Material Parameters Research Articles

A geometric variation method to extract rock strength parameters via uniaxial compression testing

Numerical modelling in rock engineering and mechanics often requires inputting multiple sets of strength parameters, such as the commonly encountered tensile strength, cohesion, and friction angle. Usually, obtaining these parameters requires performing different types of rock mechanics experiments on certain rock specimens, such as tension tests and triaxial tests, which are time-consuming and labor-intensive. Uniaxial compression testing is simpler and requires less demanding equipment. This paper proposes a solution that relies solely on uniaxial compression testing to obtain multiple sets of rock strength parameters. The basic idea is to treat the process of acquiring multiple parameters as a problem of solving a set of mathematical equations. The uniaxial tests with different geometric specimens provide known quantities and the corresponding equations that link these known quantities (e.g., peak loads) with unknown quantities (e.g., strength parameters). We established three-dimensional numerical tests to represent the relationship between input strength parameters and the peak load. By transforming it into an optimization problem, numerical modelling is embedded into the objective function of the optimization algorithm, thereby achieving the automatic extraction of strength parameters. This method is verified through uniaxial compression tests using red sandstone specimens with various geometries. The results show that by changing the geometry of the rock specimens, multiple sets of strength parameters can be obtained. These parameters are successfully used to predict (extrapolate) peak loads of other geometric specimens. This method holds promise for achieving the automated extraction of material parameters for the numerical modelling of rock.

Analysis of Laminated Composite Porous Plate under Sinusoidal Load with Various Boundary Conditions

Bending analysis was carried out for a laminated composite porous plate due to sinusoidal loading with various boundary conditions using improved third-order theory. Zero transverse shear stress provided a free surface at the top and bottom of the plate. Also, the authors developed a finite element formulation based on improved third-order shear deformation theory. To circumvent the C1 continuity requirement associated with improved third-order shear deformation theory, a C0 FE formulation was developed by replacing the out-of-plane derivatives with independent field variables. An in-house FORTRAN code was developed for the bending analysis of the laminated porous plate considering a 2D finite element model. The complete thickness of the plate was covered with different porosity patterns. The impacts of various modulus ratios, boundary conditions, thickness ratios, fiber orientation angles, and material parameters were examined for laminated porous plates. There was an 18.8% reduction in deflection in the case of the square plate as compared to rectangular plates, with a porosity value of 0.1, a thickness ratio of 10, and an orientation angle of 0°/90°/0°. According to the current research, adding porosities causes a relatively greater change in deflection rather than stress, thereby aiding in the development of a lightweight structure.

Impact location of metal structures based on time–frequency image features and deep residual network

Impact location detection plays an important role in the structural health monitoring of metal materials. However, the methods of metal material impact location detection based on physical analysis are often limited by the extraction accuracy of some parameters such as material and structure parameters and time difference calculation. Therefore, this paper develops a deep residual network method for impact location detection, time–frequency characteristic deep residual network (TF-DRN). This method takes the four-channel short-time Fourier transform time–frequency graph as input, uses the unique residual network architecture to automatically extract the advanced features, and then uses the global average pooling layer and the full connection layer to establish the mapping between the advanced features and the impact location, so as to detect the impact location. By introducing regularization and batch normalization, the problems of gradient disappearance and gradient explosion are alleviated, and the generalization and efficiency of impact location detection are further improved. The experimental results show that on an 800 mm × 800 mm × 2.5 mm aluminum plate, the average error of the validation set and the test set are 0.85 cm and 1.33 cm respectively, and the performance of the method is significantly better than that of CNN, ResNet18 and ResNet33 networks.

