Eco-enhanced silicone rubber composites reinforced with micro and nano iron slag and TiO₂ for thermal stability and radiation protection

TL;DR

This paper explores using waste iron slag and TiO₂ in silicone rubber to improve thermal stability and radiation protection.

Contribution

The study introduces a novel eco-friendly composite material with enhanced radiation shielding and thermal properties.

Findings

Nano-sized TiO₂ and iron slag composites showed better radiation protection than micro-sized ones.

Thermal stability improved with higher concentrations of nano fillers.

Experimental results aligned closely with theoretical predictions using XCOM software.

Abstract

Silicone rubber (SR) is doped with micro- and nano-sized particles of waste iron slag-titanium dioxide mixture with different weight percentages. Linear attenuation coefficient (LAC) for studied samples was measured using a NaI (Tl) scintillation detector with energy from 0.0595 to 1.332 MeV. The increase of TiO₂ concentration against Fe slag increases the values of LAC; also, the nano samples showed better performance than the micro one. The experimental results obtained were compared theoretically with XCOM software. The comparison examined the validity of experimental results where the relative deviation ranged between 0.5% and 3% for micro size. Transmission electron microscopy (TEM) showed that the sizes of iron slag and TiO₂ nanoparticles were 30 ± 5 nm and 43 ± 5 nm, respectively. The structural morphology of prepared samples was employed by scanning electron microscope (SEM) and indicated the homogeneity of the composite, on the other hand, the distribution of nanoparticles. Thermogravimetric (TGA) tests make it evident that greater thermal stability results from increased filler concentrations, particularly nano-sized fillers. Mass attenuation coefficient (MAC) and other radiation parameters such as mean free path (MFP), half value layer (HVL), and tenth value layer (TVL) were also measured. Moreover, equivalent atomic number (Zeq) and buildup factors (EBF and EABF) were calculated.

Figures

Half value layer versus energy of a): micro samples and b): nano samples.

Tenth value layer versus energy of a): microsamples and b): nanosamples.

Mean free path of a): micro samples and b): nano samples.

The fabricated samples.

Sketching diagram of NaI(Tl) scintillation detector.

TEM micrographs showing the morphology of (a) micro-TiO₂, (b) nano-TiO₂, (c) micro slag, and (d) nano slag, highlighting particle size and structural differences.

Scanning electron micrographs of (a) STS0, (b) STS1, (c) STS2, (d) STS3, and (e) STS4. The images highlight the evolution of surface morphology with micro- and nano-filler incorporation.

TGA of silicone rubber composites.

Linear attenuation coefficient as a function of photon energy for all investigated composite samples.

The equivalent atomic number for different composite samples.

Absorption buildup factor as a function of photon energy for the samples examined.

The exposure buildup factor as a function of photon energy for the samples examined.

Full text

Introduction

Radiation is widely applied in a variety of applications, including medical diagnostics (for example, X-ray imaging), industrial processes, scientific research, and nuclear power generation. It is roughly classified into two types: ionizing and non-ionizing radiation. Ionizing radiation has enough energy to dislodge tightly bound electrons from atoms, which might cause considerable biological and environmental harm. Non-ionizing radiation, while generally less energetic, can nevertheless pose dangers depending on the intensity and length of exposure. Given the growing reliance on radiation-based technologies and the risks associated with extended or unprotected exposure, it is critical to establish appropriate radiation protection techniques to protect human health, sensitive equipment, and the environment^1,2^.

Ionizing radiation can cause a variety of biological effects, including DNA damage, skin erythema, and, in severe cases, death. As a result, radiation shielding is an essential component in a variety of industries, including medical, nuclear, and industrial applications, where occupational or environmental exposure poses a serious health risk. The strategic application of materials and technology intended to attenuate or block radiation is necessary for effective shielding, which protects patients, staff, and delicate equipment. Several critical aspects must be considered while designing a radiation shielding system, including the kind and energy of the radiation, exposure length and frequency, proximity to the radiation source, and the facility’s specific operational environment. The careful selection and design of shielding materials is also critical, since they must be optimized for best attenuation efficiency while satisfying practical restrictions such as weight, cost, and mechanical performance.

Traditionally, lead has been the primary material used for gamma radiation shielding due to its high density and atomic number, making it particularly effective at blocking gamma rays and x-rays^3^. The high number of electrons in lead atoms efficiently blocks many gamma and x-ray particles attempting to pass through the barrier, with thicker shielding providing enhanced protection. However, despite its effectiveness, lead poses significant environmental and health concerns due to its toxicity, prompting researchers to seek alternative shielding materials^4^. The search for non-toxic, lightweight, flexible, and cost-effective radiation shielding materials has led to significant research into alternatives.

Recently, glass^5^, building materials^6,7^, and a variety of polymers and their composites^8,9^have attracted the attention of researchers. Also, the advent of novel polymeric materials, including epoxy resin and silicone rubber, has emerged as a significant development in the field of radiation shielding, exhibiting remarkable efficacy in this domain^10,11^. Silicone rubber is a durable material and is recycled many times. Also, it can send them off to your local recycling centers to get them properly^12^. In order to enhance the materials utilized for radiation protection, the incorporation of metal oxides in varying proportions within the polymer matrix or glass has been employed^7^.

