Iron borophosphate glasses: Merging optical transparency, structural integrity, and radiation shielding efficacy for sustainable uses

2.1 Materials and glass preparation

Analytical grade chemicals of orthoboric acid (H₃BO₃) as a source for boron oxide (B₂O₃) supplied by Lab. Rasayan, Ammonium dihydrogen orthophosphate NH₄H₂PO₄ as a source for phosphorus pentaoxide (P₂O₅) supplied by Sigma Aldrich Co. Sodium oxide and calcium oxide were drawn from their carbonate partner supplied by Lenxns Co. Iron oxide (Fe₂O₃) was supplied by Sigma Aldrich and used as received. Prepared composition simulates modified Hench bioglass 45S5 containing (45B₂O₃-24.5CaO-24.5Na₂O-6P₂O₅ wt% with full replacement of silicon oxide with boron oxide). The composition equivalent to (42.5B₂O₃-26CaO-28.7Na₂O-2.8P₂O₅ mol%).

Accurately weighted chemicals were mixed in an agate mortar and transferred into a porcelain crucible placed in an oven adjusted at 400 °C for 2 h to ensure the removal of water, carbon dioxide, and ammonia. The temperature was then raised to about 1150–1200 °C for another 2 h. The melt was swirled occasionally many times to ensure homogeneity and bubble-free samples. The melt was then poured into a heated stainless-steel mold of the required dimensions and transferred to an oven adjusted at 350 °C. The oven was switched off and kept cooling gradually to room temperature. Samples were then transferred to a dry place until use. Sample abbreviation along with composition was shown in Table 1 while the change in color with the addition of iron oxide was observed in Fig. 1.

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Fig. 1

change in glass color with the addition of iron oxide.

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2.2 Sample characterization and radiation shielding calculations

X-ray diffraction patterns (XRD) were recorded for pulverized samples using a BRUKER D8 adopting Cu target operating at 40 kV-40 mA with (λ = 1.54 A^o). FTIR vibrational spectra recorded via a double beam Nicolet is 10 spectrometer using KBr disc route within the wavenumber range extended between 2000–400 cm⁻¹. Optical absorption spectral data were measured for polished glass samples using (UV–vis) spectrophotometer (V-750) within the range from 190-1100 nm. The sample density (ρ_S) of the glass samples was calculated using Archimedes' method utilizing xylene as an immersion solvent at room temperature.

The radiation shielding characteristics were estimated using online calculations via Phys-x software within a photon energy range between 15 keV to 15 MeV.

3.1 X-ray diffraction

X-ray diffraction is an important tool that describes periodic or non-periodic structures of the studied sample and can be considered as a fingerprint that approves the formation of specific crystalline phases within the structure (Lepry and Nazhat, 2020). Fig. 2 reveals the XRD pattern of the studied soda lime borophosphate glass containing variable amounts of iron oxide. Amorphous borate glasses lack long-range structural periodicity and do not show crystalline Bragg peaks in the XRD pattern Instead, a very broad diffraction halo is observed, indicating short-range disorder in the atomic structure and absence of grain boundaries. This amorphous halo is centered around 2θ values of 10° to 35°, depending on the exact glass composition.

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Fig. 2

XRD pattern of studied glasses.

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Several authors (Lepry and Nazhat, 2020; Heuser and Nofz, 2022; Ohtori et al., 2001; Heuser et al., 2022) describe the broad peak maximum occurring near 18° in the case of alkali borate glasses, while for alkaline earth-containing borates, it shifts closer to 25°. Peak position also shifts to higher angles with increasing boron content, as BO₃ units dominate over BO₄ units leading to more tightly packed structural formations. The width and intensity of the amorphous halo provide information about deviation from periodicity and extent of disorder in the borate glass structure. Increased peak widths also suggest enhanced glass-forming ability and resistance against crystallization on heating.