VENDOR MANAGEMENT IN FACTORIES

PROCEDURE FOR SUPPLIER DEVELOPMENT The Vendor Development Process is carried out by the Purchase Department in close consultation with User Three Department 1) R&D 2) Material Testing 3) QA Department. First Step: - VENDOR REGISTRATION • Any vendor i.e., manufacturer/ authorized agents/distributors of the manufacturer /service providers and firms undertaking job works can be registered the Vendor Development Protocol. To register, the vendor should have GST registration (if applicable). The vendor must maintain an office/ shop/ show room registered in its own name, and should have a bank account wherein payments can be sent directly. • Vendors interested in registration shall submit an application furnishing details of their business and product line. On receipt of the application, they will be issued a vendor development questionnaire. The vendor should submit the duly filled questionnaire, along with their credentials, and details of manufacturing capacity, quality control facilities, past performance, after-sales service, financial background etc. • The duly filled development document received is submitted to the VENDOR DEVELOPMENT COMMITTEE. The Committee consists of Head of User Dept., Head of Material Testing/R & D Dept. & Head of Purchase and has the following powers: ○ after examining the documents and based on the Protocol for Vendor Development of that material, it, can advise the Purchase Department to call for samples for evaluation / plant trial of the material, or call for additional details / clarifications, if required. ○ In case the sample confirms to the specification, the Committee can advise Purchase Department to include the vendor in the list of approved vendors/recommend to issue plant trial order. ○ The Committee can also depute an officer for facility audit, if necessary. ○ Based on the facility audit, and plant trial reports, the Committee can advise the Purchase Department to include the vendor in the list of approved vendors. • Registered firms can be removed from the list of approved firms if they continuously fail to abide by the terms and conditions of the tender / contract or fail to supply goods on time or supply sub-standard items /goods or any false declaration made to company. Suppliers not taking part in the Tender / not supplying to HLL for a continuous period of 5 years will be removed from the list of approved suppliers Second Step: - VENDOR RATING PROCEDURE FOR SUPPLIER RATING Supplier rating is done based on the following criteria. 1) Quality of the product/service 2) Cost rating 3) Adherence to delivery schedule QUALITY RATING (QR) Quality rating comprises of two factors. 1) Inspection rating: Based on value of parameters of materials inspected. 2) Performance rating: Based on value of parameters of materials inspected during performance inspection. PRICE RATING This criterion compares the relationship of the price of vendors with the effective price of those materials. PRICE RATING = (Vendor’s effective price- Effective price of material)/ Effective price of material*100 DELIVERY RATING (DR) Delivery Rating of raw materials is calculated by Purchase Department on the basis of contracts entered into by concerned User Departments as mentioned below: • delivery in time as per schedule: Full credit 2 deliveries after the scheduled date: a grace period of 10 days is given if the material has been dispatched within the delivery date, and the party would get full credit for delivery. • if the material is received within 15 days from the date of delivery mentioned in the Order, a score of 25 % will be deducted. • if the material is delivered between the 16th day and 30th day stipulated in the Order, the score will go down by another 25 % i.e. a total deduction of 50 % • this will continue for every fortnight for the next two fortnights. • the total score thus obtained forms the basis for the grading. Frequency of supplier rating: The vendor rating shall be done on annual basis, or as detailed in Quality Management System (QMS) manual.