This approach has yielded improvements not only in the radiation properties but also in the thermal, optical, and mechanical properties of the materials. The influence of the particle size of the materials on the enhancement of these properties has also been demonstrated. The utilization of nanometric materials is characterized by an increase in surface-to-volume ratio, which further improves the entire composite^13^. Titanium dioxide (TiO₂), a material with distinctive properties, is a particularly salient candidate. The substance is naturally insoluble in water, non-toxic, inexpensive, and has good thermal stability, with higher melting and boiling points, making it extremely heat resistant.

In addition, it is an electrical insulator. The beneficial properties of TiO₂ have led to its extensive utilization in various industrial sectors, including paints, catalytic coatings, plastics, paper manufacturing, pharmaceuticals, and sunscreens. It is evident that these factors contribute to the selection of this material as a suitable shielding medium^14^. In the ongoing quest for substitute materials for lead in the radiation shielding process, industrial and agricultural waste have emerged as promising alternatives that warrant further exploration as a cost-effective and environmentally friendly technique.

Waste-derived products like red mud^15^, steel slag^16^, barite tailings^17^, recycled glass^18^, and fly ash^19,20^ have been studied for their ability to reduce ionizing radiation, notably gamma waves. These materials frequently contain elements with relatively high atomic numbers or densities, which add to their shielding effectiveness. Not much research has been done to evaluate the combined use of the limited knowledge with the conventional metal oxides in silicones and silicone-rubber hybrids using different forms of sustainable waste materials, so no study has systematically considered the different particle sizes (micro vs. nano) in these hybrid systems when it comes to density, dispersion, and other mechanisms by which gamma rays might interact. Thus, this is a critical research gap.

Al-Ghamdi et al.^21^ studied the effect of adding WO₃ nanoparticles to silicone rubber, and they found that increasing the concentration of nano WO₃ enhanced the attenuation parameters. The samples with 50% and 60% wt. of nano WO₃ have the highest values of LAC and the lowest values of HVL, TVL, and MFP, which appear to have better performance.

Sayyed, M. I., et al.^11^ examine the influence of varying MgO particle sizes on attenuation parameters using an HPGe detector. The findings revealed that SR with nano-MgO exhibited higher LAC levels than SR with micro-MgO. At lower energies, the LAC values of the micro- and nano-MgO polymers exhibited more pronounced discrepancies. Conversely, at higher energies, the advantage of nanoparticles over microparticles was less evident. It was observed that both SRs, including MgO in micro- and nano-sizes, exhibited lower MFP values than pure SR, thereby confirming the efficacy of shielding against radiation when MgO is added to the SR.

Gouda, Mona M. et al.^22^ demonstrated that the mechanical properties and the radiation protective qualities of silicone rubber loaded with nano- and micro-tin oxide were significantly enhanced. The results indicated that at a specified photon energy, the mass attenuation coefficient increased with an elevated concentration of tin oxide (II). Additionally, nano-tin oxide (II) composites demonstrated superior gamma-ray shielding capabilities compared to micro-tin oxide (II) composites.

Very worthwhile findings have been achieved, but previous studies have primarily utilized commercially available well-purified fillers. The avenue of inexpensive, green effective shielding agents such as industrial by-products, for example, slag rich in Fe-based oxides, is still not optimized. In addition, the synergistic interaction of TiO₂ with iron slag in SR matrices, as well as how their micro- and nano-sized forms influence shielding parameters, is not yet researched. Therefore, further research is required to understand whether hybrid fillers show comparable performance to commercial oxides, with an added benefit in terms of their greener and cost-effective properties.

This study aims to fabricate a novel composite based on silicone rubber (SR) and containing a mixture of TiO₂ and slag in micro and nano sizes. The linear attenuation coefficient (LAC) for samples at an energy range from 0.059 MeV to 1.332 MeV was obtained. Gamma ray interaction and penetration were evaluated by calculating other shielding parameters such as the half value layer (HVL), mean free path (MFP), tenth value layer (TVL), and the buildup factor (EBF). In order to test the reliability of the results obtained from experimental measurement, they were compared to those calculated theoretically using the X-COM database. Moreover, the morphological and thermal properties for the samples studied were measured. In addressing the identified research gap, this study evaluates the promise of sustainable slag-containing SR composites as effective substitutes to the common gamma-ray shielding materials through the use of an innovative micro-nano hybrid filler approach.

The materials and methods

Materials

The silicone rubber and titanium dioxide were brought from a commercial Egyptian company. Iron slag supplied from EZZ Steel Co. Alexandria, Egypt, is used as filler in the silicone rubber matrix. Table 1 demonstrates the elemental composition of EAF Slag powder using Energy Dispersive X-ray spectroscopy (EDX) analysis.