3.2 FTIR optical absorption spectra

Infrared spectroscopy serves as an invaluable tool to probe the short-range structural variations in glass networks based on characteristic vibrational modes of the coordination complexes. However, unraveling individual bond signatures from the complex IR spectral profile poses considerable challenges owing to extensive peak overlaps (Kamitsos, 2015). Advanced computational techniques like derivative spectroscopy and curve-fitting methods help resolve the convoluted spectral features into constituent bands. Such bands represent specific structural groups coordinated with iron species based on changes in relative peak intensities and slight band shifts (Gautam et al., 2012, 2012).

Iron represents a conditional intermediate glass component, capable of adopting both trivalent Fe³⁺ or divalent Fe²⁺ oxidation states. However, according to the charge balance considerations, the stable trivalent form is the most favored in oxide glass hosts (Dyar, 1985). In the Fe³⁺ state, it coordinates with non-bridging oxygen atoms from the borate/phosphate network forming distorted [FeO₄] trigonal bipyramidal or [FeO₆] octahedral units as the predominant typical coordination (Dunaeva et al., 2012). Each of these polyhedral structures exhibits characteristic vibrational modes discernible using FTIR spectroscopy.

At higher loadings beyond solubility limits, clustered formations of Fe³⁺ ions may occur which also possess identifiable spectral markers (Donald et al., 2006). The presence of minor Fe²⁺ fractions owing to a partial reduction of Fe³⁺ cannot be discounted. These effectively serve as network modifiers contributing free electrons and influencing optical properties (Romero-Perez et al., 2001). Fourier transforms infrared absorption spectra of an iron oxide containing soda lime borophosphate glasses comprised of multiple overlapping peaks representing various [BO₃), [BO₄], [PO₄], [FeO₄], and [FeO₆] structural groups along with other impurities (Brauer and Möncke, 2016).

Derivative spectroscopy aids the identification of precise band positions and relative amplitudes. Curve-fitting procedures facilitate reliable separation into Gaussian components centered around specific wave-number regimes indicative of coordination fields (Sadeq and Abdo, 2021). The frequencies and full-width-at-half-maxima provide information regarding bond strengths and structural order/disorder phenomena respectively. The peak area percentages determine the relative abundances of various groups, allowing quantitative assessment of changing network configurations with progressive iron assimilation (Al-Baradi et al., 2022; Kamitsos, 2015).

Fig. 3(a) displays the FTIR spectra in the 2000–400 cm⁻¹ range for soda lime borophosphate glasses with 0–10 mol% Fe₂O₃ addition prepared by standard melt-quench technique. A broad absorption regime is observed spanning across the mid-IR region comprising several overlapping peaks representing various structural groups.

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Fig. 3a

FTIR spectral data of studied glasses.

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The first-order derivative profile highlights precise inflection points more clearly as depicted in Fig. 3(b). The negative bands accurately indicate true peak positions devoid of shifts arising from shoulders/tails. Prominent minima are revealed centered around 705, 926, 1022, 1204, and 1386 cm⁻¹ wavenumbers.

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Fig. 3b

Deconvolution data of sample containing 1 mol% iron oxide.

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The original FTIR spectra are curve-fitted using these derivative minima as initial centroid positions for the Gaussian peaks. The IR bands are accordingly resolved into eight constituent structural components as shown in Fig. 3. The independence of FTIR peak frequencies on composition aids the universal application of reference peak positions across the glass series during curve-fitting procedures. Only relative intensities may vary following changing structural configurations (Kamitsos, 2003; Abdelghany, 2010).

The deconvoluted spectrum fitting composition-invariant Gaussian peaks enable reliable quantitative examination of evolving structural units with iron oxide additions in soda-lime borophosphate glasses. Fig. 3(b) reveals an example of the sample containing 1 mol% iron oxide. The specific positions and intensities of these deconvoluted bands can provide insights into the structural arrangements, connectivity, and relative concentrations of different borate groups within the glass network.

