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  <front>
    <journal-meta>
      <journal-title-group><journal-title>Research and Reviews in Sustainability</journal-title></journal-title-group>
      <issn pub-type="epub">2977-8441</issn>
      <publisher><publisher-name>Caravel Press</publisher-name></publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.65582/rrs.2026.005</article-id>
      <article-id pub-id-type="publisher-id">2026.005</article-id>
      <title-group><article-title>Comparative Analysis of PVA-bonded Oil Palm Trunk and Rubberwood Composite Boards with NaCl and CaCO3 Additives</article-title></title-group>
    <contrib-group>
      <contrib contrib-type="author" corresp="yes">
        <name><surname>Yusof</surname><given-names>Madihan</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <xref ref-type="aff" rid="aff2"/>
        <email>madihan@uts.edu.my</email>
      </contrib>
      <contrib contrib-type="author">
        <contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-2937-4295</contrib-id>
        <name><surname>Lamaming</surname><given-names>Junidah</given-names></name>
        <xref ref-type="aff" rid="aff3"/>
        <email>lajunidah@unimas.my</email>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Sulaiman</surname><given-names>Mohamad Saiful</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <xref ref-type="aff" rid="aff2"/>
        <email>saiful.sulaiman@uts.edu.my</email>
      </contrib>
      <contrib contrib-type="author">
        <contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0015-5606</contrib-id>
        <name><surname>Mohd Ghani</surname><given-names>Ros Syazmini</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <xref ref-type="aff" rid="aff4"/>
        <email>ros.syazmini@uts.edu.my</email>
      </contrib>
      <contrib contrib-type="author">
        <contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5781-4871</contrib-id>
        <name><surname>Mohd Razali</surname><given-names>Sofiyah</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <xref ref-type="aff" rid="aff5"/>
        <email>sofiyah@uts.edu.my</email>
      </contrib>
      <aff id="aff1">Centre of Excellence in Wood Engineered Products (CeWEP), University of Technology Sarawak, 96000 Sibu, Sarawak, Malaysia</aff>
      <aff id="aff2">School of Engineering and Technology, University of Technology Sarawak, 96000 Sibu, Sarawak, Malaysia</aff>
      <aff id="aff3">Chemistry Programme, Faculty of Resource Science and Technology, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak, Malaysia</aff>
      <aff id="aff4">School of Postgraduate Studies, University of Technology Sarawak, 96000 Sibu, Sarawak, Malaysia</aff>
      <aff id="aff5">School of Foundation Studies, University of Technology Sarawak, 96000 Sibu, Sarawak, Malaysia</aff>
    </contrib-group>
      <pub-date publication-format="electronic" date-type="pub"><day>03</day><month>02</month><year>2026</year></pub-date>
      <volume>2</volume>
      <fpage>57</fpage>
      <lpage>71</lpage>
      <self-uri xlink:href="https://caravelpress.com/journals/rrs/articles/2026.005"/>
      <history>
        <date date-type="received"><string-date>9 November 2025</string-date></date>
        <date date-type="rev-recd"><string-date>10 December 2025</string-date></date>
        <date date-type="accepted"><string-date>2 January 2026</string-date></date>
      </history>
      <permissions>
        <copyright-statement>© 2026 The Author(s). Published by Caravel Press.</copyright-statement>
        <copyright-year>2026</copyright-year>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
          <license-p>This is an open access article under the CC BY 4.0 licence.</license-p>
        </license>
      </permissions>
      <abstract><p>This study investigates composite boards fabricated from oil palm trunk (OPT) and rubberwood (RW) using polyvinyl alcohol (PVA) as a binder with sodium chloride (NaCl) and calcium carbonate (CaCO₃) as additives. Mechanical testing showed maximum bending strengths of 5.94 MPa (OPT) and 5.34 MPa (RW) at 10% PVA loading, while internal bonding values peaked at 0.97 MPa (RW). Dimensional stability improved with fillers, reducing thickness swelling by up to 25% compared to control boards. Flame retardancy was significantly enhanced, with LOI values exceeding 26% for all formulations containing NaCl and CaCO₃, classifying them as self-extinguishing. Thermogravimetric analysis confirmed improved thermal stability, with decomposition temperatures reaching ~543 °C in filler-modified boards. These findings highlight that integrating NaCl and CaCO₃ with PVA not only improves flame resistance but also enhances durability and thermal performance, demonstrating the potential of OPT and RW as sustainable raw materials engineered wood products.</p></abstract>
      <kwd-group kwd-group-type="author">
        <kwd>Wood</kwd>
        <kwd>flame retardancy</kwd>
        <kwd>thermal stability</kwd>
        <kwd>mechanical properties</kwd>
        <kwd>binder</kwd>
      </kwd-group>
