Chiang Mai Journal of Science

Sustainable Upcycling of Steel Waste into High-Performance LaFeO3±δ Perovskite Gas Sensors

1. INTRODUCTION

     Steel is widely used because of its strength, flexibility, and affordability, making it one of the most important materials worldwide. It plays a key role in construction, automotive manufacturing, machinery, and infrastructure industries. Global production continues to increase, with annual growth rates ranging from 0.7% to 5.7%, depending on the region [1-2]. This growth inevitably generates large amounts of steel-related waste, especially mill scale residues from hot-rolled steel processes. Mill scale is a flaky oxide layer primarily composed of FeO, Fe₂O₃, and Fe₃O₄ that forms during hot rolling and reheating stages of steel production [3]. In addition, hot-rolled steel operations generate various types of solid waste, including offcuts, scrap, and defective parts produced during rolling and shaping. Improper management of these waste materials poses significant environmental risks, including soil and water contamination, airborne particulate emissions, and increased strain on landfill capacity [4]. Furthermore, conventional disposal methods such as landfilling, contribute to greenhouse gas emissions and impose notable economic burdens on steel manufacturers. Despite its prevalence, landfilling remains the dominant waste management strategy in many regions. However, its inefficiencies—both in terms of land use and environmental impact—highlight the urgent need for more sustainable alternatives. These challenges create an opportunity to reframe steel waste not as a burden but as a valuable resource. Transforming steel-related waste into high-value functional materials not only mitigates environmental concerns but also supports circular economic practices by promoting resource recovery and material reuse.
     Several studies have investigated the transformation of industrial by-products into high-value functional materials. For instance, mill scale has been reduced with CO at 750–1050 °C to produce >98% Fe powder for powder metallurgy [5], while other Fe-wastes have been used to create ceramic pigments for Ceramic-clay based products [6], conductive perovskites cathode material for intermediate-temperature solid oxide fuel cells (IT-SOFCs) [7-8], calix[6]arene adsorbents via solvent-free grinding for Cr(III) removal [9], red pigments from ARP waste through rod milling and mixing for coating use [10], and Fe(II) oxalate from steel waste using green methods involving leaching, photoreduction, and hydrothermal processing for pigment and battery applications [11]. Heavy metals (HMs) from industrial smelting waste poses serious environmental challenge by accumulating in soils and entering food crops, and several studies have reported significant health risks in soil–wheat systems due to Cd, Pb, and other contaminants [12]. Notably, iron-rich waste materials such as condensed milk containers have been processed into α-Fe₂O₃ nanoparticle ceramic-pigments through acid leaching, oxidation and calcination steps, achieving controlled nanostructures, high surface areas and ferromagnetic behavior suitable for advanced ceramic applications [13]. These examples highlight the chemical richness of steel waste and its potential as a precursor for synthesis complex oxides such as LaFeO_3±δ perovskite.
     Among advanced functional oxides, perovskite-type compounds such as lanthanum ferrite (LaFeO_3±δ) and Ce-doped LaCoO₃/LaMnO₃ have attracted interest for their excellent electrical conductivity, catalytic activity, and gas-sensing potential, with Ce substitution shown to enhance structural stability and reducibility [14]. The ABO₃-perovskite structure allows flexible doping and oxygen vacancy tuning, which are critical for charge transport and surface reactivity. LaFeO_3±δ is particularly promising because it is a stable p-type perovskite with a suitable band gap (~2.0 eV), tunable oxygen non-stoichiometry (LaFeO_3±δ), and well-documented gas-sensing functionality [15]. Furthermore, LaFeO3 consists of inexpensive and non-toxic elements, making it environmentally benign and suitable for large-scale applications. LaFeO_3±δ-based sensing materials exhibit high sensitivity and selectivity toward various gases, fast response and recovery characteristics, and strong thermal stability, which make them attractive for industrial gas-sensor applications [16, 17]. In addition, the Fe-rich composition of LaFeO₃ allows it to be synthesized from iron-containing industrial wastes, providing an opportunity for sustainable and cost-effective material development.
      To improve properties, numerous doping strategies have been reported. LaFeO₃ doped with alkaline earth metals such as calcium (Ca) and barium (Ba) has shown modified structural, optical, and magnetic properties, reduce band gaps, and enhance photocatalytic activity for environmental applications [18]. Other studies have successfully synthesized LaFeO_3±δ-based perovskites for detecting volatile organic compounds (VOCs) and indoor air pollutants such as formaldehyde and ammonia. For instance, Ag-modified porous LaFeO₃ nanosheets synthesized via a GO-assisted co-precipitation method achieved a high response value (Rg/Ra = 20.9) to 20 ppm ethanol at 180 °C. It also showed rapid response and recovery times (26/27 s) and excellent selectivity toward ethanol, attributed to porous nanostructures and noble metal sensitization [19]. Similarly, perovskite-type LnFeO₃ (Ln = La, Sm, Eu) oxides synthesized via a CTAB-assisted method showed high crystallinity and selectivity, with LaFeO₃, SmFeO₃, and EuFeO₃ responding well to acetone, gasoline, and formaldehyde, respectively [20].
      Other doping strategies have also proven effective. Ni-doped LaFeO₃ synthesized via a one-step hydrothermal method exhibited a significantly improved response of 102 toward 100 ppm at 190 °C, as well as enhanced selectivity and stability. The improved performance was attributed to finer, more porous microsphere structures that facilitated oxygen adsorption and gas diffusion, as well as increased charge carrier concentration from Ni substitution [21]. Molecularly imprinted Ag-LaFeO₃ polymers (ALMIPs) fabricated on fiber templates demonstrated excellent methanol selectivity between 125–175 °C, while showing significantly lower responses to other interfering gases [22]. Rong et al. reported a sensor response of 52.3 for 5 ppm methanol at 155 °C using quasi-molecularly imprinted Ag-doped LaFeO3. This material exhibited excellent selectivity and fast response–recovery times of around 30 seconds [23]. Mo doping material has also demonstrated enhance LaFeO₃'s sensitivity to triethylamine by more than 11 times compared to undoped samples. This highlights the crucial role of dopants in tuning oxygen vacancy concentrations and surface reactivity [24]. Sharma et al. fabricated rGO–LaFeO₃ microsphere-based sensors via photolithography, achieving a 183% response to 3 ppm NO₂ at 250 °C. The performance was attributed to the increased surface area and improved electron transport provided by rGO [25]. Porous spherical LaFeO₃ also showed high sensitivity to NH₃, further emphasizing the role of porosity in enhancing gas adsorption and diffusion [26]. Collectively, these studies emphasize the importance of defect engineering, strategic doping, and nano-morphological control in improving the gas-sensing performance of LaFeO_3±δ-based perovskite materials. However, most synthesis methods still depend on high-purity commercial precursors, which limits cost-effectiveness and scalability. Few studies have explored using or reuse of industrial waste materials for LaFeO₃ synthesis, particularly in developing perovskite incorporating iron oxides derived from waste and evaluating their performance in gas-sensing applications.
     This work presents a novel approach to synthesizing LaFeO_3±δ-based perovskite materials using iron oxide recovered from steel waste. Unlike previous reports based on high-purity commercial chemicals, this method offers a cost-effective and sustainable synthesis pathway aligned with circular economic principles. The synthesis was carried out through mechanochemical milling followed by high-temperature calcination. Structural, chemical and morphological properties were examined by XRD, XRF, PSD and SEM. Gas-sensing performance was evaluated under controlled exposure to combustion gases. The findings confirm the feasibility of using steel waste as a precursor for advanced sensor materials and highlight its potential for developing environmentally responsible functional materials.