Molecular Simulation of Covalent Adaptable Networks and Vitrimers: A Review

Covalent adaptable networks and vitrimers are novel polymers with dynamic reversible bond exchange reactions for crosslinks, enabling them to modulate their properties between those of thermoplastics and thermosets. They have been gathering interest as materials for their recycling and self-healing properties. In this review, we discuss different molecular simulation efforts that have been used over the last decade to investigate and understand the nanoscale and molecular behaviors of covalent adaptable networks and vitrimers. In particular, molecular dynamics, Monte Carlo, and a hybrid of molecular dynamics and Monte Carlo approaches have been used to model the dynamic bond exchange reaction, which is the main mechanism of interest since it controls both the mechanical and rheological behaviors. The molecular simulation techniques presented yield sufficient results to investigate the structure and dynamics as well as the mechanical and rheological responses of such dynamic networks. The benefits of each method have been highlighted. The use of other tools such as theoretical models and machine learning has been included. We noticed, amongst the most prominent results, that stress relaxes as the bond exchange reaction happens, and that at temperatures higher than the glass transition temperature, the self-healing properties are better since more bond BERs are observed. The lifetime of dynamic covalent crosslinks follows, at moderate to high temperatures, an Arrhenius-like temperature dependence. We note the modeling of certain properties like the melt viscosity with glass transition temperature and the topology freezing transition temperature according to a behavior ruled by either the Williams–Landel–Ferry equation or the Arrhenius equation. Discrepancies between the behavior in dissociative and associative covalent adaptable networks are discussed. We conclude by stating which material parameters and atomistic factors, at the nanoscale, have not yet been taken into account and are lacking in the current literature.

Simulation‐Guided Design of Gradient Multilayer Microwave Absorber with Tailored Absorption Performance

AbstractFlexible microwave absorber (MAR), vital in advanced applications such as wearable electronics and precision devices, are highly valued for their lightweight, exceptional electromagnetic waves (EWs), and ease of fabrication. However, optimizing the electromagnetic parameters of microwave absorption materials (MAMs) to enhance absorption ability and expand effective absorption broadband (EAB, reflection loss (RL) <−10 dB) is a considerable challenge. Herein, a permittivity‐attenuation evaluation diagram (PAED) is constructed using parameter scanning based on the Materials Genome Initiative to determine the ideal electromagnetic parameters and thickness, optimize absorption efficiency, and obtain highly efficient absorbers. Guided by the PAED, a multilayer MAR consisting of a “matching‐absorption‐reflection layer” and a dielectric loss gradient aligned with the direction of EWs propagation is developed. This design significantly enhances the EWs penetration and ensures effective absorption, attributed to the well‐matched impedance and attenuation characteristics. As anticipated, the microwave absorption of the absorber (density = 0.063 g cm−3) is optimized, with an RL of −34 dB at d = 4 mm and an EAB covering the entire X‐band (8.2–12.4 GHz). This study presents a novel approach for establishing a material database for MAMs and developing high‐performance absorbers characterized by thinness, lightness, broad operational frequency range, and robust absorption capacity.

Correlation of fabric parameters and characteristic features of granular material behaviour in DEM in constitutive modelling

AbstractThe anisotropic microstructure of granular materials has a profound effect on their macroscopic behaviour and can be characterised using a fabric tensor. To include of fabric in the critical state theory (CST), anisotropic critical state theory (ACST) was proposed by modifying the state parameter $$(\psi )$$ ( ψ ) of CST to a fabric-dependent dilatancy state parameter $$(\upzeta )$$ ( ζ ) . Noteworthy that $$\uppsi$$ ψ showed a very strong correlation with characteristic features (e.g. instability, phase transformation and characteristic state) of macroscopic behaviour and, as a result, it has been adopted in many constitutive models. While $$\upzeta$$ ζ aided the inclusion of fabric in ACST models, the correlation between $$\upzeta$$ ζ and characteristic features has not been evaluated in detail yet, although a large number of works are found on micromechanics and fabric only. In this study, a large number of discrete element method simulations for drained and undrained triaxial were conducted to evaluate the correlation between $$\upzeta$$ ζ and characteristic features. To this purpose, the correlation between stress ratio and both classic and dilatancy state parameter ($$\psi$$ ψ and $$\upzeta$$ ζ ) were studied in important characteristic features (e.g. instability, phase transformation and characteristic state). It was found that this correlation was improved using $$\upzeta$$ ζ which might be due to the inclusion of fabric in our model. This observation is new and significant for inclusion of fabric evolution in constitutive modelling.