N4 is specifically defined as the ratio of tetrahedral BO₄ units to the sum of tetrahedral BO₄ and trigonal BO₃ units in borate glass compositions and their value is controlled through the effect of network modifiers on the conversion of BO₃ units to BO₄ units. The addition of network modifiers (such as Na₂O and CaO in this case) promotes the conversion of BO₃ units to BO₄ units, increasing the N4 value. However, the exact relationship between the composition and the N4 value is complex and depends on various factors, such as the relative amounts of network formers and modifiers, the presence of other structural units (e.g., P₂O₅), and the melting conditions. Based on the relatively high content of network modifiers (28.7Na₂O + 26CaO = 54.7 mol%), we can expect a higher N4 value, possibly in the range of 0.4 to 0.7. such ratio can be calculated using the deconvoluted FTIR data through calculations adopting obtained relative areas for such function groups as reported by several authors (Elbasuoni et al., 2024; Abdelghany et al., 2017; Yiannopoulos et al., 2001; Topper et al., 2023). A reasonable value for the N4 value in base soda lime borpophosphate glass composition was found to be around 0.5, indicating that approximately half of the borate units are present as BO₄ tetrahedral units, and the other half as BO₃ trigonal units.

When iron oxide (Fe₂O₃) replaces the same amount of the B₂O₃ in the given borate glass composition, it can potentially affect the glass structure and properties through the following (Abou Hussein and Barakat, 2022; Abou Hussein and Abdel-Galil, 2023; Abou Hussein et al., 2021):

• Network former/modifier balance: In glass structures, network formers (e.g., B₂O₃, P₂O₅) create the glass network, while network modifiers (e.g., Na₂O, CaO) modify the network by creating non-bridging oxygens. Replacing B₂O₃ with Fe₂O₃ can affect this balance.

• Depending on its coordination environment within the glass structure, Fe₂O₃ can act as a network former or modifier. If it acts as a network former, it can further depolymerize (break up) the borate network, potentially increasing the N4 value (proportion of tetrahedral borate units).

• Iron can exist in two oxidation states, Fe²⁺ and Fe³⁺, in glasses. The presence of both these ions can create a mixed ionic-covalent character in the glass network, affecting its physical and optical properties.

• If Fe₂O₃ acts as a network former, it can further break up the borate network by creating more non-bridging oxygens, potentially increasing the proportion of tetrahedral borate units (N4 value).

• The changes in the glass network structure, the mixed ionic-covalent character due to Fe²⁺ and Fe³⁺, and the potential increase in N4 value can influence various physical and optical properties of the glass, such as density, thermal stability, refractive index, and optical absorption/transmission.

Calculation of the N4 value for such composition may shed light on the role of iron oxide and possible changes in the properties of the studied glasses. The calculated N4 value was estimated as shown in Table 2. The decrease in the value when iron reaches 8 mol% suggests the presence of iron in both former and modifier sites within the glass structure.

3.3 UV/Vis optical absorption spectra

Fig. 4 reveals UV/Vis. spectral data of the prepared samples. The UV–visible spectra of borate glasses often show characteristic absorption bands that provide insights into the glass structure and the effects of adding transition metal ions like iron. The peak at about 240 nm may be attributed to electronic transitions in the BO₃ structural units of the borate glass network corresponding to π-π* transitions of O-B-O linkages indicating the presence of trigonal BO₃ units as the main borate species (Marzouk and Elbatal, 2014). Several authors attributed such peaks to the presence of iron as a contamination in the chemicals used for the preparation of glasses even at ppm level (Marzouk et al., 2017; Shashikala and Udayashankar, 2020). The shoulder at ∼ 305 nm is considered to be related to charge transfer transitions in Fe³⁺ ions representing ligand–metal (O₂-Fe³⁺) charge transfer reported by several authors (Ehrt and Möncke, 2002; Volotinen and Pehlivan, 2022).