Table 1EDX analysis for iron slag powder.ElementMass %C2.53 ± 0.10O39.57 ± 0.43Mg1.39 ± 0.08Al1.59 ± 0.08Si5.47 ± 0.13P0.08 ± 0.03S0.07 ± 0.03Cl0.53 ± 0.04K0.07 ± 0.03Ca17.03 ± 0.22Ti0.20 ± 0.04Mn0.74 ± 0.08Fe30.73 ± 0.39

Preparation of nano powder

Nanomaterials were prepared by using a ball mill machine (Photon, a local company in Egypt), with a milling time of 21 h for iron slag and 10 h for TiO₂. The ratio of balls to powder is 10:1. Stainless steel balls of diameters 5, 10, and 20 mm are used as a milling medium. The milling speed was set at 600 rpm.

Synthesis of silicone rubber composition

The additives (TiO₂ and iron slag) of various weight fractions were mixed to avoid any agglomeration. Table 2 shows the weight% of silicone rubber and fillers of prepared samples. By adding a stiffener with a 2% weight fraction to the silicone rubber for converting into a rigid composite by catalyzed reaction. The particles were gently added to silicone rubber and then thoroughly mixed until the powder disappeared. The liquid was put into cylindrical molds of 2.5 cm in diameter and 1 cm thick. The produced samples are kept at room temperature until they are totally dry as shown in Fig. 1. The maximum weight% of TiO₂ was 20%, since increasing it would ruin the mechanical characteristics of the samples.

Fig. 1. The fabricated samples.

The density of each sample was determined by applying the Archimedes principle according to ASTM D 792–912433. To achieve this, a calibrated single-pan electrical balance with a precision of 0.0001 g was employed to weigh the samples and experimentally estimate volumes for the cylindrical samples^16^. Density measurements were performed prior to any thermal testing to ensure that thermal degradation did not influence the subsequent radiation shielding parameters.

Table 2. The weight% of silicone rubber and fillers of prepared samples.Sample codeSilicone rubber wt%TiO₂ wt%Iron slag wt%Densityg/cm³STS0100%0%0%1.150 ± 0.078Micro-compositesSTS170%10%20%1.335 ± 0.010STS270%20%10%1.432 ± 0.022NanocompositesSTS370%10%20%1.466 ± 0.025STS470%20%10%1.550 ± 0.065

Structural analysis

Energy dispersive X-ray (EDX)

Energy dispersive X-ray (EDX) analysis was carried out to determine the elemental composition of the iron slag using a JEOL JSM-5300 microscope, Faculty of Science at Alexandria University in Egypt. The measurements were performed at an accelerating voltage of 20 kV under high-vacuum conditions and at a magnification of ×370.

Scanning electron microscope (SEM)

For SEM analyses, a scanning electron microscope of the JSM-5300 JEOL type was used at the Faculty of Science at Alexandria University in Egypt. For the scanning process, the samples were coated using an ion sputtering coating device, then placed inside the electron microscope with an operating voltage of 20 kV, and the magnification order was 150, 1000, and 20,000.

Transmission electron microscope (TEM)

TEM was performed for titanium oxide (TiO₂) and iron slag NPs on a JEOL JEM-2100 high-resolution transmission electron microscope at an accelerating voltage of 20 kV at the Faculty of Science, Alexandria University, Egypt.

Thermogravimetric analysis (TGA)

The thermal stability of micro- and nano- (TiO₂-iron slag)/SR was evaluated at a heating rate of 10 °C/min as a function of temperature from 25 to 800 °C (23), and the thermal characteristics of composites were examined using a TGA [SDT-Q600] apparatus.

Shielding parameters

Shielding characterization of the samples was performed using four radioactive point sources ¹³³Ba, ¹³⁷Cs, ⁶⁰Co, and ²⁴¹Am, covering photon energies from 0.0595 MeV to 1.332 MeV. The activities of the sources, as provided by PTB, are 275.3 ± 2.8 kBq for ¹³³Ba, 385.0 ± 4.2 kBq for ¹³⁷Cs, 212.1 ± 1.5 kBq for ⁶⁰Co, and 259 ± 2.6 kBq for ²⁴¹Am^23^. A hermetically sealed Sodium Iodide (NaI(Tl)) scintillation detector, Canberra model 802 from the U.S.A., was employed in this study. The detector features an aluminum housing, an internal magnetic light shield, a photomultiplier tube, a high-resolution NaI(Tl) crystal, and a 14-pin connector. The 802 series detectors, available in well and cylindrical geometries, are known for their high efficiency, consistent performance, and long-term reliability. In our measurements, a 3 × 3-inch cylindrical NaI(Tl) detector with a resolution of 7.5% at the ¹³⁷Cs 661.66 keV peak was used, powered via the Model 2007 tube base (or 2007P preamplifier combination). A lead collimator with an inner diameter of 8 mm and an outer diameter of 100 mm was used as a house shield for the radioactive source, composite material, and detector. A source-to-detector distance of 115 mm and a detector-to-sample distance of 30 mm were maintained during measurements as shown in Fig. 2^24^.

The detected spectra were acquired and analyzed using WinTMC software. The net area under each characteristic peak was determined to calculate the corresponding count rate. Acquisition times were adjusted to ensure a minimum of 20,000 counts under the full-energy peak, resulting in statistical uncertainty below 1%. To minimize counting rate, dead-time, and pile-up effects, the sources were positioned at an appropriate distance from the detector surface.

Fig. 2. Sketching diagram of NaI(Tl) scintillation detector.