2. MATERIALS AND METHODS

2.1 Steel Waste Preparation
     Two types of steel waste such as mill scale and hot-rolled steel sludge were utilized as starting precursors. Both materials were initially characterized using X-ray diffraction (XRD) before and after preliminary treatment to determine their phase compositions.
     For mill scale waste, the treatment involved two main steps. First, the material was cleaned with distilled water to remove surface contaminants, followed by magnetic separation to isolate ferromagnetic particles. The cleaning step generated only a small amount of suspended dust particles, which were removed with the washing water; these particles are inert and do not pose significant environmental impact. The separated material was oven-dried at 100 °C for 24 h and sieved to a uniform particle size below 45 µm (325 mesh). Second, Fe₃O₄ was converted into Fe₂O₃ through calcination in an electric ceramic furnace at 700 °C for 2 h. This step produced no additional solid residues or toxic gases, as it involved only oxygen release and phase transformation. After calcination, the material was sieved again to ensure uniformity below 45 µm. From 1 kg of mill scale powder, approximately 0.90–0.95 kg of Fe₂O₃ was recovered, corresponding to a yield of 90–95%.
     Hot-rolled steel waste was obtained from the hydrochloric acid regeneration process in hot-rolling operations, where the dissolved iron in spent acid had been recovered and converted into Fe₂O₃ through upstream recycling process [27]. In this study, the preparation consisted only of washing with distilled water to remove possible surface contaminants from storage, followed by drying at 100 °C for 24 h and sieving to below 45 µm. Calcination was not required. Consequently, the process resulted in the absence of additional solid waste and hazardous by-products. The effective recovery efficiency was approximately 0.98–1.00 kg of Fe₂O₃ per 1 kg of hot-rolled steel waste, equivalent to 98–100% yield.
     Both treated waste powders were subsequently analyzed using X-ray diffraction (XRD) and X-ray fluorescence (XRF) to confirm their crystalline phases and chemical compositions prior to LaFeO_3±δ perovskite synthesis.