      <funding-group><funding-statement>The Research were supported by research grants which are YSRG/1/2022/02, 1001/PTEKIND/8014083 and The Science and Technology Research Partnership for Sustainable Development (SATREPS) (203.PTEKIND.67811002).</funding-statement></funding-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec1">
      <title>Introduction</title>
      <p>In the achievement of a low-carbon and sustainable future, convergence of scientific innovation, technological advancement, and social responsibility has become a global imperative. One of the promising solutions is to turn agricultural residues into high-value-added products for environmental and economic resilience. OPT and RW, two abundant by-products of Southeast Asia's agro-industrial complex, have great potential as renewable raw materials for engineered wood products. The strategic application of such biomass feedstocks minimizes waste generation and supports local economies via sustainable material creation</p>
      <p>(<xref ref-type="bibr" rid="ref-r11">Lamaming <italic>et al.</italic> 2015</xref>; <xref ref-type="bibr" rid="ref-r26">Yusof <italic>et al.</italic> 2020</xref>).</p>
      <p>OPT, recovered from aged oil palm plantations, and RW, derived from latex-deficient rubber trees, have been researched in depth to discover their mechanical suitability for application in plywood, composites, and fiberboards. Their use aligns with circular economy principles by extending the value chain of crops and reducing dependence on primary forest resources (<xref ref-type="bibr" rid="ref-r1">Abd Karim <italic>et al.</italic> 2020</xref>; <xref ref-type="bibr" rid="ref-r18">Ratnasingam <italic>et al.</italic> 2015</xref>). However, moving away from conventional wood adhesives, particularly formaldehyde-based resins, is critical for ensuring low-emission manufacturing processes. Here, polyvinyl alcohol (PVA) has also been identified as a safe, non-toxic binder that aligns with green chemistry principles and improves indoor air quality (Shakir et al., 2017; Li et al., 2017).</p>
      <p>For further reinforcing the safety and functionality of composite materials, NaCl and CaCO₃ are incorporated in the present research as functional additives. NaCl exhibits flame retarding and thermal buffering action, while CaCO₃ enhances the mechanical strength and thermal insulation of the composite (Rajaei et al., 2014; Tao et al., 2019). Synergistic use of such additives in combination with PVA is a sign of science-based design to develop innovative biomaterials that meet evolving requirements for fire safety, environmental sustainability, and material durability.</p>
      <p>This work thus highlights the intersection of science, technology, and society, demonstrating that biomass from a local source can be upcycled into fire-resistant particleboards with minimal environmental impact. Through the use of agricultural residues, renewable binders, and nontoxic additives, we envision being part of sustainable building material options that align with global efforts in carbon reduction, resource preservation, and human health.</p>
    </sec>
    <sec id="sec2">
      <title>Experimental</title>
      <p>OPT particles were sourced from Encore Agriculture Industries Sdn. Bhd. Selangor, Malaysia, while RW particles were obtained from a plywood manufacturer in Penang. Both materials were initially milled into coarse particles with an approximate size of 10 mm. These were then screened using a four-tier sieving system, and the final retained particles used for board fabrication were in the range of 0.5–2 mm, consistent with standard particleboard dimensions (<xref ref-type="bibr" rid="ref-r27">Zhang <italic>et al.</italic> 2018</xref>; <xref ref-type="bibr" rid="ref-r10">Júda <italic>et al.</italic> 2023</xref>). CaCO₃ and NaCl were purchased from ChemAr and QRec, respectively. PVA and citric acid were supplied by R &amp; M Chemicals. All reagents were analytical grade and used without further purification.</p>
      <p>The OPT and RW particles were blended with additives in different proportions: 10% or 20% PVA, 10% or 20% CaCO₃, and up to 30% NaCl, as shown in Table 1. The NaCl content was capped at 30% because higher salt loadings have been reported to compromise mechanical integrity by weakening particle bonding, similar to the effects observed with other inorganic fillers in lignocellulosic composites (Tao et al., 2019; Wang et al., 2022). This upper limit is consistent with previous findings that excessive mineral additives cause brittleness and reduced bending strength. In addition, 10% citric acid was incorporated as a cross-linking agent for PVA, as suggested by Birck et al. (<xref ref-type="bibr" rid="ref-r3">2014</xref>), who reported that such a formulation enhances crosslinking efficiency. Control boards containing 100% OPT and 100% RW were also fabricated. The composites were hot-pressed at 160 °C for 20 minutes to a target density of 700 kg/m² (Wahab et al., 2018). In total, twelve types of particleboard were produced (Table 1), with three replicates prepared for each formulation to ensure experimental reliability.</p>
      <table-wrap id="tbl1">
        <label>Table 1</label>
        <caption><p>Formulation for composite board making.</p></caption>
        <table>
          <thead>
            <tr>