The experimental data have been measured in the presence and absence of samples to count initial intensity and attenuated intensity. The radiation shielding parameters are determined as the following:

Linear attenuation coefficient (µ) is measured by using Beer-Lambert’s law^25^:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\mu\:=\frac{1}{t}ln\left(\frac{{I}_{o}}{I}\right)$$\end{document}

In addition, the mass attenuation coefficient (MAC) was computed by dividing the estimated linear attenuation coefficient (µ) of a specific composite by its density (ρ). Furthermore, the mass attenuation coefficient (µ_m_) can also be calculated using Eq. 2^26^:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{\mu\:}_{m}=\frac{\mu\:}{\rho\:}$$\end{document}

In a medium, the mean-free path is the average distance that incident photons travel between successive contacts. This number can be quantitatively represented as the linear attenuation coefficient’s inverse^15^.

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:MFP=\frac{1}{\mu\:}$$\end{document}

In order to create materials that effectively guard against radiation, the half-value layer (HVL) and tenth-value layer are crucial characteristics. These values represent the material thickness required to minimize incident radiation on the substance by 50% and 10%, respectively, as shown by these numbers. Equations 4 and 5 are used to calculate the HVL and the tenth value layer, respectively. These computations offer crucial data for creating materials that can efficiently reduce radiation and guarantee appropriate shielding^26^.

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:HVL=\frac{ln2}{\mu\:}$$\end{document} \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:TVL=\frac{ln10}{\mu\:}$$\end{document}

Additionally, the X-COM software code can be used to theoretically evaluate the mass attenuation coefficient. The following formulas can be used to calculate the relative deviation of MAC results (Δ%) between experimental and theoretical results and (δ%) between the micro- and nano-measured results:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\varDelta\:\%=\frac{{\left({\mu\:}_{m}\right)}_{exp}-{\left({\mu\:}_{m}\right)}_{XCOM}}{{\left({\mu\:}_{m}\right)}_{XCOM}}$$\end{document} \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\delta\:\%=\frac{{\left({\mu\:}_{m}\right)}_{nano}-{\left({\mu\:}_{m}\right)}_{micro}}{{\left({\mu\:}_{m}\right)}_{micro}}$$\end{document}

Buildup factors serve as critical parameters in radiation shielding design, quantified through two principal categories: energy absorption buildup factor (EABF) and exposure buildup factor (EBF). These factors are computed using the geometrical progression (G-P) fitting method (Eqs. 9 and 10), a computational framework validated across photon energies of 0.015–15 MeV^27^. This approach accounts for scattered photons and secondary particles, enabling precise modeling of total radiation exposure relative to uncollided dose rates.

The methodology facilitates systematic evaluation of shielding efficacy, particularly for materials interacting with gamma rays via photoelectric, Compton, and pair-production mechanisms^28^. By integrating these factors into attenuation calculations, researchers optimize shielding thickness and composition to meet safety standards while addressing secondary radiation effects. The equivalent atomic number (Z_eq_) is a key to understanding the concept of radiation shielding design. This value must fall within a specific energy range between the atomic numbers Z_1_ and Z_2_ (where Z_1_ < Z_eq_ < Z_2_), and it is calculated using the following equation:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{Z}_{eq}=\frac{{Z}_{1}\left(log{R}_{2}-logR\right)+{Z}_{2}(logR-log{R}_{1})}{log{R}_{2}-log{R}_{1}}$$\end{document}

where Z_1_ and Z_2_, respectively, are the atomic numbers of the elements based on ratios R_1_ and R_2_. For the sample at the same energy, R is the ratio of MAC Compton to MAC total both of which are obtained from the XCOM program (https://www.physics.nist.gov/PhysRefData/Xcom/html/xcom1.html). The Zeq values for the examined materials and the interpolated GP-fitting EBFs (b, c, a, xk, d) in the energy range of 0.015–15 MeV must be computed using the given interpolation formula in order to precisely identify the EBFs. To get accurate information on the behavior and characteristics of the materials in various energy ranges, this calculation is crucial.

To get accurate results, make sure the interpolation procedure is done carefully.

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:C=\frac{{C}_{1}\left(log{Z}_{2}-log{Z}_{eq}\right)+{C}_{2}(log{Z}_{eq}-log{Z}_{1})}{log{Z}_{2}-log{Z}_{1}}$$\end{document}

The GP fitting parameters C The ANSI/ANS-6.4.3 standard database^29^ contains the GP fitting parameters C_1_ and C_2_, which translate to Z_1_ and Z_2_ of the chosen material. Finally, the resulting GP fitting parameters, C_1_ and C_2_, which correlate to Z_1_ and Z_2_ of the selected material, are collected from the ANSI/ANS-6.4.3 standard database^29^ and are used to estimate the EBF for the selected samples. Finally, the obtained GP fitting parameters are used to estimate the EBF for the chosen samples.