Torsion and Combined Torsion-Axial Load Behaviour of Concrete Filled Steel Tube Columns with and without ECC/CFRP Wrap

ABSTRACT Concrete-filled tube columns may experience coupled torsion and axial compression under seismic and wind loading. Fifteen square, rectangular, and circular concrete filled steel/aluminium tube (CFST/CFAT) are tested under pure torsion to understand the behaviour and develop/validate finite element (FE) models. Parametric studies under pure torsion are conducted using FE models to study the effect of geometric (tube cross-section, length, and thickness) and tube/concrete material parameters on torsional strength, stiffness, and tube-concrete composite interaction. FE models are used to study strength, stiffness, and failure modes of CFST columns under combined torsion and axial compression load at various preload levels of axial and torsion. Coupled torsional preloading and subsequent axial load reduce the axial load capacity significantly, while coupled axial preloading and subsequent torsional loading have shown no significant influence on the torsional strength of CFST columns. Implementation of FE models developed for CFST columns with engineered cementitious composite (ECC) and carbon fibre reinforced polymer (CFRP) wraps showed significant enhancement of axial strength and stiffness compared to control (without wrap) even under high torsional preload level. The energy absorption capacity and ductility of the CFRP wrapped CFST column are about 1.38 and 1.1 times higher than its counterpart with ECC wrap of same axial load capacity. Overall, the results suggest that use of both CFRP and ECC wrap is an effective approach to enhance the torsional behaviour and ductility of CFST columns under combined torsion and axial loading conditions. However, high crack resistance and better post-peak ductility of ECC wrapped CFST compared to sudden CFRP rupture failure in CFRP-wrapped counterpart should be taken into consideration for seismic applications.

Molecular strong coupling: evaluating dipole oscillator and cavity field parameters

Abstract In this report we use material parameters to calculate the strength of the expected Rabi splitting for a molecular resonance. As an example we focus on the molecular resonance associated with the C=O bond in a polymer host, specifically the stretch resonance at $\sim$1730 cm$^{-1}$. Two related approaches to modelling the anticipated extent of the coupling are examined, and the results compared with data from experiments available in the literature. The approaches adopted here indicate how material parameters may be used to assess the potential of a material to exhibit strong coupling, and also enable other useful parameters to be derived, including the molecular dipole moment and the vacuum cavity field strength.

Adventitious root culture dyeing and optimisation of dyeing parameters using roots of Gynochthodes umbellata (L.) Razafim and B. Bremer

This study offers a new source of natural dye. Taguchi's design of experiments was used to statistically and optimize the dyeing parameters of different fabrics. The results varied with different fabrics and the optimum conditions for cotton were found to be ultrasonication for 5 min, a material-to-liquor ratio of 10 mL dye to 100 mL water, a temperature of 60 ºC, and a pH of 8. For linen, the optimum values were ultra-sonication for 15 min, 15 mL dye to 100 mL water, pH of 8, and temperature of 80 ºC. Optimum combinations for silk were a temperature of 80 ºC, the material-to-liquor ratio of 20 mL of dye extract to 100 mL water, pH of 8, and ultrasonication for 15 min. The results indicated the commercial viability of dyeing fabrics using this procedure.

Efficient and accurate parameter extraction for quantum-well DFB lasers: a comprehensive approach integrating multiple mathematical models

This study proposes an efficient and accurate method for parameter extraction of quantum well distributed feedback (DFB) lasers by combining the rate equation model, finite element method, transmission matrix method, and traveling wave model (TWM). By fabricating and measuring the companion Fabry-Perot (FP) lasers, material and structural parameters common with the target DFB laser are extracted efficiently. All the intrinsic parameters of the DFB laser are accurately extracted by integrating multiple mathematical models, and the possibility of multiple solutions is avoided. From the extracted parameters, the output characteristics of the DFB laser are simulated using the TWM. The simulation results agree closely with the experimental results, proving the feasibility and accuracy of the proposed method.