              <th><bold>Materials</bold></th>
              <th colspan="2"><bold>Particles</bold></th>
              <th colspan="5"><bold>Addition</bold></th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td></td>
              <td><bold>OPT (%)</bold></td>
              <td><bold>RW (%)</bold></td>
              <td><bold>PVA (%)</bold></td>
              <td><bold>CaCO<sub>3</sub> (%)</bold></td>
              <td></td>
              <td colspan="2"><bold>NaCl (%)</bold></td>
            </tr>
            <tr>
              <td>A1</td>
              <td>100</td>
              <td>0</td>
              <td>0</td>
              <td>0</td>
              <td colspan="2"></td>
              <td>0</td>
            </tr>
            <tr>
              <td>B1</td>
              <td>0</td>
              <td>100</td>
              <td>0</td>
              <td>0</td>
              <td colspan="2"></td>
              <td>0</td>
            </tr>
            <tr>
              <td>A2</td>
              <td>90</td>
              <td>0</td>
              <td>10</td>
              <td>0</td>
              <td colspan="2"></td>
              <td>0</td>
            </tr>
            <tr>
              <td>B2</td>
              <td>0</td>
              <td>90</td>
              <td>10</td>
              <td>0</td>
              <td colspan="2"></td>
              <td>0</td>
            </tr>
            <tr>
              <td>A3</td>
              <td>60</td>
              <td>0</td>
              <td>10</td>
              <td>0</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
            <tr>
              <td>B3</td>
              <td>0</td>
              <td>60</td>
              <td>10</td>
              <td>0</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
            <tr>
              <td>A4</td>
              <td>40</td>
              <td>0</td>
              <td>10</td>
              <td>20</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
            <tr>
              <td>B4</td>
              <td>0</td>
              <td>40</td>
              <td>10</td>
              <td>20</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
            <tr>
              <td>A5</td>
              <td>50</td>
              <td>0</td>
              <td>10</td>
              <td>10</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
            <tr>
              <td>B5</td>
              <td>0</td>
              <td>50</td>
              <td>10</td>
              <td>10</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
            <tr>
              <td>A6</td>
              <td>40</td>
              <td>0</td>
              <td>20</td>
              <td>10</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
            <tr>
              <td>B6</td>
              <td>0</td>
              <td>40</td>
              <td>20</td>
              <td>10</td>
              <td colspan="2"></td>
              <td>30</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <sec id="sec3">
        <title>Bending test and internal bonding test (IB)</title>
        <p>The bending test was done according to Japanese Industrial Standard JIS A 5908-2003 (2003) using an Instron machine model 4204. A central point load was applied at a crosshead speed of 10 mm/min across an effective span of 150 mm. The test specimens measured 50 mm × 200 mm, and four replicates were prepared for each particleboard type. Internal bonding testing was also carried out by the Japanese Industrial Standard (JIS A 5908-2003) (2003) using the same type of Instron machine, model 4204, as the bending test machine. A sample specimen was strapped to the 50 mm x 50 mm block and then secured in the machine. The tension load was applied vertically on the face of the board with a tension loading speed of 2 mm/min. Subsequently, the maximum load (P') was recorded at the breaking point of the perpendicular tensile strength of the board. Four test samples were prepared to determine internal bonding performance.</p>
      </sec>
      <sec id="sec4">
        <title>Dimensional stability test</title>
        <p>The thickness swelling (TS) and water absorption (WA) tests of the composite board were determined based on the percentage increase in thickness and weight after water immersion, relative to their initial values (<xref ref-type="bibr" rid="ref-r28">Zuo <italic>et al.</italic> 2018</xref>). These tests were conducted by soaking the composite boards in water, after which TS and WA were measured following the Japanese Industrial Standard JIS A 5908-2003. Specimens with dimensions of 50 mm × 50 mm × 10 mm were oven-dried at 105 ± 2 °C until constant weight, then immersed in distilled water at room temperature (25 ± 2 °C) for 24 h. After immersion, samples were surface-dried and re-weighed, and the thickness was re-measured. Four replicates were tested for each board.</p>
      </sec>
      <sec id="sec5">
        <title>Limited Oxygen Index test (LOI)</title>