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:B\left(E,x\right)=1+\left(b-1\right)\frac{\left({K}^{x}-1\right)}{\left(K-1\right)}\:\:\:\:\:\:\:\:\:\:K\ne\:1$$\end{document} \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:B\left(E,x\right)=1+\left(b-1\right)x\:\:\:\:\:\:K=1$$\end{document}

where K(E, x) is the photon dose multiplication factor, and b is the buildup factor corresponding to 1 MFP, which is obtained by:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:K\left(E,x\right)=C{x}^{a}+d\frac{tanh\left(\frac{x}{{X}_{k}}-2\right)-tanh(-2)}{1-tanh(-2)}\:\:\:\:\:\:x\le\:40\:mfp$$\end{document}

Despite its assumption of homogeneous media, the Beer-Lambert equation and buildup factor models are frequently used as first-order approximations for composite shielding materials. It appears that the imposed uncertainty stays within acceptable bounds based on the good agreement between experimental and theoretical results.

Results and discussion

Transmission electron microscope

A TEM image of TiO₂ and iron slag micro- and nanoparticles is shown in Fig. 3. The TiO₂ particles have a mostly spherical shape, with grain sizes of 30 ± 5 nm for nano samples and roughly 3 ± 1 μm for micro samples. An uneven range of forms, from micro- to nanoparticle sizes, can be seen in the iron slag photos. In the micro range, the particles’ mean diameter was roughly 7 ± 2 μm, while in the nano range, it was 43 ± 5 nm.

Fig. 3TEM micrographs showing the morphology of (a) micro-TiO₂, (b) nano-TiO₂, (c) micro slag, and (d) nano slag, highlighting particle size and structural differences.

Scanning electron microscope

The microstructure of micro- and nano-samples is illustrated in Fig. 4. The SEM micrograph for the pure silicone Fig. 4a reveals a smooth, homogeneous surface with a characteristic wrinkled texture. There are no observable particulate inclusions or agglomerates, indicating a continuous polymer matrix without phase separation or filler-induced heterogeneity. For sample STS1, Fig. 4b displays a significant increase in surface roughness and heterogeneity. Numerous dispersed particles of varying sizes are distributed throughout the matrix. The fillers are not perfectly uniformly distributed; some localized clusters and larger particles are evident, especially for iron slag, which tends to form larger inclusions.

The introduction of both TiO₂ and iron slag disrupts the smooth matrix, introducing multiple interfaces. For the same weight fraction of the nano sample, the STS3 (Fig. 4d) introduces better distribution of powder in the silicone matrix than the sample STS1; this is attributed to the small size of the nanoparticles of filling powder. By increasing the amount of TiO₂ to 20%, Fig. 4c explains that the surface remains rough and heterogeneous, but the particulate dispersion appears finer and somewhat more uniform. The number of large agglomerates is reduced compared to the STS1 image, with more numerous but smaller particles visible. Moreover, the sample STS4 (Fig. 4e) evidently shows the best dispersions of TiO₂ among the silicone matrix, but the coverage of the silicone rubber is higher.

Fig. 4. Scanning electron micrographs of (a) STS0, (b) STS1, (c) STS2, (d) STS3, and (e) STS4. The images highlight the evolution of surface morphology with micro- and nano-filler incorporation.

Thermal analysis

Thermal analysis is a crucial factor in determining whether a material can be applied in technologically advanced applications. Heat-resistant polymers have been widely used in many industrial products. However, with the advancement of industrial technologies, differences between the thermal stability of polymer matrices and industry standards have emerged, highlighting the need to explore new material solutions. The addition of metal oxides has been shown to enhance the thermal stability of various industrial polymers, including silicone rubber^30^.

Fig. 5TGA of silicone rubber composites.

As illustrated in Fig. 5 and summarized in Table 3, the thermogravimetric analysis (TGA) results reveal clear differences in the thermal behavior of pure silicone rubber and its composites reinforced with TiO₂ and iron slag in both micro- and nano-forms. Pure silicone rubber (STS0) exhibits the lowest thermal resistance, with degradation starting around 300 °C, a maximum decomposition rate (T_max_) near 420 °C, and a final residue of ~ 28%, indicating the presence of inorganic components but limited thermal durability^31^.

The incorporation of micro-fillers (STS1 and STS2) significantly enhances thermal performance, shifting the onset temperatures to 350–380 °C and T_max_ to 450–470 °C. Decomposition residues increase to 60–70%, reflecting the beneficial effect of TiO₂ and iron slag in restricting chain scission and promoting ceramic-like char formation during degradation. While STS2 (20% micro TiO₂ + 10% micro slag) shows a higher char yield than STS1, careful examination of the full TGA profile indicates that STS2 exhibits slightly slower degradation at intermediate temperatures but does not uniformly surpass STS3 in all regions^30,32^.

The nano-filled composites (STS3 and STS4) show the highest thermal stability across the majority of the temperature range. Onset temperatures are increased to ~ 400 °C, T_max_ is delayed to 480–500 °C, and final residues exceed 75%. The enhanced surface area and improved interfacial interactions of nanoscale fillers restrict the mobility of volatile fragments during pyrolysis, leading to superior thermal resistance. Notably, STS4 (20% nano TiO₂ + 10% nano slag) demonstrates the most stable overall degradation profile, confirming the significant role of nanoscale TiO₂ in promoting char stability and reducing thermal weight loss^33^.