2.2 Synthesis of LaFeO3±δ-based Perovskite Materials
     LaFeO_3±δ was synthesized using Fe₂O₃ obtained from processed steel waste and high-purity lanthanum (III) oxide (La₂O₃) in a 1:1 molar ratio. Ethanol was used as the mixing medium. The powders were ball-milled for 8 h to ensure uniform mixing, dried at 100 °C and sieved to obtain a particle size below 45 µm. The dried mixture was then calcined at 1200 °C for 2 h to form the perovskite phase. After calcination, the powder was ground and sieved again to below 45 µm, and its phase was confirmed by X-ray diffraction (XRD). The resulting powders were then pressed into compacted workpieces (7 mm × 32 mm × 4 mm) using a hydraulic press at a pressure of 2 MPa and sintered at 1200 °C for 2 h. The final sintered materials underwent detailed characterization to evaluate their microstructure, gas adsorption behavior, and electrical resistivity. The oxygen content (δ) in LaFeO_3±δ depends on the firing atmosphere, sintering temperature, and heating/cooling profile. Deviations from ideal oxygen stoichiometric (δ ≠ 0) composition occur when oxygen vacancies or, in some cases, oxygen interstitials form in the lattice. At high temperatures (1200–1300 °C), oxygen can escape from the structure, especially under low oxygen partial pressure, leading to oxygen-deficient LaFeO_3−δ. In contrast, oxygen-rich atmospheres may introduce excess oxygen and form LaFeO_3±δ. Under the synthesis conditions used here, which involved calcination in ambient air, the material generally forms as slightly oxygen-deficient LaFeO_3−δ. The small deviation from stoichiometry results from the high temperature and the limited oxygen chemical potential in air. This intrinsic non-stoichiometry can influence the electrical conductivity and gas-sensing performance LaFeO₃-based materials [28, 29]. Although LaFeO_3−δ usually shows higher resistivity due to the presence of oxygen vacancies, oxygen-rich LaFeO_3+δ can also exhibit increased resistivity. In this case, excess oxygen does not create vacancies but can enter interstitial sites or accumulate at grain boundaries. These additional oxygen species may trap charge carriers or distort the Fe–O–Fe network, decreasing carrier mobility. Such behavior has been reported in perovskite oxides containing interstitial oxygen [30–32]. In this study, δ was not intentionally controlled beyond normal processing in air. Future studies may precisely adjust δ through post-annealing under controlled atmospheres, such as pure O₂, ozone, or low-oxygen environments. Techniques such as thermogravimetric analysis (TGA), iodometric titration, or synchrotron-based X-ray absorption spectroscopy (XAS) can be used to quantify oxygen non-stoichiometry [33]. The focus of the present work was to demonstrate that steel industrial waste can be successfully processed into LaFeO_3±δ with the correct perovskite phase formation.

2.3 Characterizations and Properties test
     Phase analysis was performed using X-ray diffraction (XRD, Bruker D2 PHASER) over a 2θ range of 10–80°, with a step size of 0.02° and a total scan time of 30 min. To verify the phase composition, elemental analysis was performed using X-ray fluorescence spectroscopy (XRF, Horiba XGT-5200). Particle size distribution (PSD) was measured using a laser diffraction analyzer (Horiba LA-950V2), with distilled water as the dispersion medium. To ensure uniform dispersion and reduce particle agglomeration, the samples were ultrasonicated for 2 min before testing. The refractive indices used in the calculations were 3.010 for Fe₂O₃, 2.440 for LaFeO_3±δ, and 1.333 for water. The instrument was calibrated to ensure accurate PSD result for both raw and synthesized powders. The gas-sensing performance of the LaFeO_3±δ-based perovskite materials was evaluated using the four-point DC method under controlled laboratory conditions. All measurements were conducted at a fixed operating temperature of 200 °C to activate the charge transport processes within the samples. The bulk density of the sintered LaFeO_3±δ ceramics was measured using the Archimedes’ principle, which is based on buoyant force when the specimen is submerged in water. The density (ρ_b) was calculated using Eq. 1:

ρ_b = (W_f x ρ_L)/(W_s-W_ss)                                        (Eq. 1)

     where Wf is the dry weight (g), W_s is the saturated weight after water filled the open pores (g), W_ss is the suspended weight in water (g), and 𝜌_𝐿 is the density of water (1.0 g/cm³ at room temperature). This method provides a reliable estimate of the effective volume of the sample, giving an accurate bulk density. Higher density indicates better grain packing, lower porosity, and improved functional properties such as electrical conductivity and gas-sensing behavior.  
     Microstructure characterization was performed using scanning electron microscopy (SEM, JEOL JCM-5000). The analysis provided information on particle morphology, porosity, and surface features that influence gas diffusion and adsorption. SEM imaging was carried out at a magnification of 3000× with an accelerating voltage of 15 kV and a working distance of 15 mm. Before imaging, all samples were sputter-coated with a thin layer of gold to improve surface conductivity and image clarity.
     The evaluation process consisted of three stages:
     Stage 1 involved precise measurement of each sample pellet’s physical dimensions, including the cross-sectional area (A) and the distance (L) between the two inner voltage probes. These parameters were required for calculating electrical resistivity (ρ). The measurement setup was placed inside a sealed chamber to minimize the influence of ambient oxygen and humidity.
     Stage 2 focused on heating the sample to 200 °C. Once thermal stabilized, the electrical voltage (V) and resistance (R) were recorded every minute for five minutes before gas exposure. These values were used to calculate the electrical resistivity (ρ) using Eq. 2:

ρ = R·A/L                                                       (Eq. 2)

     where R is the electrical resistance, A is the cross-sectional area, and L is the distance between voltage probes.
     Stage 3 simulated combustion conditions were created by burning agricultural waste in a combustion chamber (Box 1) to generate test gases. The resulting gases mainly consisted of CO, CO₂, CH₄, and NO₂ [34]. These gases were used to evaluate the gas sensing performance of the LaFeO3±δ-based materials. The atmosphere ranged from reducing to partially oxidizing because of limited oxygen availability. The gases were directed into the measurement chamber (Box 2) through a controlled valve system. Electrical resistance and voltage were recorded every minute for five minutes to capture the response of the material to gas exposure. The sensor signal (S), a key indicator of gas detection sensitivity was calculated using Eq. 3:  

S = ρgas/ρair                                                (Eq. 3)

    Where ρgas is the resistivity after gas exposure and ρair is the resistivity before exposure. All measurements were performed in triplicate to ensure reproducibility among samples prepared from different precursor sources. The overall experimental workflow, from waste treatment and purification to synthesis of LaFeO3±δ, is shown in Figure 1.