        <p>The flammability of the composite boards was evaluated using the Limited Oxygen Index (LOI) test, following ASTM D2863 with a Fire Testing Technology LOI apparatus. Rectangular specimens (80 mm × 10 mm × 5 mm) were positioned vertically in the sample holder, and the minimum oxygen concentration required to sustain combustion was recorded. All tests were performed in a controlled atmosphere, and 15 replicate specimens of each board were prepared to ensure accuracy.</p>
      </sec>
      <sec id="sec6">
        <title>Thermogravimetric analysis test</title>
        <p>TGA was conducted with a Shimadzu TGA-50, heating the samples from room temperature to 920 °C at 20 °C/min under nitrogen flow. Weight loss profiles were obtained as a function of temperature and analyzed using the Freeman–Carroll method (Hatakeyama &amp; Quinn, 2006).</p>
      </sec>
      <sec id="sec7">
        <title>Fourier Transform Infrared (FTIR) Analysis</title>
        <p>FTIR spectra were recorded using a Perkin Elmer spectrometer at 2 cm⁻¹ resolution with 15 scans, employing the KBr pellet method at a 1:100 sample-to-KBr ratio.</p>
      </sec>
    </sec>
    <sec id="sec8">
      <title>Results And Discussion</title>
      <sec id="sec9">
        <title>Evaluation of mechanical properties and dimensional stability</title>
        <p>The bending strength results of all samples are presented in Fig. 1. Among the OPT composite boards, sample A2 exhibited the highest bending strength, while sample B2 recorded the highest value for RW. Specifically, the mixture of OPT with 10% PVA reached 5.94 MPa, whereas RW with 10% PVA showed 5.34 MPa. Lamaming et al. (<xref ref-type="bibr" rid="ref-r11">2015</xref>) reported that PVA addition enhances the mechanical performance of composite boards. The lowest bending strength values were obtained from A1 (100% OPT, 0.40 MPa) and B1 (100% RW, 0.97 MPa). As shown in Fig. 1, the bending strength decreased with the incorporation of CaCO₃ and NaCl. According to Hongzhen et al. (2017), excessive CaCO₃ (&gt;10%) weakens intermolecular forces, destabilizes the internal structure, and reduces bending strength.</p>
        <fig id="fig1">
          <label>Figure 1</label>
          <caption><p>Bending test and internal bonding (IB) test result of comparative study of OPT and RW particleboards.</p></caption>
          <graphic xlink:href="obj/52/e6/52e664cbc5bf3481f7afab1abf995a4f6f97371663cc723737816a004b0299d9"/>
        </fig>
        <p>The ANOVA results for bending strength in Table 2 revealed significant differences among particleboard formulations for both OPT and RW (p &lt; 0.001). This indicates that variations in PVA, CaCO₃, and NaCl contents had a measurable influence on the bending performance of the composites. For OPT-based boards, the between-group variance (F = 12.523) was notably higher than the within-group variance, confirming that formulation played a dominant role in determining flexural strength. Similarly, RW composites also showed significant treatment effects (F = 5.546), though the lower F value suggests that RW was less sensitive to additive changes compared with OPT. These findings highlight that the mechanical properties of the boards are strongly dependent on binder and filler composition, consistent with previous studies reporting that filler loading can either enhance or weaken stress transfer across the particle–matrix interface.</p>
        <p>The Duncan post-hoc test shown in Table 3 further clarified which formulations differed significantly. For OPT, sample A2 clustered in a distinct subset with the highest bending strength, confirming the positive role of moderate PVA content in improving matrix cohesion. In contrast, formulations with high CaCO₃ and NaCl loadings (A3, A5, A6) fell into subsets associated with lower bending values, suggesting that excessive filler disrupted interfacial bonding. For RW, a similar pattern was observed, where B2 produced the highest bending strength, while filler-heavy formulations (B3, B4, B6) yielded lower values. These results demonstrate that PVA alone significantly enhances bending properties through hydrogen bonding interactions, whereas high mineral filler contents tend to dilute the effectiveness of the binder. Collectively, the ANOVA and post-hoc outcomes validate the experimental observations and confirm that formulation optimization is critical for achieving the desired balance between strength and functionality.</p>
        <table-wrap id="tbl2">
          <label>Table 2</label>
          <caption><p>ANOVA for the Bending Test of OPT and RW particleboard with different ratio</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>Bending Test</bold></th>
                <th></th>
                <th><bold>Sum of Squares</bold></th>
                <th><bold>df</bold></th>
                <th><bold>Mean Square</bold></th>
                <th><bold>F</bold></th>
                <th><bold>Sig.</bold></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>94.692</td>
                <td>5</td>
                <td>18.938</td>
                <td>12.523</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>OPT</td>
                <td>Within Group</td>
                <td>63.516</td>
                <td>42</td>
                <td>1.512</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>158.208</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>62.918</td>