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Fig. 4

UV/Vis. Optical Spectral data of studied glasses.

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The band at ∼ 375 nm considered to be arising from d-d transitions in Fe³⁺ ions specifically corresponds to ⁶A_1g → ⁴T_1g (G) transitions and indicates the presence of Fe³⁺ ions occupying tetrahedral sites still increased and red-shifted, but when the Fe concentration becomes 8 %it showed a broad band.

The UV–vis spectra provide characteristic fingerprints regarding the B³⁺ coordination state and the incorporation of Fe³⁺ ions in interstitial sites in the borate glass structure. The growth of 305 and 375 nm peaks indicates the progressive inclusion of Fe³⁺ ions in the glass network with additional iron oxide content.

Calculating the direct and indirect optical energy bandgap (E_g) of glasses provides an understanding of the electronic structure and availability of electronic transitions. A lower indirect gap suggests transitions through band tails needing phonon assistance. Larger bandgaps allow a wider wavelength transparency range. Glasses with bandgaps > 3 eV can enable good visible light transmission. In addition, it can help predict some electrical properties. Smaller bandgaps facilitate easy excitation of electrons across bands leading to improved conductivity while larger bandgaps are associated with highly insulating glasses (Elesh et al., 2023; Sallam et al., 2023). Tauc’s plots (Fig. 5) are usually used to calculate the energy gap following the equations:

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Fig. 5

Tauc’s plots of the parent (S1) and selected glass samples (S2, S4) containing iron oxide.

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(αhν)² = B(hν − Eg_direct) For direct allowed transitions.

(αhν)^1/2 = B(hν – Eg_indirect) For indirect allowed transitions.

Where α is the Absorption coefficient, h Planck's constant, ν is the frequency of incident light, B is a constant, Eg_direct is the direct allowed optical bandgap, and Eg_indirect is the Indirect allowed optical bandgap. Tauc plots can be generated by plotting (αhν)² and (αhν)^1/2 versus photon energy (hν) for direct and indirect allowed transitions respectively. The extrapolation of the linear portions near absorption edges to x-axis intercepts can supply both energies as indicated by Fig. 5 and Table 3.

The IR, UV, and calculated N4 and optical energy gap results are evidence of the presence of iron in both former and modifier sites within the glass structure as Fe³⁺ ions.

3.4 Calculation of physical parameters

Fig. 6 reveals changes in the measured density and calculated molar volume of the studied glass while Table 3 reports a peripheral change in theoretical and experimental densities when iron oxide is incorporated at the expense of boron oxide, the balancing effects on glass structure led to marginal changes in density and molar volume of the borate glass system. This also reflects the variation of both packing density (Pd) and free volume (Vf) shown in Fig. 7.

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Fig. 6

Variation of density and molar volume with iron oxide addition.

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Fig. 7

Variation of packing density and free volume with iron oxide addition.

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The theoretical density can be calculated using the Additive Method assuming that the density of the glass is the weighted sum of the densities of its constituent oxides. The theoretical density (ρ_th) can be calculated using the following equation: $${\rho }_{\mathit{th}}=\sum _{i=0}^n{x}_i{\rho }_i$$ Where x_i is the mole fraction of the i^th oxide component, and ρ_i is the density of that oxide.

The observed behavior can be interpreted as (Abou Hussein and Barakat, 2022; Abou Hussein and Abdel-Galil, 2023):

• Fe³⁺ can act as both a glass network former and a modifier in a borate glass structure. As B₂O₃ (glass former) is replaced by Fe₂O₃, Fe³⁺ ions maintain the integrity of the borate glass network, preventing major density fluctuations.

• The boron coordination state in the borate glass network is constrained to be predominantly trigonal BO₃ units. As more Fe₂O₃ is added, the Fe³⁺ ions preferentially occupy interstitial sites without heavily disturbing the boron coordination state.