Overall, the thermal stability of the composites follows the order: pure < micro-filled < nano-filled. While final residue is an important indicator of thermal performance, a comprehensive evaluation based on the entire degradation profile, including onset temperature, T_max_, and weight loss trends, provides a more accurate assessment of thermal stability. These findings align with recent literature reporting that TiO₂ and iron oxide fillers, particularly at the nanoscale, delay decomposition and enhance char yield due to catalytic and barrier effects.

Table 3. The onset temperature and residual percentage of pure SR, micro- and nanofillers.SampleCodeOnsetTemperature (°C)T_max_ (°C)Residueat 800 °C (%)STS030042028STS135045060STS238047070STS340048075STS441050078

Shielding results

The measured results of MAC of study samples and theoretical data utilizing XCOM software are listed in Table 4.

Table 4. The experimental and theoretical MAC results of micro- and nanocomposites.SampleMicro-compositesSampleNanocompositeEnergy(MeV)MAC(XCOM)(cm²/g)MAC (EXP.)(cm²/g)Δ%Energy(MeV)MAC(EXP.)(cm²/g)δ%STS00.05950.2260.258 ± 0.022−0.8980.08090.1840.209 ± 0.014−1.1990.3650.1070.121 ± 0.021−1.0180.6610.0830.092 ± 0.023−3.9971.1730.0630.069 ± 0.011−4.2021.3320.0590.067 ± 0.031−1.666STS10.05950.5490.559 ± 0.0111.896STS30.05950.614 ± 0.0059.8910.08090.2520.259 ± 0.0252.9810.08090.279 ± 0.0317.7230.3650.0980.097 ± 0.014−1.0820.3650.103 ± 0.0425.6730.6610.0740.076 ± 0.0221.2690.6610.080 ± 0.0023.8821.1730.0580.057 ± 0.032−1.2361.1730.058 ± 0.0111,9171.3320.0540.055 ± 0.0211.5441.3320.056 ± 0.0031.006STS20.05950.5590.575 ± 0.0112.811STS40.05950.652 ± 0.02213.3270.08090.2550.261 ± 0.0251.7780.08090.292 ± 0.02511.8720.3650.0980.099 ± 0.0111.4580.3650.109 ± 0.02110.5130.6610.0760.077 ± 0.0141.3030.6610.084 ± 0.0168.7991.1730.0580.059 ± 0.011−2.6151.1730.060 ± 0.0147.0541.3320.0540.054 ± 0.051−0.2571.3320.057 ± 0.0215.150

The MAC decreases with an increase in photon energy and increases with higher filler concentration. This is a trend that corresponds well with the dependence of photon interactions on energy: at lower energies, the photoelectric effect is dominant and extremely sensitive to the atomic number (Z) of the filler; in intermediate energy ranges, Compton scattering takes the lead, while at higher energies, the contribution from pair production starts becoming measurable.

In the case of micro- and nanocomposites, there seems to be a consistent observation of higher MAC values for nanofillers than for micro fillers. The replacement of micro fillers by nanofillers, for instance, increases the MAC by 1–13% for certain photon energy values. This improvement can be attributed to several nanoscale-related effects: nanoparticles provide a higher surface-to-volume ratio that enhances filler-matrix interfacial interactions and diminishes micro voids, thus increasing the effective density and improving photon absorption. Also, the comparatively better dispersion of nanoparticles in silicone rubber matrix decreases scattering losses and improves energy dissipation efficiency. These factors account for the better attenuation of STS3 and STS4 with respect to their micro-filled counterparts (STS1 and STS2), even with the same weight as fillers^22^.

The linear attenuation coefficient (LAC), presented in Fig. 6, behaves similarly: posing an increasing function of filler concentration and a decreasing function of photon energy. STS4 has the highest LAC amongst all the samples in the energy spectrum, thus showing maximum potential for shielding. The observed increase in LAC of 4.3–19.9% for nanocomposites confirms that nanoscale fillers not only provide higher density but also allow more efficient photon interaction per unit thickness. This, in turn, becomes critical especially at low photon energies whereby the photoelectric effect is accentuated by the presence of high-Z elements like Ti and Fe in the fillers.

Fig. 6. Linear attenuation coefficient as a function of photon energy for all investigated composite samples.

In contrast, the pure silicone rubber sample STS0 has the lowest LAC throughout the energy range, confirming the necessity of incorporating high-Z fillers to improve radiation shielding performance. The equivalent atomic number parameter (Z_eq_) may vary with energy. It was employed to determine the properties of a substance in relation to related constituents. The values of the materials’ Z_eq_ for a particular energy can be found using the ratio of the Compton cross-section to the total cross-section (MAC_Compton_/MAC_Total_)^26^. First, the (MAC_Compton_/MAC_Total_) ratios for 23 unique elements (atomic numbers 4–92) were calculated over a range of energies from 0.015 to 15 MeV.

These computations were performed using XCOM. As depicted in Fig. 7, the variation of the equivalent atomic number (Zeq) is closely linked to the dominant photon interaction mechanisms rather than to energy loss alone. At low photon energies (0.015–0.1 MeV), Zeq exhibits higher values due to the predominance of the photoelectric absorption process. In the intermediate energy range (0.1–1 MeV), Zeq gradually increases, reflecting the increasing influence of Compton scattering. The maximum Zeq is observed around 1 MeV for all samples. For photon energies above 2 MeV, Zeq decreases as pair production becomes the dominant interaction mechanism, which reduces the relative contribution of atomic number-dependent processes^10^.