                <td>5</td>
                <td>12.584</td>
                <td>5.546</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>RW</td>
                <td>Within Groups</td>
                <td>95.290</td>
                <td>42</td>
                <td>2.269</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>158.208</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <table-wrap id="tbl3">
          <label>Table 3</label>
          <caption><p>Duncan Post-Hoc for Bending Test</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>Bending Test</bold></th>
                <th></th>
                <th colspan="2"><bold>Subset for alpha= 0.05</bold></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td><bold>OPT</bold></td>
                <td><bold>N</bold></td>
                <td><bold>1</bold></td>
                <td><bold>2</bold></td>
              </tr>
              <tr>
                <td>A1</td>
                <td>4</td>
                <td>.5325</td>
                <td></td>
              </tr>
              <tr>
                <td>A2</td>
                <td>4</td>
                <td></td>
                <td>6.0525</td>
              </tr>
              <tr>
                <td>A3</td>
                <td>8</td>
                <td>1.1025</td>
                <td></td>
              </tr>
              <tr>
                <td>A4</td>
                <td>4</td>
                <td>1.9471</td>
                <td></td>
              </tr>
              <tr>
                <td>A5</td>
                <td>24</td>
                <td>.8437</td>
                <td></td>
              </tr>
              <tr>
                <td>A6</td>
                <td>4</td>
                <td>.5600</td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td>.106</td>
                <td>1.000</td>
              </tr>
              <tr>
                <td>RW</td>
                <td></td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>B1</td>
                <td>4</td>
                <td>.9300</td>
                <td></td>
              </tr>
              <tr>
                <td>B2</td>
                <td>4</td>
                <td></td>
                <td>5.4900</td>
              </tr>
              <tr>
                <td>B3</td>
                <td>4</td>
                <td>1.7225</td>
                <td></td>
              </tr>
              <tr>
                <td>B4</td>
                <td>24</td>
                <td>1.6558</td>
                <td></td>
              </tr>
              <tr>
                <td>B5</td>
                <td>8</td>
                <td>1.2900</td>
                <td></td>
              </tr>
              <tr>
                <td>B6</td>
                <td>4</td>
                <td>.9600</td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td>.461</td>
                <td>1.000</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>a. Uses Harmonic Mean Sample Size = 5.143</p>
        <p>Figure 1 also presents the internal bonding (IB) performance of OPT and RW composites. The highest IB for OPT was observed in A2 (OPT + 10% PVA), while B4 (RW + 10% PVA, 20% CaCO₃, and 30% NaCl) showed the highest IB for RW composites. The lowest IB was recorded in B1 (control RW, 0.13 MPa). Overall, the addition of CaCO₃ and NaCl reduced IB in both OPT and RW, likely due to the higher CaCO₃ content. The decline in IB is attributed to changes in particle composition, where CaCO₃ partially covered the OPT particle surfaces, limiting the adhesive bonding of PVA. Similar findings were reported in CaCO₃-filled pine flake composites with phenol–formaldehyde resin (<xref ref-type="bibr" rid="ref-r22">Tao <italic>et al.</italic> 2019</xref>). In general, RW particleboards exhibited higher IB than OPT particleboards, which is consistent with the findings of Lee et al. (<xref ref-type="bibr" rid="ref-r13">2018</xref>).</p>
        <p>The performance variations can be attributed not only to the filler content but also to interfacial interactions between PVA and the lignocellulosic particles. PVA, rich in hydroxyl (–OH) groups, forms hydrogen bonds with hydroxyl groups present on cellulose and hemicellulose surfaces of both OPT and RW. This molecular interaction improves adhesion and stress transfer across the matrix, explaining the enhanced internal bonding observed at moderate PVA levels, consistent with recent reports of hydrogen bonding and physical entanglement effects in PVA–wood systems (<xref ref-type="bibr" rid="ref-r15">Liu <italic>et al.</italic> 2024</xref>; <xref ref-type="bibr" rid="ref-r7">Huang <italic>et al.</italic> 2024</xref>; <xref ref-type="bibr" rid="ref-r4">Chen <italic>et al.</italic> 2024</xref>). However, excessive filler loading (NaCl or CaCO₃) disrupts this interaction by occupying surface sites and reducing effective contact between PVA and wood particles, thereby lowering mechanical strength.</p>