• Conversion of the BO₃ function group to BO₄ unit with the addition of Fe₂O₃ combined with the change in density may be balanced with replacing B₂O₃ (atomic mass densities 2.46 g/cm³) with Fe₂O₃ (atomic mass densities 5.25 g/cm³) which does not significantly alter the overall glass density and molar volume as observed by Sallam et al (Sallam et al., 2023).

• Only a small fraction of B₂O₃ (typically < 10 mol%) can be substituted by Fe₂O₃ before phase separation occurs as indicated by the amorphous nature of glass detected by X-ray diffraction (XRD). So the composition variation is not enough to drastically affect overall density.

Other parameters including Ion concentration (N), Polaron radius (r_p), Field strength (F), Molar volume of the boron atoms V_b, and Average boron–boron distance(d_B–B), can be calculated as described previously (Basha et al., 2023; Madshal et al., 2023) and listed in the Table 3.

3.5 Radiation shielding characteristics

Borate glasses have emerged as effective radiation shielding materials owing to the high neutron capture cross-section of boron, which facilitates strong interaction with neutron radiation. The high cross-section for neutron absorption which is a measure of the probability of a particular nuclear reaction occurring between a neutron and a nucleus makes boron attractive for specialized shielding applications in nuclear reactors, spent fuel storage, medical devices, etc (Basha et al., 2023; Baykal et al., 2023).

Various theoretical and experimental studies have analyzed the influence of glass composition, the presence of modifiers, dopants, etc. on the gamma-ray attenuation and neutron shielding efficiency in borates (Baykal et al., 2023; Kurtulus et al., 2023; Kilic et al., 2023). Key radiation shielding parameters that are used to quantify the protection ability include mass attenuation coefficient, half-value layer thickness, mean free path, tenth value layer, etc.

The mass attenuation coefficient (μ/ρ) indicates the probability of radiation interaction on a per-unit density basis. For effective shielding, glasses require high μ/ρ to maximize attenuation (Kurtulus et al., 2023; Kilic et al., 2023). The half-value layer (HVL) thickness signifies the amount of material needed to reduce the initial radiation intensity by half. Lower HVL allows compact and lightweight shield design without compromising protection levels (Baykal et al., 2023). A similar metric is the tenth value layer (TVL) indicating 90 % attenuation. Through compositional optimization, borates with HVL < 1 mm and TVL < 2 mm are feasible (Ali et al., 2022; Levet, 2023).

The mean free path gives the average distance between two successive interactions and needs to be lowered using dopants with high interaction cross-section (Saleh et al., 2022). The radiation shielding characteristics of the prepared glasses were computed using the PhysX/PSD software.

3.5.1

3.5.1 Mass attenuation coefficient (MAC)

Beer-Lambert rule ( $I=I_0{e}^{-\mu x}$ ) can be used to determine the interaction of gamma rays with matter through the linear attenuation coefficient parameter μ, where, $I$ and $I_0$ are the intensities of gamma rays (incident) and (attenuated).

The mass attenuation coefficient (μ_m) is calculated using the linear attenuation coefficient and density of glass ( ${\mu }_m=\frac{\mu }{\rho }$ ). Accurate values of ( ${\mu }_m$ ) are necessary to give fundamental information in various fields, including radiation protection, radiation dosimetry, and nuclear diagnostics.

The mass attenuation coefficient expresses the probability that incident photons and matter of a given mass per unit area will interact (Saleh et al., 2022). The MAC results plotted against photon energy for all the glasses under study at photon energies ranging from 0.015 to 15 MeV. Fig. 8 shows the relationship between photon energy and Fe₂O₃ concentration variations and the MAC for S1-S5 glasses. Because photons interact with matter through different mechanisms depending on their energy, the MAC increases with increasing concentration of Fe and decreases with increasing photon energy. Compton scattering has the advantage that the probability of the photoelectric effect decreases with photon energy (Al-Hadeethi and Tijani, 2019). Moreover, the ratio of μ_m is observed to decrease very slowly at high energies, depending on the energy of the incident photon and the Fe₂O₃ concentrations.