Fig. 7. The equivalent atomic number for different composite samples.

Based on the equivalent atomic number (Z_eq_), thickness, and photon energy, the buildup factors were calculated using interpolation of GP fitting parameters. The energy absorption and exposure buildup factors (EABF and EBF) versus photon energy for penetration depths up to 40 mfp for different composites are shown in Figs. 8 and 9. The behavior of BFs can be divided into three regions according to the interaction of photon energy with the material sample.

At low energy, the photoelectric effect is the predominant process; the photons lose their energy, so the BFs values were low. After that, the increase reaches its maximum value at medium energies, where Compton scattering is a determinant. Therefore, the production of secondary photons is enhanced, leading to a rapid decrease in buildup factor (BF) values at high energies, indicating the increasing dominance of pair production effects^22^.

Fig. 8. Absorption buildup factor as a function of photon energy for the samples examined.

Fig. 9. The exposure buildup factor as a function of photon energy for the samples examined.

One of the most important criteria impacting a shielding material’s efficiency is its thickness, which is commonly represented by the half-value layer (HVL), tenth-value layer (TVL), and mean free path (MFP)^34^. Figures 10, 11 and 12 show how photon energy affects the HVL, TVL, and MFP values of silicone rubber composites with micro- or nano-sized fillers. In all cases, a consistent pattern is observed: as photon energy increases, so do HVL, TVL, and MFP. In contrast, raising the filler concentration reduces these values, indicating improved shielding performance.

Fig. 10. Half value layer versus energy of a): micro samples and b): nano samples.

As illustrated in Fig. 10a, the HVL at the low photon energy of 0.05951 MeV is measured to be 2.66 cm for sample STS0, 0.93 cm for STS1, and 0.77 cm for STS3. The HVL values rise to 7.20 cm (STS0), 6.74 cm (STS1), and 5.91 cm (STS3) at the intermediate energy of 0.661 MeV. Further increase is shown at the higher energy level of 1.332 MeV, where HVL values for STS0, STS1, and STS3 are 10.10 cm, 9.41 cm, and 8.45 cm, respectively.

As depicted in Fig. 10b, samples with larger filler concentrations have significantly lower HVL values at 0.05951 MeV, measuring 0.84 cm for STS2 and 0.63 cm for STS4. At 0.661 MeV, the HVL values are 6.30 cm and 5.34 cm for STS2 and STS4, respectively, while at 1.332 MeV, they are recorded as 8.97 cm (STS2) and 7.88 cm (STS4). These results clearly indicate that increasing the filler content, particularly with nano-sized particles, enhances the photon attenuation capability, especially at lower energies.

Similarly, the Tenth-Value Layer (TVL) and Mean Free Path (MFP) values for all micro- and nano-filled samples exhibit an increasing tendency with rising photon energy, while they decrease with increasing filler concentration. As illustrated in Figs. 11 and 12, the TVL and MFP values follow the order STS0 > STS1 > STS2 > STS3 > STS4. This sequence clearly indicates that sample STS4 demonstrates the most effective radiation shielding performance among all the studied compositions. Finally, the HVL, TVL, and MFP decreased by 4–16.6% in nano-filled samples.

Fig. 11. Tenth value layer versus energy of a): microsamples and b): nanosamples.

Fig. 12. Mean free path of a): micro samples and b): nano samples.

Overall, Nanocomposites are excellent in radiation shielding-performance because of the increased density, packing of particles, improvement in interfacial interactions, and better utilization of high-Z elements; thus, all of these are enhanced with photoelectric absorption and the probabilities of Compton scattering, especially for low and intermediate energies of photons. In addition, waste iron slag was also found to be for environmental sustainability and shielding effectiveness because this added further high-Z constituents, which raised their MAC and LAC values^22,25^.

Table 5 is a comparative table listing the advantages and disadvantages of the current study versus some similar publications. The table demonstrates that while similar works contribute valuable partial insights, the present study offers a more integrated and novel framework for understanding and developing advanced lead-free polymer composite materials for radiation protection.

The results in Table 5 compare the linear attenuation coefficients (LAC) of the current glass-polymer composite system to those reported in prior polymer-based radiation shielding investigations. Across the investigated photon energy range (59.5–1332 keV), it is clear that the LAC values of the current samples, especially those incorporating nanofillers, are higher than those of the majority of previously reported polymer composites. The enhanced dispersion and interfacial contact of nano-sized heavy metal oxides in the silicone rubber matrix, which raise the likelihood of photon interaction and lower the mean free path, are responsible for this improvement.

The enhanced dispersion and interfacial interaction of nano-sized heavy metal oxides inside the silicone rubber matrix, which raise the likelihood of photon interaction and lower the mean free path, are responsible for this improvement.

The existing materials show equivalent or better attenuation performance while retaining more flexibility and lower density when compared to systems like PMMA–WC or epoxy composites, making them promising for lightweight shielding applications.

