 69.3% of total publications and witnessing exponential growth from 22 papers in 2019 to 366 in 2022. Mechanics and Material Science followed, with an impressive growth trajectory from 3 to 65 papers within the same period. The study also underscored the rising interest in PINNs across diverse fields such as Biomedical Engineering and Biophysics, and Renewable Energy and Power Systems. Furthermore, the focus of the most active countries within each application category was examined, revealing, for instance, the USA’s significant contribution to Fluid Dynamics and CFD with 319 papers and to Mechanics and Material Science with 66 papers.

This analysis illuminates the rapidly expanding role of PINNs in tackling complex scientific problems and highlights its potential for future research across diverse domains.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This study aims to focuse on the flow behavior of a specific nanofluid composed of blood-based iron oxide nanoparticles, combined with motile gyrotactic microorganisms, in a ciliated channel with electroosmosis.

This study applies a powerful mathematical model to examine the combined impacts of bio convection and electrokinetic forces on nanofluid flow. The presence of cilia, which are described as wave-like motions on the channel walls, promotes fluid propulsion, which improves mixing and mass transport. The velocity and dispersion of nanoparticles and microbes are modified by the inclusion of electroosmosis, which is stimulated by an applied electric field. This adds a significant level of complexity.

To ascertain their impact on flow characteristics, important factors such as bio convection Rayleigh number, Grashoff number, Peclet number and Lewis number are varied. The results demonstrate that while the gyrotactic activity of microorganisms contributes to the stability and homogeneity of the nanofluid distribution, electroosmotic forces significantly enhance fluid mixing and nanoparticle dispersion. This thorough study clarifies how to take advantage of electroosmosis and bio convection in ciliated micro channels to optimize nanofluid-based biomedical applications, such as targeted drug administration and improved diagnostic processes.

First paper discussed “Numerical Computation of Cilia Transport of Prandtl Nanofluid (Blood-Fe₃O₄) Enhancing Convective Heat Transfer along Micro Organisms under Electroosmotic effects in Wavy Capillaries”.

The main purpose of this study is to analyze the heat transfer phenomena in a dynamically bulging enclosure filled with Cu-water nanofluid. This study examines the convective heat transfer process induced by a bulging area considered a heat source, with the enclosure's side walls having a low temperature and top and bottom walls being treated as adiabatic. Various factors, such as the Rayleigh number (Ra), nanoparticle volume fraction, Darcy effects, Hartmann number (Ha) and effects of magnetic inclination, are analyzed for their impact on the flow behavior and temperature distribution.

The finite element method (FEM) is employed for simulating variations in flow and temperature after validating the results. Solving the non-linear partial differential equations while incorporating the modified Darcy number (10⁻³ ≤ Da ≤ 10⁻¹), Ra (10³ ≤ Ra ≤ 10⁵) and Ha (0 ≤ Ha ≤ 100) as the dimensionless operational parameters.

This study demonstrates that in enclosures with dynamically positioned bulges filled with Cu-water nanofluid, heat transfer is significantly influenced by the bulge location and nanoparticle volume fraction, which alter flow and heat patterns. The varying impact of magnetic fields on heat transfer depends on the Rayleigh and Has.

The geometry configurations employed in this research have broad applications in various engineering disciplines, including heat exchangers, energy storage, biomedical systems and food processing.

This research provides insights into how different shapes of the heated bulging area impact the hydromagnetic convection of Cu-water nanofluid flow in a dynamically bulging-shaped porous system, encompassing curved surfaces and various multi-physical conditions.

Several graphs, streamlines, isotherms and 3D plots are illustrated to enlighten the noteworthy fallouts of the investigation. Embedding flow factors for velocity, induced magnetic field and temperature have been determined using parametric analysis.

Ternary hybrid nanofluids has outstanding hydrothermal performance compared to classical mono nanofluids and hybrid nanofluids owing to the presence of triple tiny metallic particles. Ternary hybrid nanofluids are considered as most promising candidates in solar energy, heat exchangers, electronics cooling, automotive cooling, nuclear reactors, automobile, aerospace, biomedical devices, food processing etc. In this work, a ternary hybrid nanofluid flow that contains metallic nanoparticles over a wedge under the prevalence of solar radiating heat, induced magnetic field and the shape factor of nanoparticles is considered. A ternary hybrid nanofluid is synthesized by dispersing iron oxide (Fe3O4), silver (Ag) and magnesium oxide (MgO) nanoparticles in a water (H₂O) base fluid. By employing similarity transformations, we can convert the governing equations into ordinary differential equations and then solve numerically by using the Runge–Kutta–Fehlberg approach.