3. RESULTS AND DISCUSSION

3.1 Initial Characterization of Iron-rich Waste
     Iron-rich industrial wastes, such as mill scale and hot-rolled steel waste (HRSW), are generated in large quantities as by-products of steel production processes. Often underutilized, these materials can pose environmental challenges. However, when appropriate recovery and purification methods are applied, these wastes can be transformed into value-added materials supporting circular-economic strategies and sustainable industrial practices. Mill scale forms naturally on the surface of steel during hot rolling at high temperatures (approximately 900-1200 °C). At these temperatures, exposure to atmospheric oxygen results in the formation of a mixture of iron oxides (FeO, Fe₂O₃, and Fe₃O₄) resulting in a dark gray to black flaky scale that loosely adheres to the steel surface. In contrast, hot-rolled steel waste originates from the regeneration of spent hydrochloric acid used during the steel soaking process, containing a high concentration of dissolved iron. Recovery was performed by neutralizing the acidic solution with 2 M NaOH to pH 7, which induced the precipitation of iron species. Hydrogen peroxide (H₂O₂) was then added to oxidize ferrous ions (Fe²⁺) to ferric ions (Fe³⁺) via a Fenton-type reaction in Eq. 4:

2Fe²⁺ + H₂O₂ + 2H⁺ → 2Fe³⁺ + 2H₂O                          (Eq. 4)

     This reaction confirms that H₂O₂ acted as a strong oxidizing agent, enabling complete oxidation of Fe²⁺ to Fe³⁺ during the waste treatment process [35]. The resulting precipitate is then filtered and calcined at 700 °C for 2 h to produce hematite (Fe₂O₃). Although both waste types ultimately yield Fe₂O₃ as a primary component, they differ markedly in their origin, composition, and treatment processes, giving each material distinct characteristics that may influence subsequent applications. As such, both represent promising starting materials for the development of functional iron-based products.
     X-ray diffraction (XRD) was used to analyze two types of iron-rich industrial waste, namely mill scale and hot-rolled steel waste, as shown in Figure 2. The data shown correspond to the samples before any cleaning or treatment processes. The XRD patterns clearly show the presence of different crystalline phases, indicated by blue triangles and green diamonds. The dominant phase in both materials is hematite (Fe₂O₃), confirmed by the strong and numerous peaks (marked by blue triangles) that match the standard reference pattern (JCPDS no. 89-0596) for rhombohedral Fe₂O₃ (space group R-3c, no. 167). The nine most intense diffraction peaks appear at 2θ values of 24.13°, 33.12°, 35.62°, 40.84°, 49.43°, 54.01°, 57.51°, 62.40°, and 63.98°, corresponding to the (012), (104), (110), (113), (024), (116), (122), (214), and (300) planes, respectively. Both waste types contain a high concentration of Fe₂O₃, reaffirming their potential for recovery and reuse.

      However, a key difference emerges from the XRD analysis, the hot-rolled steel waste exhibits a single-phase pattern consisting solely of Fe₂O₃, indicating a more uniform and purer oxide composition. In contrast, the mill scale waste contains a minor secondary phase identified as magnetite (Fe₃O₄) (JCPDS no. 65-3107), which appears as six additional peaks at approximately 2θ values of 18.30°, 30.10°, 35.46°, 43.09°, 56.98°, and 62.58°. Quantitative analysis using the TOPAS method estimates that Fe3O4 accounts for approximately 32% of the mill scale composition. The presence of this secondary phase suggests that partial oxidation occurred during high-temperature steel processing, resulting in a mixture of iron oxides in the mill scale waste. The term "partial" is used because oxidation did not fully progress to a single stoichiometric oxide, which accounts for the coexistence of FeO, Fe₂O₃, and Fe₃O₄, rather than a complete transformation into Fe₂O₃ [5]. No reduction occurs during this process. This distinction, the presence of magnetite in mill scale but not in HRSW waste, is an important factor differentiating the two materials. Overall, both waste types contain valuable Fe₂O₃ phases and exhibit strong potential for reuse as purified iron-based compounds.
      Two types of high-iron industrial waste, mill scale and hot-rolled steel waste (HRSW), were subjected to a waste management process aimed at purification and separation. The treatment began with a necessary cleaning step to remove residual oil, dust, and particulate contaminants often present from storage in uncontrolled environments. The material was then sieved (using a 325-mesh screen, 45 µm) to isolate fine iron particles. For mill scale, which initially contained the primary phases hematite (Fe₂O₃) and magnetite (Fe₃O₄), magnetic separation was applied to distinguish between component, The non-magnetic fraction MSW, which settled at the bottom, in Figure 3 was confirmed by XRD to contain only a single Fe₂O₃ phase (JCPDS No. 89-0596).The magnetic fraction MSMW} was found to contain a mixture of both Fe₂O₃ and Fe₃O₄ (JCPDS Nos. 89-0596 and 65-3107), likely due to fine magnetite particles adhering to or agglomerating around larger particles during separation. Although HRSW had shown pure Fe₂O₃ in the initial XRD analysis, it still underwent the same cleaning and screening procedures to ensure the material was free from external contamination (dust, water, or oil residues) and suitable for use as a precursor in the synthesis of gas-sensing materials. Consequently, the two treated waste types, MSW and HRSW, are composed entirely of pure Fe₂O₃.
     To enable the full reuse of all waste fractions and support sustainable practices, the MSMW (mixture of Fe₂O₃ and Fe₃O₄) was subjected to heat treatment to convert the Fe₃O₄ into the complete form of Fe₂O₃. According to the theoretical Fe-O binary system phase diagram (Figure 4), Fe₃O₄ can be completely transformed into Fe₂O₃ through thermal treatment at a minimum temperature of approximately 700 °C. Before calcination, the XRD pattern of MSMW (top graph, Figure 4) shows the presence of both Fe₂O₃ and Fe₃O₄. After heat treatment at 700 °C, the complete conversion of Fe₃O₄ to Fe₂O₃ is confirmed by the disappearance of all Fe3O4 peaks and the persistence of only Fe2O3 peaks, consistent with the oxidation reaction in Eq. 5:

4Fe₃O₄ + O₂ → 6Fe₂O₃                                      (Eq. 5)

     These results demonstrate that the calcination conditions were effective in achieving complete phase transformation of MSMW waste, producing high-purity Fe₂O₃ suitable for use as a precursor in the synthesis of LaFeO_3±δ-based materials. In addition, the observed non-linear and high background intensity in the XRD pattern of calcined MSMW may be attributed to X-ray scattering and fluorescence effects caused by the high concentration of heavy metal oxides (such as iron oxides). Heavy elements strongly absorb and re-emit X-rays, leading to increased background and non-linear intensity. Since absorption and fluorescence correction settings were not specifically optimized for these samples, this may have further contributed to the elevated background signal [36].
     Chemical composition analysis was also performed using X-ray fluorescence (XRF). The results showed that, prior to cleaning, mill scale waste and hot-rolled steel waste contained high iron (Fe) contents of 90.76% and 96.10%, respectively. Other oxides such as SiO₂, Al₂O₃, Cr₂O₃, MnO₂, and CuO were present in amounts ranging from 3.90%-9.24%. These elements are typically introduced into steel during production to enhance properties such as hardness, corrosion resistance, and fluidity, as summarized in Table 1. Following the cleaning process and magnetic separation, the iron content increased significantly in all samples. Specifically, the Fe content in non-magnetic mill scale (MSW), magnetically separated mill scale (MSWM), and hot-rolled steel waste (HRSW) rose to 94.01%, 93.64%, and 96.52%, respectively. This improvement reflects the effectiveness of the waste treatment process in removing contaminants introduced during production and storage, including dust, fine powders, water, and oil residues. These findings confirm that iron-rich industrial wastes possess sufficiently high Fe content to be considered suitable starting materials for the synthesis of perovskite-type materials with the general formula LaFeO_3±δ.

     The microstructure of raw wastes such as MSW, MSWM, HRSW, and Fe₂O₃ chemical compound, was examined using scanning electron microscopy (SEM) and quantified using ImageJ software with Martin’s diameter technique [37-38]. Mill scale waste (MSW) exhibited an average particle size of 7.44±0.33 µm (Figure 5(a)). Magnetically separated mill scale, subsequently sintered at 700 °C (MSWM), showed a slightly smaller average size of 6.01±0.34 µm (Figure 5(b)). Both MSW and MSWM displayed roughly rectangular morphology with similar dimensions. In contrast, hot-rolled steel waste (HRSW) exhibited a much finer average particle size of 0.11±0.21 µm with a near-spherical morphology (Figure 5(c)). Fe₂O₃ obtained from pure chemical precursors showed an average particle size of 0.32±0.26 µm with a needle-like morphology (Figure 5(d)). These particle sizes influence the grain size of the sintered LaFeO_3±δ materials, thereby affecting their gas adsorption and sensing performance.

3.2 Synthesis and Characterization of LaFeO_3±δ-based Perovskite Structures
     LaFeO_3±δ (LFO) powders were synthesized using the solid-state reaction, employing Fe₂O₃ as the starting material sourced from four different origins: non-magnetic mill scale waste (LFO-MSW), magnetically separated mill scale waste (LFO-MSMW), hot-rolled steel waste (LFO-HRSW), and high-purity laboratory-grade chemicals (LFO-Chem) for comparison. All samples were calcined at 1200 °C and subsequently analyzed for phase composition using X-ray diffraction (XRD), as shown in Figure 6. The results revealed that Fe₂O₃ compounds purified from all three types of industrial waste were successfully used as precursors for the complete synthesis of LaFeO_3±δ, comparable to those derived from laboratory-grade chemicals. XRD analysis confirmed the formation of a single-phase LaFeO_3±δ structure in all samples, consistent with the standard JCPDS No. 37-1493. The material exhibited an orthorhombic crystal structure with space group Pnma (No. 62). From the diffraction patterns, the first seven prominent peaks appeared at 2θ values of 22.61°, 32.19°, 39.67°, 46.14°, 57.40°, 67.35°, and 76.64°, which were identical across all samples. This strong agreement in peak positions and intensities indicates that complete solid-state reaction between La₂O₃ and Fe₂O₃ proceeded to completion regardless of the Fe₂O₃ source. These findings demonstrate that high-iron industrial waste can serve as a viable and sustainable raw material for synthesizing high-purity LaFeO_3±δ perovskite oxide materials, offering an eco-friendly alternative to conventional chemical precursors.