Image‐based inertial impact test for viscoelastic constitutive identification: A digital replica for error quantification

AbstractPolymers find widespread use in applications where they are subjected to impact loading. Therefore, understanding the time dependence of their mechanical response is critical to the design of structures subjected to these high strain rate environments. However, characterising these materials on microsecond time scales has proven challenging. Traditional experimental techniques rely on satisfying a number of limiting assumptions and typically do not provide direct measurements of the material parameters. Here, we propose a novel implementation of the image‐based inertial impact (IBII) test to extract viscoelastic constitutive parameters on these microsecond time scales using the stress gauge implementation of the virtual fields method. We validate the experiment using a digital replica approach in which the constitutive parameters are first extracted on a finite element model of an IBII test on a viscoelastic material. The finite element data are then used to synthetically deform computer‐generated grid images, which are then polluted with grey‐level noise to simulate the images that would be captured in a real‐life experiment. These images are processed identically to a physical experiment, and the identification is repeated using the full‐field displacements extracted from the computer‐generated images to determine the ideal processing parameters. Parameter identification was found to strongly depend on the processing parameters used to extract the kinematic fields from full‐field images, emphasising the need for computational validation before attempting a physical experiment to extract constitutive parameters. The IBII experimental method was found to be capable of simultaneously identifying the bulk modulus and the shear modulus along with their associated time constant.

Development and Calibration of a Phenomenological Material Model for Steel-Fiber-Reinforced High-Performance Concrete Based on Unit Cell Calculations

A phenomenological material model has been developed to facilitate the efficient numerical analysis of fiber-reinforced high-performance concrete (HPC). The formulation integrates an elasto-plastic phase-field model for simulating fractures within the HPC matrix, along with a superimposed one-dimensional elasto-plasticity model that represents the behavior of the embedded fibers. The Drucker–Prager plasticity and one-dimensional von-Mises plasticity formulations are incorporated to describe the nonlinear material behavior of both the HPC matrix and the fibers, respectively. Specific steps are undertaken during the development and calibration of the phenomenological material model. In the initial step, an experimental and numerical analysis of the pullout test of steel fibers embedded in an HPC matrix is conducted. This process is used to calibrate the micro-mechanical model based on the elasto-plastic phase-field formulation for fracture. In the subsequent step, virtual experiments based on an ellipsoidal unit cell, also with the resolution of fibers (used as a representative volume element, RVE), are simulated to analyze the impact of fiber–matrix interactions and their physical properties on the effective material behavior of fiber-reinforced HPC. In the final step, macroscopic boundary value problems (BVPs) based on a cuboid are simulated on a single scale using the developed phenomenological material model. The resulting macroscopic stress–strain characteristics obtained from both types of simulations, namely simulations of virtual experiments and macroscopic BVPs, are compared. This comparison is utilized for the calibration of material parameters to obtain a regularized solution and to assess the effectiveness of the presented phenomenological material model.

Region specific anisotropy and rate dependence of Göttingen minipig brain tissue.

Traumatic brain injury is a major cause of morbidity in civilian as well as military populations. Computational simulations of injurious events are an important tool to understanding the biomechanics of brain injury and evaluating injury criteria and safety measures. However, these computational models are highly dependent on the material parameters used to represent the brain tissue. Reported material properties of tissue from the cerebrum and cerebellum remain poorly defined at high rates and with respect to anisotropy. In this work, brain tissue from the cerebrum and cerebellum of male Göttingen minipigs was tested in one of three directions relative to axon fibers in oscillatory simple shear over a large range of strain rates from 0.025 to 250s-1. Brain tissue showed significant direction dependence in both regions, each with a single preferred loading direction. The tissue also showed strong rate dependence over the full range of rates considered. Transversely isotropic hyper-viscoelastic constitutive models were fit to experimental data using dynamic inverse finite element models to account for wave propagation observed at high strain rates. The fit constitutive models predicted the response in all directions well at rates below 100s-1, after which they adequately predicted the initial two loading cycles, with the exception of the 250s-1 rate, where models performed poorly. These constitutive models can be readily implemented in finite element packages and are suitable for simulation of both conventional and blast injury in porcine, especially Göttingen minipig, models.