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Fig. 8

Variation of MAC vs. photon energy for studied glasses.

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3.5.2

3.5.2 Linear attenuation coefficient (LAC)

The relationship between photon energy and variations in Fe₂O₃ concentration and the LAC for S1-S5 studied glasses is depicted in Fig. 9. At low photon energies, the maximum values of μ were observed in all the studied glasses. It was revealed that the μ values were extremely high in S5 glass and extremely low in S1 glass. This is explained by the glass's chemical makeup. In other words, the μ values are raised by the number of components and the atomic numbers of the glass's constituent elements. The highest μ values were found for S5 glass because its constituent elements have the largest atomic numbers (Z = 5, 11, 20, 15, and 26 for B, Na, Ca, P, and Fe, respectively) among all the glasses examined. μ values decrease above 30 keV, and the cross-section in the considered photon energies is determined by the photoelectric absorption, which varies with the photon the Compton scattering is the cause of the observed decrease (Cheewasukhanont et al., 2022).

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Fig. 9

Variation of LAC vs. photon energy for studied glasses.

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3.5.3

3.5.3 Half value layer (HVL), and mean free path (MFP)

HVL is one of the most significant gamma transmission factors in radiation studies and is frequently used to comprehend how various studied glasses interact with gamma rays (Almuqrin et al., 2024; Altowyan et al., 2024; Alomairy et al., 2022). This factor directly indicates the thickness needed to reduce the incident gamma-ray intensity by half. The computed HVL values for the studied glasses under investigation are displayed in Fig. 10. The HVL values increased with photon energy, increased at high photon energies, and decreased with increasing Fe₂O₃ concentrations, suggesting that the synthesized samples' shielding ability was improved. Another gamma transmission factor, MFP, is depicted in Fig. 11. The distance between a photon's subsequent interactions with glass is known as the MFP (Al-Hadeethi et al., 2020). MFP behaves in a way that is comparable to HVL. In other words, a lot of photons with higher energies can flow through the glass. The MFP value decreases with increasing Fe₂O₃ content. According to the study, the MFP value for S5 glass is low.

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Fig. 10

Variation of HVL with photon energy for the studied glasses.

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Fig. 11

Variation of MFP with photon energy for the studied glasses.

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3.5.3.1

3.5.3.1 Atomic cross-section (ACS) and electronic cross-section (ECS)

The cross-section of each atom shows the intensity of the photon beam during transmission for all processes involving photons and absorber atoms. Figs. 12 and 13, respectively, show atomic cross-section σ_a and electronic cross-section σ_e. σ_a increases at low energy regions due to an increase in Fe₂O₃ content and then decreases with increasing photon energy. This is explained by the fact that coherent scattering causes σ_a to be sensitive to interference effects at very low energies. As energy increases, σ_e decreases for all studied glass samples (Jiang et al., 2018). As a result, the photon energy utilized, and the chemical makeup of the material determine the values of σ_a (Prajapati et al., 2019).

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Fig. 12

Variation of ${\sigma }_a$ and ${\sigma }_e$ , respectively vs. photon energy for studied glasses.

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Fig. 13

Variation of ${\sigma }_a$ and ${\sigma }_e$ , respectively vs. photon energy for studied glasses.