There is no fund for the research work.

This kind of study may be used to improve the performance of solar collectors, solar energy and solar cells.

This investigation unfolds the hydrothermal changes of radiative water-based Fe₃O₄-Ag-MgO-H₂O ternary hybrid nanofluidic transport past a static and moving wedge in the presence of solar radiating heating and induced magnetic fields. The shape factor of nanoparticles has been considered in this study.

The purpose of this study is therefore to detail an additive manufacturing process for printing TiD parts for implant applications. Titanium–diamond (TiD) is a new composite that provides biocompatible three-dimensional multimaterial structures. Thus, the authors report a powder-deposition and print optimization strategy to overcome the dual-functionality gap by printing bulk TiD parts. However, despite favorable customization outcomes, relatively few additive manufacturing (AM) feedstock powders offer the biocompatibility required for medical implant and device technologies.

AM offers a platform to fabricate customized patient-specific parts. Developing feedstock that can be 3D printed into specific 3D structures while providing a favorable interface with the human tissue remains a challenge. Using laser metal deposition, feedstock powder comprising diamond and titanium was co-printed into TiD parts for mechanical testing to determine optimal manufacturing parameters.

TiD parts were fabricated comprising 30% and 50% diamond. The composite powder had a Hausner ratio of 1.13 and 1.21 for 30% and 50% TiD, respectively. The flow analysis (Carney flow) for TiD 30% and 50% was 7.53 and 5.15 g/s. The authors report that the printing-specific conditions significantly affect the integrity of the printed part and thus provide the optimal manufacturing parameters for structural integrity as determined by micro-computed tomography, nanoindentation and biocompatibility of TiD parts. The hardness, ultimate tensile strength and yield strength for TiD are 4–6 GPa (depending on build position), 426 MPa and 375 MPa, respectively. Furthermore, the authors show that increasing diamond composition to 30% results in higher osteoblast viability and lower bacteria count than titanium.

In this study, the authors provide a clear strategy to manufacture TiD parts with high integrity, performance and biocompatibility, expanding the material feedstock library and paving the way to customized diamond implants. Diamond is showing strong potential as a biomedical material; however, upscale is limited by conventional techniques. By optimizing AM as the avenue to make complex shapes, the authors open up the possibility of patient-specific diamond implant solutions.

In this study, we investigate the effects of an extended ternary hybrid Tiwari and Das nanofluid model on ethylene glycol flow, with a focus on heat transfer. Using the Cross non-Newtonian fluid model, we explore the heat transfer characteristics of this unique fluid in various applications such as pharmaceutical solvents, vaccine preservatives, and medical imaging techniques.

Our investigation reveals that the flow of this ternary hybrid nanofluid follows a laminar Cross model flow pattern, influenced by heat radiation and occurring around a stretched cylinder in a porous medium. We apply a non-similarity transformation to the nonlinear partial differential equations, converting them into non-dimensional PDEs. These equations are subsequently solved as ordinary differential equations (ODEs) using MATLAB’s bvp4c tools. In addition, the magnetic number in this study spans from 0 to 5, volume fraction of nanoparticles varies from 5% to 10%, and Prandtl number for EG as 204. This approach allows us to examine the impact of temperature on heat transfer and distribution within the fluid.

Graphical depictions illustrate the effects of parameters such as the Weissenberg number, porous parameter, Schmidt number, thermal conductivity parameter, Soret number, magnetic parameter, Eckert number, Lewis number, and Peclet number on velocity, temperature, concentration, and microorganism profiles. Our results highlight the significant influence of thermal radiation and ohmic heating on heat transmission, particularly in relation to magnetic and Darcy parameters. A higher Lewis number corresponds to faster heat diffusion compared to mass diffusion, while increases in the Soret number are associated with higher concentration profiles. Additionally, rapid temperature dissipation inhibits microbial development, reducing the microbial profile.