Thermoplastic polymers as water substitutes

Background. New applications of 3D printing have recently appeared in the fields of radiotherapy and radiology, but the knowledge of many radiological characteristics of the compounds involved is still limited. Therefore, studies are needed to improve our understanding about the transport and interaction of ionizing radiation in these materials. Purpose. The purpose of this study is to perform an analysis of the most important radiation interaction parameters in thermoplastic materials used in Fused Deposition Modeling 3D printing. Additionally, we propose improvements to bring their characteristics closer to those of water and use them as water substitutes in applications such as radiodiagnosis, external radiotherapy, and brachytherapy. Methods. We have calculated different magnitudes as mass linear attenuation, mass energy absorption coefficients, as well as stopping power and electronic density of several thermoplastic materials along with various compounds that have been used as water substitutes and in a new proposed blend. To perform these computations, we have used the XCOM and ESTAR databases from NIST and the EGSnrc code for Montecarlo simulations. Results. From the representation of the calculated interaction parameters, we have been able to establish relationships between their properties and the proportion of certain chemical elements. In addition, studying these same characteristics in different commercial solutions used as substitutes for water phantoms allows us to extrapolate improvements for these polymers. Conclusion. The radiological characteristics of the analyzed thermoplastic materials can be improved by adding some chemical elements with atomic numbers higher than oxygen and by using polyethylene in new blends.

Optimization of femtosecond laser processing parameters of SiC using ANN-NSGA-II

Abstract In the field of femtosecond laser machining, it is essential to select the appropriate process parameters to obtain near thermal damage-free and high efficient machining of SiC wafer. In this work, a method of process parameter optimization for femtosecond laser machining of 4H-SiC was proposed by using the predictive ability of the Artificial Neural Network (ANN) and the optimization algorithm of the non-dominated sorting genetic algorithm (NSGA-II). Firstly, the femtosecond laser was used to fabricate microgrooves on SiC wafers, and the effects of process parameters (laser average power, scanning speed and repetition rate) on groove depth, width, heat affected zone (HAZ) and material removal rate (MRR) were investigated. Secondly, The ANN model is established based on experimental data. Other experiments verify the accuracy of the model, and the average error in the model's predictions is around 5%. Thirdly, Pareto optimal solutions are obtained by global optimization of the ANN model using the NSGA-II. The experimental results show that the Pareto optimal solutions are effective and reliable. This proposed method offers dependable guidance for the selecting and optimizing process parameters of high hardness and brittle materials in the field of femtosecond laser processing, and reduces the cost of selecting the appropriate processing parameters in the production process. The method can also be extended to other machining means, such as turning and milling.

Electrical conductivity enhancement of rGO-MoS2 composite electrode for inverted PSC by parameter optimization

Carbon-based electrodes are widely used in photovoltaic, metal-ion batteries, supercapacitors, and sensors due to their low ohmic resistance and ability to integrate modifiers. Reduced graphene oxide (rGO) represents a promising alternative to graphite in carbon-based electrodes because of its high electrical conductivity, large surface area, and robust mechanical properties. This study aimed to optimize the fabrication parameters of rGO-MoS2 composite electrodes prepared via a one-pot hydrothermal method, focusing on maximizing their electrical conductivity for potential electronic applications. Taguchi analysis was employed to evaluate the impact of three key factors: rGO-MoS2 mixing ratio, annealing temperature, and annealing time. The novelty of this work lies in the systematic optimization approach using the Taguchi method, which allowed for the identification of the most significant factors and their optimal levels. The optimal combination was found to be a 1:1 ratio, 75 °C annealing temperature, and 15-min annealing time, resulting in an impressive electrical conductivity of 11 800 S m⁻1. This optimized rGO-MoS2 composite electrode exhibited an approximate 11 % reduction in sheet resistance compared to the unoptimized composite. Furthermore, all samples show an improvement in sheet resistance values compared to pure rGO and MoS2, which were 82.5 Ω/sq and 48.9 Ω/sq. Numerical simulations further revealed a 13.23 % improvement in device performance when the optimized rGO-MoS2 composite was implemented as the top electrode in an inverted perovskite solar cell, demonstrating the significant potential of this material for various electronic applications.