     Particle size Distribution (PSD) of the synthesized LaFeO_3±δ powders is shown in Figure 7. The average particle size (D50) values and distribution ranges (D10–D90) were obtained for each sample. The LaFeO_3±δ from hot-rolled steel waste (LFO-HRSW) had the smallest average particle size of 4.08±0.46 µm, with a broad distribution of 2.32–28.48 µm and two distinct peaks, indicating that very fine particles tend to agglomerate. In addition, LaFeO_3±δ from non-magnetic mill scale (LFO-MSW exhibited a slightly larger average size of 6.31±0.12 µm with a narrower distribution range of 2.16–21.26 µm. In contrast, LaFeO_3±δ from magnetically separated mill scale (LFO-MSWM) was coarser at 8.61±0.21 µm and a broader range of 3.89–42.82 µm, likely due to calcination at 700 °C that promoted particle growth. LaFeO_3±δ synthesized from chemical-grade iron oxide (LFO-Chem) exhibited an average particle size of 7.70±0.21 µm with a distribution range of 2.70–39.31 µm. These results confirm that both precursor type and thermal history strongly affect the average particle size and the distribution of LaFeO_3±δ powders.

3.3 Characterizations and Properties test of LaFeO3±δ Perovskite Specimens
3.3.1 Density of LaFeO_3±δ-based perovskite materials
     The density of the sintered LaFeO3±δ samples was determined using Archimedes’ principle, as presented in Figure 8. The measured density values were 3.85±0.36 g/cm³ for LFO-MSW, 3.33±0.56 g/cm³ for LFO-MSWM, 4.34±0.59 g/cm³ for LFO-HRSW, and 3.66±0.09 g/cm³ for LFO-Chem. Using the theoretical density of 6.64 g/cm³ calculated from XRD unit-cell parameters, the corresponding relative densities were estimated as 57.98% (LFO-MSW), 50.15% (LFO-MSWM), 65.36% (LFO-HRSW), and 55.12% (LFO-Chem). The calculated porosities were 43.50%, 42.37%, 43.39%, and 51.31%, respectively, as illustrated in Figure 9, indicating that all samples exhibit significant porosity.

     Among the samples, LFO-HRSW exhibited the highest relative density (65.36%) and lowest porosity (43%), suggesting the most compact microstructure. In contrast, LFO-Chem showed the lowest relative density (55.12%) and the highest porosity (51.31%), reflecting a more open structure. LFO-MSW and LFO-MSWM samples showed intermediate densities and comparable porosities around 42–44%. These differences are attributed to variations in synthesis routes and sintering efficiency, which affect the reduction of interparticle voids. Sample density is a critical factor for gas-sensing performance in perovskite-based materials. Higher density generally reduces the porosity and the available surface area, limiting gas adsorption and hindering gas diffusion within the material. Conversely, lower-density samples tend to have higher porosity and larger surface area, which facilitates gas diffusion and interaction with the sensing sites, thereby enhancing sensitivity and response speed. Therefore, controlling the density of LaFeO_3±δ is essential for optimizing gas-sensing properties [39-40].
     Porosity strongly affects gas-sensing behavior. Highly porous samples (e.g. LFO-Chem, LFO-MSWM) provide larger specific surface areas and more adsorption sites, favoring gas interaction and potentially enhancing gas-sensing sensitivity [18, 41]. However, excessive porosity may disrupt conduction pathways, increase grain boundary resistance, and limit electronic transport. Denser samples (e.g. LFO-HRSW) restrict gas diffusion due to lower porosity but offer better grain connectivity and improved electrical conductivity, which can enhance sensing performance. Overall, relative densities between 50–65% achieve a balance between surface activity and electrical transport. The high density and superior gas response of LFO-HRSW suggest that an optimal combination of porosity and compactness, rather than maximum porosity alone, governs the sensing behavior of LaFeO_3±δ ceramics.

3.3.2 Microstructure of LaFeO_3±δ-based perovskite materials
     The microstructure of LaFeO_3±δ materials made from four different starting materials such as LFO-MSW, LFO-MSWM, LFO-HRSW, and LFO-Chem, was studied using scanning electron microscopy (SEM) at 3000x magnification. As shown in Figure 10(a–d), all samples showed tightly packed grains with visible pores on the surface. These features are characteristic of materials prepared via solid-state synthesis followed by high-temperature sintering, which promotes grain growth and partial coalescence.

     Among the four samples, LFO-HRSW (Figure 10(c)) displayed the smallest and most uniformly distributed grains. Its grain and pore sizes were notably smaller and more homogeneous than those of the other samples. This observation is consistent the grain size measurements obtained using ImageJ software, which indicated av average grain size of 0.31 µm for LFO-HRSW. For comparison, LFO-MSW, LFO-MSWM, and LFO-Chem exhibited average grain sizes of 0.36 µm, 0.37 µm, and 0.42 µm, respectively. A similar trend was observed for pore size, where LFO-HRSW had the smallest average pore diameter (0.36 µm), and LFO-Chem the largest (0.57 µm). LFO-MSW and LFO-MSWM had average pore diameters of 0.48 µm and 0.51 µm, respectively.
     The measured densities of the sintered LaFeO_3±δ samples correlate strongly with the SEM-observed microstructures. Samples with lower relative density and higher porosity, such as LFO-MSW and LFO-MSWM, exhibited larger, less uniform grains and pores, indicating their more open structures. In contrast, LFO-HRSW, with possessed the highest relative density (65.36%) and lowest porosity (43.39%), displayed the smallest and most uniformly distributed grains and pores. This compact and uniform microstructure facilitates efficient charge transport while still allowing gas molecules to diffuse effectively through fine pores. Consequently, the combination of high density, small grain size, and well-distributed porosity explains the superior gas-sensing performance of LFO-HRSW, highlighting the close relationship between density, porosity, microstructure, and sensor response in LaFeO_3±δ ceramics.
     Overall, LFO-HRSW exhibited the most favorable microstructure for gas sensing. Its small, uniform grains and fine pores enhance the adsorption of gas molecules on the surface, enhancing the sensor’s sensitivity and reducing its response time. Furthermore, the well-distributed pore structure promotes efficient gas diffusion, allowing target molecules to reach active sites more efficiently.