As a whole, the addition of nanoscale fillers to the current study significantly improved attenuation capability over both micro filled and previously reported polymer composites, implying that the developed material strikes an effective balance between mechanical performance, processability, and radiation-shielding efficiency.

Table 5. Comparison of a recent study on the enhancement of Attenuation properties with nanocomposites for gamma photons.MaterialsEnergy range (keV)LAC valueDetection method—Detector typeAuthors - yearSR + nano mix (SnO₂, Bi₂O₃, CdO)59.5480.99661.61173.231332.50.2186 to 2.55780.1796 to 1.19500.1067 to 0.08390.0680 to 0.05970.0573 to 0.0567Experimental – NaI (33) scintillation detector. El-Khatib, 2024 ^33^ Epoxy + Fe₂O₃ nP + Carbon nP59.5480.99661.61173.231332.50.2975 to 0.37830.2275 to 0.08450.0880 to 0.09570.0639 to 0.06960.0602 to 0.0656Experimental – NaI (33) scintillation detector.M.M. Khalil, 2024 ^10^ PMMA + micro tungsten carbide59.5480.99661.61173.231332.50.773 to 1.9511.493 to 4.2190.084 to 0.0880.063 to 0.0590.058 to 0.055Experimental - pure germaniumdetector (HPGe) El-Khatib, 2024^9^ZPMMA + nano tungsten carbide59.5480.99661.61173.231332.50.898 to 2.3031.726 to 4.9380.095 to 0.1000.069 to 0.0660.063 to 0.059Experimental - pure germaniumdetector (HPGe) El-Khatib, 2024^9^SR + Micro tin oxide (SnO₂)59.5480.99661.61173.231332.51.184 to 2.6320.593 to 1.2070.081 to 0.0780.061 to 0.0580.057 to 0.054Experimental – NaI (33) scintillation detector.M. Gouda, 2023 ^22^ Li₂B₄O₇ glass + ilmenite812763023563880.388 to 0.4940.282 to 0.2960.269 to 0.2650.238 to 0.2570.228 to 0.244Experimental - pure germaniumdetector (HPGe)Nergiz Yorgun, 2026^36^Li₂B₄O₇ glass + witherite812763023563880.704 to 1.9560.312 to 0.3660.275 to 0.3160.258 to 0.2900.235 to 0.284Experimental - pure germaniumdetector (HPGe)Nergiz Yorgun, 2026 ^36^ SR + Bi₂ (WO₄)₃--------------------------661.61173.21332.5--------------------------0.076 to 0.0880.051 to 0.0560.049 to 0.054Experimental – NaI (33) scintillation detector.Aly Saeed, 2022 ^37^ Present work(Micro filler)59.5480.99661.61173.231332.50.559 to 0.575, 0.259 to 0.2610.077 to 0.0790.056 to 0.0590.054 to 0.055Experimental – NaI (33) scintillation detector.Present work(Nano filler)59.5480.99661.61173.231332.50.614 to 0.6520.279 to 0.2920.080 to 0.0840.058 to 0.0600.056 to 0.057Experimental – NaI (33) scintillation detector.

Conclusion

1. The study demonstrates that incorporating TiO₂ and waste iron slag into a silicon rubber matrix, particularly in nano-sized form, improves the structural, thermal, and radiation shielding properties of the composite. These results suggest potential applicability of these materials as radiation shielding candidates.

2. Morphological analysis confirmed that the filler particles are nanoscale and uniformly distributed within the matrix. Increasing the filler concentration reduces voids and pores in the silicon rubber, contributing to enhanced thermal and radiation properties.

3. Thermal analysis indicates improved stability of the composites compared to pure or micro-filled silicon rubber. Higher TiO₂ content further enhances thermal resistance, consistent with previous findings that nanoscale TiO₂ and iron oxide act as barriers and catalysts, delaying decomposition and increasing char yield.

4. Gamma-ray shielding measurements show that the mass attenuation coefficient (MAC) increases with filler concentration, particularly for nanofillers, while decreasing with increasing photon energy. This trend reflects the density effect of the fillers and their efficiency in gamma-ray attenuation.

5. Parameters such as mean free path (MFP), half-value layer (HVL), and tenth-value layer (TVL) decrease with increasing filler content, indicating improved shielding performance. Among the tested samples, STS4 demonstrates the most favorable attenuation, though thickness-related performance should be interpreted cautiously, as it can vary with photon energy and interaction mechanisms.

6. Analysis of the energy buildup factor (EBF) shows higher values in the intermediate energy region, where Compton scattering dominates. Sample STS0 exhibits the highest EBF, while STS2 shows lower EBF and equivalent atomic number (Zeq) values. These results highlight the influence of filler content and distribution on photon interactions, without overgeneralizing the effects across all energies.

7. Overall, silicon rubber composites with higher nano TiO₂ content (STS4) show superior attenuation characteristics, indicating their potential as effective gamma-ray shielding materials.

8. The study confirms that these composites possess the properties required for multiple radiation-protection applications, including flexible wearable protectors, low-density portable sheets, medical apron replacements, and housings for nuclear detection and measurement devices.