The numerical analysis of skin friction coefficients and Nusselt numbers in tabular form further validates our approach. Overall, our findings demonstrate the effectiveness of our numerical technique in providing a comprehensive understanding of flow and heat transfer processes in ternary hybrid nanofluids, offering valuable insights for various practical applications.

The purpose of this study is to consider the dynamics of Casson–Walters-B alongside gyrotactic microorganisms through the investigation of antibacterial and antiviral mechanisms using silver nanoparticles (AgNPs). The Casson fluid and Walters-B flow from the penetrable plate to the boundary layer (BL) in this analysis. The antiviral and antibacterial mechanisms of AgNPs were separately examined in this study.

The physical phenomenon of this problem was analyzed with partial differential equations (PDEs). These PDEs were changed into ordinary differential equations (ODEs) to further explain the significance of pertinent control parameters. The set of equations is solved numerically by implementing the spectral relaxation method (SRM). SRM is a numerical technique that uses the basic techniques of Gauss-Seidel. The SRM first decouples and linearizes the coupled nonlinear set of ODEs.

In this finding, it is found that the thermal radiation parameter produces higher temperatures within the BL to cause blockage in viral replications. It is found in this study that the magnetic parameter assisted in disinfection by lowering the antiviral and antibacterial mechanisms within the momentum BL. This is evident from the reduction in the velocity and momentum BL as the Casson and Walters-B parameters increase.

This paper is unique because it examined the antiviral and antibacterial mechanisms by using AgNPs. Prior to the authors’ understanding, no study of this type was conducted in the past. To the best of the authors’ knowledge, no other study in the past has examined the mechanisms of antiviral and antibacterial separately within the BL. Also, the simultaneous flow of Casson (honey) and Walters-B fluids were considered flowing through the vertical porous plate to the BL.

This study aims to develop a simplified bioink preparation method that can be applied to most hydrogel bioinks used in extrusion-based techniques.

The parameters of the bioprinting process significantly affect the printability of the bioink and the viability of cells. In turn, the bioink formulation and its physicochemical properties may influence the appropriate range of printing parameters. In extrusion-based bioprinting, the rheology of the bioink affects the printing pressure, cell survival and structural integrity. Three concentrations of alginate-gelatin hydrogel were prepared and printed at three different flow rates and nozzle gauges to investigate the print parameters. Other characterizations were performed to evaluate the hydrogel structure, printability, gelation time, swelling and degradation rates of the bioink and cell viability. An experimental design was used to determine optimal parameters. The analyses included live/dead assays, rheological measurements, swelling and degradation.

The experimental design results showed that the hydrogel flow rate substantially influenced printing accuracy and pressure. The best hydrogel flow rate in this study was 10 ml/h with a nozzle gauge of 18% and 4% alginate. Three different concentrations of alginate-gelatin hydrogels were found to exhibit shear-thinning behavior during printing. After seven days, 46% of the structure in the 4% alginate-5% gelatin sample remained intact. After printing, the viability of skin fibroblast cells for the optimized sample was 91%.

This methodology offers a straightforward bioink preparation method applicable to the majority of hydrogels used in extrusion-based procedures. This can also be considered a prerequisite for cell printing.

The paper aims to fabricate shape memory composites using polylactic acid (PLA) matrix and graphite. Shape memory polymers are a promising family of materials for biomedical applications because of their favourable mechanical properties, fast reactions and good biocompatibility. For most SMPs, however, achieving controllable sequential shape change is challenging.

In the present work, 4D printing technology is used to fabricate shape memory composites using polylactic acid (PLA) matrix and graphite. A comparative study of pure PLA and graphite’s different weight % composition has been done.

By carefully managing the deformation state, PLA with graphite shape memory composites produced controllable sequential deformation with an amazing shape memory effect. Surface morphology, thermal properties, melt flow index and shape recovery tests have all been carried out to assess the qualities of manufactured samples.

This is a one-of-a-kind to fabricate shape memory composites using graphite and a PLA matrix. Thus, this research attempts to deliver the possible use of PLA/graphite composites fabricated using 4D printing in robotics and biomedical devices.