        <p>The ANOVA results for internal bonding in Table 4 demonstrated statistically significant differences among formulations for both OPT and RW composites (p &lt; 0.001). The F values 10.319 for OPT and 6.680 for RW indicate that binder and filler ratios had a strong influence on tensile strength perpendicular to the board surface. Similar to the bending test, OPT appeared more sensitive to additive variation than RW, suggesting that the lower density and higher porosity of OPT fibers amplified the effects of PVA and mineral fillers.</p>
        <p>The Duncan post-hoc analysis shown in Table 5 revealed that A2 had the highest internal bonding strength, confirming that moderate PVA addition optimizes interfacial adhesion. In contrast, formulations with excessive fillers for A3 and A6 exhibited the lowest IB, reflecting poor particle binder contact. For RW composites, B2 and B5 formed distinct subsets with the highest IB values, whereas B1 showed the weakest bonding. These results emphasize the role of PVA as a hydrogen-bonding binder while demonstrating that excessive mineral loading diminishes adhesion by masking hydroxyl-rich wood surfaces.</p>
        <table-wrap id="tbl4">
          <label>Table 4</label>
          <caption><p>ANOVA for the IB of OPT and RW particleboard with different ratio</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>IB</bold></th>
                <th></th>
                <th><bold>Sum of Squares</bold></th>
                <th><bold>df</bold></th>
                <th><bold>Mean Square</bold></th>
                <th><bold>F</bold></th>
                <th><bold>Sig.</bold></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>80.814</td>
                <td>5</td>
                <td>16.163</td>
                <td>10.319</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>OPT</td>
                <td>Within Group</td>
                <td>65.788</td>
                <td>42</td>
                <td>1.566</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>146.601</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>64.938</td>
                <td>5</td>
                <td>12.988</td>
                <td>6.680</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>RW</td>
                <td>Within Groups</td>
                <td>81.663</td>
                <td>42</td>
                <td>1.944</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>146.601</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <table-wrap id="tbl5">
          <label>Table 5</label>
          <caption><p>Duncan Post-Hoc for IB</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>IB</bold></th>
                <th></th>
                <th colspan="3"><bold>Subset for alpha= 0.05</bold></th>
                <th></th>
                <th></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td><bold>OPT</bold></td>
                <td><bold>N</bold></td>
                <td><bold>1</bold></td>
                <td colspan="2"><bold>2</bold></td>
                <td><bold>3</bold></td>
                <td><bold>4</bold></td>
              </tr>
              <tr>
                <td>A1</td>
                <td>4</td>
                <td>2.40125</td>
                <td colspan="2">2.40125</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>A2</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td>5.75750</td>
                <td></td>
              </tr>
              <tr>
                <td>A3</td>
                <td>4</td>
                <td>.84750</td>
                <td colspan="2"></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>A4</td>
                <td>24</td>
                <td colspan="2"></td>
                <td>3.39333</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>A5</td>
                <td>8</td>
                <td colspan="2">2.07250</td>
                <td>2.07250</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>A6</td>
                <td>4</td>
                <td colspan="2">.71500</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td colspan="2">.053</td>
                <td>.117</td>
                <td>1.00</td>
                <td></td>
              </tr>
              <tr>
                <td>RW</td>
                <td></td>
                <td colspan="3"></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>B1</td>
                <td>4</td>
                <td>.51500</td>
                <td colspan="2"></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>B2</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td></td>
                <td>4.83750</td>
              </tr>
              <tr>
                <td>B3</td>
                <td>4</td>
                <td></td>
                <td colspan="2">3.78500</td>
                <td>3.78500</td>
                <td>3.78500</td>
              </tr>
              <tr>
                <td>B4</td>
                <td>24</td>
                <td></td>
                <td colspan="2">2.31104</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>B5</td>
                <td>8</td>
                <td></td>
                <td colspan="2"></td>
                <td>4.29375</td>
                <td>4.29375</td>
              </tr>
              <tr>
                <td>B6</td>
                <td>4</td>
                <td></td>
                <td colspan="2">2.63500</td>