3.4 Electrical Characterization of LaFeO3±δ-based Perovskite Materials
      The electrical properties of LaFeO_3±δ-based perovskite (LFO) materials synthesized from industrial steel wastes and laboratory-grade precursors were evaluated to assess their suitability for gas sensing applications. Electrical resistance measurements were performed using the four-point DC method under baseline air conditions and during exposure to the target gas, enabling direct comparison of sensor performance across material types.

3.4.1 Electrical resistance behavior of LaFeO3±δ-based perovskite materials under baseline and gas-exposed conditions
     The electrical resistivity (ρ) of LaFeO_3±δ materials synthesized from different Fe₂O₃ precursors was measured using a four-point DC method. As presented in Figure 11, LFO from mill scale waste (LFO-MSW) exhibited a ρ_air of 22.79 Ω·m, increasing to 33.90 Ω·m upon gas exposure. For LFO separated mill scale (LFO-MSWM), electrical resistivity increased from 19.88 Ω·m to 33.25 Ω·m. The hot-rolled steel waste (LFO-HRSW), the values changed from 19.56 Ω·m to 32.02 Ω·m. The chemically synthesized sample (LFO-Chem) showed the lowest resistivity values, with ρ_air at 18.98 Ω·m and also showed the lowest ρ_gas at 27.60 Ω·m.

     Electrical resistivity was measured under two conditions: before gas exposure (ρ_air) and during gas exposure (ρ_gas). Prior to gas introduction, samples were thermally activated at 200 °C to promote charge transport. Thermal activation facilitates the formation of hole (h⁺) charge carriers, consistent with the characteristic p-type semiconductor behavior of LaFeO_3±δ. Conductivity is governed by thermally assisted small-polaron hopping between neighboring Fe³⁺/Fe⁴⁺ sites via Fe–O–Fe bridges, and is strongly influenced by intrinsic defect chemistry, particularly oxygen vacancies [25]. Upon gas exposure, oxygen species (O⁻, O²⁻, O₂⁻) adsorb on the surface and may diffuse into near-surface regions, where they fill oxygen vacancies or occupy interstitial positions. These species withdraw electrons or trap hole carriers, thereby reducing the effective hole concentration and increasing electrical resistivity. As a p-type semiconductor, LaFeO_3±δ primarily relies on holes as the dominant charge carriers; thus, any reduction in hole concentration directly increases resistivity (ρ_gas). While defect-induced lattice distortions may cause minor reductions in carrier mobility, this effect is secondary. The dominant contribution to the increase in ρgas arises from the reduction in effective hole concentration due to defect-mediated hole trapping. In this study, the electrical resistivity (ρ) of LaFeO_3±δ increases primarily due to a reduction in hole carrier concentration, the dominant charge carriers in these p-type semiconductors. Oxygen vacancies, present in the oxygen-deficient LaFeO_3−δ phase, disrupt the Fe3+/Fe4+ small-polaron hopping pathways, thereby lowering the number of available holes. Upon exposure to gases, surface-adsorbed oxygen species (O⁻, O²⁻, O₂⁻) further trap holes or withdraw electrons, which reduces the effective hole concentration and increases resistivity. Defect-induced lattice distortions may slightly reduce carrier mobility, but this effect is secondary. Therefore, the observed resistivity increase is mainly controlled by changes in carrier concentration rather than mobility [30-31]. This explanation is consistent with reports that LaFeO₃ calcined in ambient air typically forms an oxygen-deficient phase (LaFeO_3−δ), as oxygen vacancies are thermodynamically favored under the synthesis conditions used. These vacancies modify Fe oxidation states, interrupt polaron hopping pathways, and thus increase resistivity. Conversely, excess-oxygen compositions (LaFeO_3+δ), which introduce interstitial oxygen and additional trapping sites, form only under strongly oxidizing conditions that were not present in this work. Therefore, the resistivity behavior observed here is most reasonably attributed to an oxygen-deficient LaFeO_3−δ composition. The difference between the material’s resistivity in air (ρ_air) and under gas exposure (ρ_gas) serves as a key indicator of gas-sensing performance. A larger gap between ρair and ρgas suggests better gas detection capability, as it reflects the material’s strong response to gas absorption. Based on the magnitude of the resistivity shift, the materials can be ranked by their sensitivity based on the magnitude of this resistivity change as follows: LFO-MSWM shows the highest difference, followed by LFO-HRSW, LFO-MSW, and finally LFO-Chem. This result highlights the promising potential of waste-derived materials, particularly LFO-MSWM, for use in gas-sensing applications.