A Constitutive Law Modeling the Mixed Hardening Behavior of Particle-Reinforced Composites

Abstract A homogenized elasto-plastic constitutive law (including both constitutive equations and inversed constitutive equations) is proposed in an incremental form for the particle-reinforced composites based on the flow theory of plasticity and the asymptotic homogenization method. The constitutive law can be used to predict the mixed hardening behavior of particle-reinforced composites under arbitrary loading conditions if the uniaxial tension test curve of matrix materials is known. It is found that the constitutive law of particle-reinforced composites is similar in form to the law of matrix materials. There is a simple proportional relationship between the yield stress, the plastic modulus, and the deviatoric back stress of particle-reinforced composites and the corresponding parameters of matrix materials, which is equal to the ratio of the shear modulus of composites to the shear modulus of matrix materials. The tangent modulus of particle-reinforced composites can be calculated using a simple arithmetic formula according to the tangent modulus of matrix materials. A numerical algorithm is suggested.

Spatial Graphene Structures with Potential for Hydrogen Storage

Spatial graphene is a 3D structure of a 2D material that preserves its main features. Its production can be originated from the water solution of graphene oxide (GO). The main steps of the method include the crosslinking of flakes of graphene via treatment with hydrazine, followed by the reduction of the pillared graphene oxide (pGO) with hydrogen overpressure at 700 °C, and further decoration with catalytic metal (palladium). Experimental research achieved the formation of reduced pillared graphene oxide (r:pGO), a porous material with a surface area equal to 340 m2/g. The transition from pGO to r:pGO was associated with a 10-fold increase in pore volume and the further reduction of remaining oxides after the action of hydrazine. The open porosity of this material seems ideal for potential applications in the energy industry (for hydrogen storage, in batteries, or in electrochemical and catalytic processes). The hydrogen sorption potential of the spatial graphene-based material decorated with 6 wt.% of palladium reached 0.36 wt.%, over 10 times more than that of pure metal. The potential of this material for industrial use requires further refining of the elaborated procedure, especially concerning the parameters of substrate materials.

Unveiling the potential of cellulose, chitosan and polylactic acid as precursors for the production of green carbon nanofibers with controlled morphology and diameter

Carbon nanofibers (CNFs) are very promising materials with application in many fields, such as sensors, filtration systems, and energy storage devices. This study aims to explore the use of eco-friendly biopolymers for CNF production, finding novel, suitable and sustainable precursors and thus prioritising environmentally conscious processes and ecological compatibility.Polymeric nanofibers (PNFs) using cellulose acetate, polylactic acid, and chitosan as precursors were successfully prepared via electrospinning. Rheological testing was performed to determine suitable solution concentrations for the production of PNFs with controlled diameter and appropriate morphology. Their dimensions and structure were found to be significantly influenced by the solution concentration and electrospinning flow rate. Subsequently, the electrospun green nanofibers were subject to stabilisation and carbonisation to convert them into CNFs. Thermal behaviour and chemical/structural changes of the nanofibers during stabilisation were investigated by means of thermogravimetric analysis and Fourier-transform infrared spectroscopy, while the final morphology of the fibers after stabilisation and carbonisation was examined through scanning electron microscopy to determine the optimal stabilisation parameters. The optimal fabrication parameters for cellulose and chitosan-based CNFs with excellent morphology and thermal stability were successfully established, providing valuable insight and methods for the sustainable and environmentally friendly synthesis of these promising materials.