                <td>2.63500</td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td>1.000</td>
                <td colspan="2">.116</td>
                <td>.078</td>
                <td>.261</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>a. Uses Harmonic Mean Sample Size = 5.143</p>
        <fig id="fig2">
          <label>Figure 2</label>
          <caption><p>Thickness swelling (TS) and water absorption (WA) results of a comparative study for OPT and RW particleboards</p></caption>
          <graphic xlink:href="obj/f8/ce/f8ce6ee1feb76ae4ef6415c898a1c7b7dc513fea89f1b7a55a298cbdb4b961fd"/>
        </fig>
        <p>Dimensional stability, typically evaluated through thickness swelling (TS) and water absorption (WA), is a crucial property influencing the service life of particleboards under environmental exposure. As shown in Fig. 2, both WA and TS of OPT and RW particleboards decreased with the incorporation of PVA, CaCO₃, and NaCl. Srivabut et al. (<xref ref-type="bibr" rid="ref-r21">2018</xref>) reported that such reductions occur because chemical fillers act as barriers that limit water penetration into the boards. This modification therefore enhances the durability of both OPT and RW based composites. Swelling occurs when water molecules diffuse into the cell wall, and the extent of swelling is directly related to the quantity of water absorbed (<xref ref-type="bibr" rid="ref-r25">Younis 2017</xref>). Figure 2 further indicates that RW particleboards exhibit better dimensional stability than OPT boards, consistent with findings by Lee et al. (<xref ref-type="bibr" rid="ref-r13">2018</xref>). Wahab et al. (2018) also explained that the porous structure of OPT particles promotes water uptake, leading to higher WA, which in turn results in swelling and greater TS.</p>
        <p>The ANOVA results for TS and WA confirmed highly significant differences among board types for both OPT and RW (p &lt; 0.001). For TS in Table 6, OPT had a higher F value (11.280) compared with RW (7.516), indicating stronger treatment effects in OPT-based boards. Similarly, for WA in Table 8, the influence of formulation was more pronounced in RW boards (F = 56.757) than in OPT (F = 13.265), highlighting that dimensional stability improvements depend not only on additive type but also on intrinsic wood characteristics.</p>
        <p>Duncan post-hoc tests in Tables 7 and 9 showed that boards containing fillers and PVA for A5 and B5 exhibited significantly lower TS and WA values compared with control boards for A1 and B1. Particularly, B5 recorded the lowest water uptake, reflecting the effectiveness of mineral fillers in reducing porosity and limiting water penetration. Conversely, controls and low-PVA boards absorbed more water and swelled extensively, demonstrating the crucial role of both binder and filler in enhancing dimensional stability. These results validate that filler incorporation, when optimized, can act as a hydrophobic barrier, thereby prolonging the service life of the boards under humid conditions.</p>
        <table-wrap id="tbl6">
          <label>Table 6</label>
          <caption><p>ANOVA for the TS of OPT and RW particleboard with different ratio</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>TS</bold></th>
                <th></th>
                <th><bold>Sum of Squares</bold></th>
                <th><bold>df</bold></th>
                <th><bold>Mean Square</bold></th>
                <th><bold>F</bold></th>
                <th><bold>Sig.</bold></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>48535.129</td>
                <td>5</td>
                <td>9707.026</td>
                <td>11.280</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>OPT</td>
                <td>Within Group</td>
                <td>36143.965</td>
                <td>42</td>
                <td>860.571</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>84679.094</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>39987.441</td>
                <td>5</td>
                <td>7997.488</td>
                <td>7.516</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>RW</td>
                <td>Within Groups</td>
                <td>44691.653</td>
                <td>42</td>
                <td>1064.087</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>84679.094</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <table-wrap id="tbl7">
          <label>Table 7</label>
          <caption><p>Duncan Post-Hoc for TS</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>TS</bold></th>
                <th></th>
                <th colspan="3"><bold>Subset for alpha= 0.05</bold></th>
                <th></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td><bold>OPT</bold></td>
                <td><bold>N</bold></td>
                <td><bold>1</bold></td>
                <td colspan="2"><bold>2</bold></td>
                <td><bold>3</bold></td>
              </tr>
              <tr>
                <td>A1</td>
                <td>4</td>
                <td></td>
                <td colspan="2">149.2500</td>
                <td></td>
              </tr>
              <tr>
                <td>A2</td>
                <td>4</td>