3.4.2 Sensor signal analysis of synthesized LaFeO_3±δ-based perovskite materials
     The sensor signal (S), defined as the ratio of electrical resistivity during gas exposure (ρ_gas) to that in ambient air (ρ_air), was used to evaluate the gas-sensing response of the synthesized LaFeO_3±δ-based perovskite materials. This parameter serves as a key indicator of gas detection sensitivity and overall sensor performance. The sensor signal was calculated according to Eq. 3. Measurements were performed using the four-point DC method over a five-minute period, with data collected at one-minute intervals at a constant operating temperature of 200 °C.
     The gas-sensing measurements were performed on five independent samples (n = 5) for each material to ensure reproducibility. LFO-MSWM exhibited the highest average sensor signal value of 1.67±0.32, followed by LFO-HRSW (1.64±0.54), LFO-MSW (1.49±0.21), and LFO-Chem (1.45±0.41), as shown in Figure 12 with error bars representing the standard deviation. For all samples, the sensor signals gradually increased over time, indicating continuous adsorption of combustion-generated gas molecules onto the perovskite surface. This adsorption enhances charge-carrier scattering, resulting in higher resistivity.
     The pronounced response of LFO-MSWM from ρ_air = 19.88 Ω·m to ρ_gas = 33.25 Ω·m, is attributed to its favorable microstructure and efficient gas–solid interaction. A similar trend was observed for LFO-HRSW, which showed a comparable shift in resistivity (from 19.56 Ω·m to 32.02 Ω·m) and sensor signal, reinforcing the performance benefits associated with waste-derived precursors.
     In contrast, LFO-Chem synthesized from high-purity reagents exhibited the lowest sensor signal. Although it demonstrated good baseline conductivity (ρ_air = 18.98 Ω·m), its smaller resistivity change during gas exposure (ρ_gas = 27.60 Ω·m) suggests weaker surface interaction with gas molecules, possibly due to a lower defect density or less reactive surface chemistry. Mechanistically, the observed increase in ρ_gas for all samples is consistent with the p-type semiconducting behavior of LaFeO_3±δ. Both LaFeO_3+δ and LaFeO_3−δ typically exhibit p-type conductivity under most synthesis conditions. In LaFeO_3−δ, oxygen vacancies create hole carriers that dominate conduction, while in LaFeO_3+δ, Fe⁴⁺ formation under oxygen-rich conditions also results in p-type behavior. N-type conductivity may occur only under strongly reducing environments, which are not relevant to the present synthesis [30]. Oxidizing gases such as CO₂ or NO_x act as electron acceptors when adsorbed onto the surface, reducing the concentration of mobile holes and lowering conductivity. This reduction in charge-carrier density leads to a measurable rise in resistivity, reflected in the sensor signal.

     LFO-MSWM shows a slower gas response compared to LFO-HRSW. When evaluating gas detection performance, the speed at which the sensor signal stabilizes following gas exposure is critical. The graph shows that the sensor based on LFO-HRSW responds rapidly, with the signal stabilizing within just 2 minutes. After this point, the curve becomes linear, indicating a steady and an essential characteristic of an effective gas sensor. In contrast, the signal of LFO-MSWM remains unstable signal even after 5 minutes, suggesting a slower response time. Although LFO-MSWM exhibits slightly higher overall sensor-signal values, its slower stabilization and lower sensitivity make it less suitable for applications requiring rapid gas detection.
    In summary, LFO-HRSW emerges as the more promising candidate for gas-sensing applications, offering a combination of fast response time, good sensitivity, and high overall efficiency. These characteristics are essential for reliable and high-performance gas-sensor materials, positioning LFO-HRSW as a strong contender for practical implementation.

4. CONCLUSIONS

     This study successfully synthesized LaFeO_3±δ perovskite materials using iron oxide recovered from steel industry waste. Four types of samples were prepared: LFO-MSW, LFO-MSWM, LFO-HRSW, and LFO-Chem. Among these, LFO-HRSW exhibited the most favorable microstructure and gas-sensing performance.
     SEM analysis revealed that LFO-HRSW had the smallest average grain size (0.31 µm) and the finest average pore diameter (0.36 µm), resulting in increased surface area for gas adsorption. Particle size distribution confirmed its fine powder characteristics. Bulk density measurements showed that LFO-HRSW had the highest relative density (65.36%) and the lowest porosity (43.39%), suggesting a compact microstructure that supports efficient charge transport.
     Gas-sensing tests conducted at 200 °C demonstrated that LFO-HRSW achieved a stable sensor signal within just 2 minutes, with an average value of 1.64. Its electrical resistivity increased from 19.56 Ω·m in air to 32.02 Ω·m under gas exposure, confirming effective gas adsorption and strong sensor response. In comparison, LFO-MSW and LFO-MSWM showed lower density and slower response times, while LFO-Chem, despite high purity, exhibited the lowest sensor signal.
     Overall, LFO-HRSW stands out as a suitable candidate for high-performance, low-cost gas sensors derived from recycled steel waste. The study highlights the feasibility of transforming industrial iron-rich waste into valuable functional materials, contributing to sustainable material development and circular economy practices. This approach provides potential benefits for environmental monitoring and industrial emission control.

ACKNOWLEDGEMENTS

     This research was financially supported by the Suranaree University of Technology Research and Development Fund. We express gratitude to Suranaree University of Technology (SUT) for facilitating a portion of the research.

AUTHOR CONTRIBUTIONS

     Siriwan Chokkha contributed to the writing of the article, Literature review, Designed- performed the experiment, Tester and analyzed the results.
     Phawaran Phinyosri contributed to Tester and Literature review.
     Atittacha Rosungnoen, Mawadee Kerdmuenwai and Methawee Khomorakha contributed to Tester.

CONFLICT OF INTEREST STATEMENT

     The authors are required to declare whether or not they hold any conflicting interests.

DECLARATION OF USE OF GENERATIVE AI

     During the preparation of this manuscript, the author used ChatGPT (OpenAI, GPT-5.0) for preliminary assistance with English language editing, including grammar and sentence clarity. The author subsequently reviewed, revised, and finalized the manuscript to ensure accuracy, coherence, and originality of the content. All interpretations, analyses, and conclusions presented in this work are the sole responsibility of the author.

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