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3.5.3.2

3.5.3.2 Effective conductivity C_eff − effective electron density N_eff −and effective atomic number Z_eff

The variation in effective conductivity (C_eff) for each sample of glass is shown in Fig. 14. A photon becomes a free electron when it strikes an electron on glass. Also, a variation in the quantity of free electrons would result in an alteration in the electrical conductivity of the substance (Abdelghany et al., 2022). The effective number of electrons per mole is directly proportional to the effective conductivity C_eff of a shielding material for attenuation. C_eff values decrease quickly as photon energy increases, particularly in the region where photoelectric interactions predominate (ALMisned et al., 2021). This is because C_eff has an inverse relationship with photon energy. Effective electron density (Neff), which is the electron number per unit mass in complex materials, is calculated by dividing the MAC values by the ECS values. N_eff cannot be expressed as a single number, as in pure element atoms at different photon energies. Fig. 15 shows the N_eff values decrease with increasing energy, but they rise with increasing Fe₂O₃. As shown in Fig. 16, the effective atomic number Z_eff was computed using the glass samples' atomic and electric cross sections. At low energy, the glass samples' Z_eff values tend toward higher values. The photoelectric process causes all manufactured glass samples' Z_eff to rapidly decrease to increase incident energy at low gamma-ray energy. Generally, The effective electron density is related to the polarizability and refractive index of the glass. Higher electron density generally leads to higher refractive indices. The variation of effective electron density with composition can be used to design glasses with desired refractive indices for optical applications like lenses, prisms, and fiber optics. Understanding the effective conductivity is important for designing glasses with specific electrical properties, such as high ionic conductivity for solid-state batteries or low electronic conductivity for insulating materials. Moreover, by calculating the effective atomic number of glasses, researchers and engineers can better understand and optimize the radiation interaction properties of these materials, enabling their effective use in various applications ranging from radiation shielding and dosimetry to X-ray and gamma-ray spectroscopy. These relationships are valuable for tailoring glass properties by modifying the composition or processing conditions, as well as for developing new glass compositions with desired characteristics (Rotkovich et al., 2024; Waida and Rilwan, 2024; Alasali et al., 2024).

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Fig. 14

C_eff vs. photon energy for studied glasses.

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Fig. 15

N_eff vs. photon energy for studied glasses.

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Fig. 16

Z_eff vs. photon energy for studied glasses.

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3.5.3.3

3.5.3.3 Exposure buildup factor (EBF) – And energy absorption buildup factor (EABF)

In general, three regions can be distinguished by three distinct incidents in the interactions between the material and energy: the low-energy photoelectric effect, the intermediate-energy region's Compton scattering, and the high-energy pair production. EBF and EABF are the lowest in the low-energy region because of the photoelectric effect process. Due to the Compton scattering effect, the EBF and EABF rise with increasing energies in the more mid-energy region (Abuzaid et al., 2020). Figs. 17 and 18 display the photon energy dependent EBF and EABF, respectively change for the studied glass at 1–40 MFP. The probability of photons interacting with the material in the range of 15–40 MFP varied with Z² after 1 MeV (Kavaz et al., 2020; Ahmed et al., 2024; Rotkovich et al., 2023). As the Fe₂O₃ content increased, the EBF and EABF values decreased as well had were affected by the studied glass's chemical composition, and the S5 sample had the lowest EBF and EABF values.

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Fig. 17

EBF vs. photon energy for studied glasses.

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Fig. 18

EABF vs. photon energy for studied glasses.

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3.6 Correlation between low energy and high energy shielding

While most radiation shielding studies focus on high-energy gamma rays or neutrons, there is a growing need to explore shielding materials for low-energy radiation in the UV and visible ranges. This is particularly relevant for applications such as protective coatings, specialized optics, and shielding in certain instrumentation or sensing devices. The iron-doped soda-lime borophosphate glasses investigated in this study present an opportunity to evaluate their shielding capabilities across a broader energy range, including the UV and visible regions. In addition to the high-energy radiation shielding properties, the attenuation behavior of the iron-doped glasses in the UV and visible range was observed from UV–Vis. Optical absorbance Fig. 4 where the absorbance increases with increasing iron content followed by a decrease in transmittance within the region extended between 200–800 nm. However, the glasses with lower iron oxide concentrations (e.g., 1–4 mol%) exhibit reasonable transmittance in the visible range, making them potential candidates for applications requiring a balance between optical transparency and low-energy radiation shielding.