                <td>44.5700</td>
                <td colspan="2"></td>
                <td></td>
              </tr>
              <tr>
                <td>A3</td>
                <td>4</td>
                <td>40.4250</td>
                <td colspan="2"></td>
                <td></td>
              </tr>
              <tr>
                <td>A4</td>
                <td>24</td>
                <td colspan="2">35.9121</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>A5</td>
                <td>8</td>
                <td colspan="2">25.8825</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>A6</td>
                <td>4</td>
                <td colspan="2">50.4800</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td colspan="2">.239</td>
                <td>1.000</td>
                <td></td>
              </tr>
              <tr>
                <td>RW</td>
                <td></td>
                <td colspan="3"></td>
                <td></td>
              </tr>
              <tr>
                <td>B1</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td>119.000</td>
              </tr>
              <tr>
                <td>B2</td>
                <td>4</td>
                <td>35.4625</td>
                <td colspan="2">35.4625</td>
                <td></td>
              </tr>
              <tr>
                <td>B3</td>
                <td>4</td>
                <td>20.9575</td>
                <td colspan="2">20.9575</td>
                <td></td>
              </tr>
              <tr>
                <td>B4</td>
                <td>24</td>
                <td></td>
                <td colspan="2">56.0817</td>
                <td></td>
              </tr>
              <tr>
                <td>B5</td>
                <td>8</td>
                <td>8.8425</td>
                <td colspan="2"></td>
                <td></td>
              </tr>
              <tr>
                <td>B6</td>
                <td>4</td>
                <td>22.3675</td>
                <td colspan="2">22.3675</td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td>.241</td>
                <td colspan="2">.122</td>
                <td>1.000</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>a. Uses Harmonic Mean Sample Size = 5.143</p>
        <table-wrap id="tbl8">
          <label>Table 8</label>
          <caption><p>ANOVA for the WA of OPT and RW particleboard with different ratio</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>WA</bold></th>
                <th></th>
                <th><bold>Sum of Squares</bold></th>
                <th><bold>df</bold></th>
                <th><bold>Mean Square</bold></th>
                <th><bold>F</bold></th>
                <th><bold>Sig.</bold></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>16495.192</td>
                <td>5</td>
                <td>3299.038</td>
                <td>13.265</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>OPT</td>
                <td>Within Group</td>
                <td>10445.663</td>
                <td>42</td>
                <td>248.706</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>26940.855</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>23467.672</td>
                <td>5</td>
                <td>4693.534</td>
                <td>56.757</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>RW</td>
                <td>Within Groups</td>
                <td>3473.183</td>
                <td>42</td>
                <td>82.695</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>26940.855</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <table-wrap id="tbl9">
          <label>Table 9</label>
          <caption><p>Duncan Post-Hoc for WA</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>WA</bold></th>
                <th></th>
                <th colspan="3"><bold>Subset for alpha= 0.05</bold></th>
                <th></th>
                <th></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td><bold>OPT</bold></td>
                <td><bold>N</bold></td>
                <td><bold>1</bold></td>
                <td colspan="2"><bold>2</bold></td>
                <td><bold>3</bold></td>
                <td><bold>4</bold></td>
              </tr>
              <tr>
                <td>A1</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td>86.2475</td>
                <td></td>
              </tr>
              <tr>
                <td>A2</td>
                <td>4</td>
                <td></td>
                <td colspan="2">66.4550</td>
                <td>66.4550</td>
                <td></td>
              </tr>
              <tr>
                <td>A3</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td>84.3525</td>
                <td></td>
              </tr>
              <tr>
                <td>A4</td>
                <td>24</td>
                <td colspan="2">38.0633</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>A5</td>
                <td>8</td>
                <td colspan="2"></td>
                <td>69.7213</td>
                <td>69.7213</td>
                <td></td>
              </tr>
              <tr>
                <td>A6</td>
                <td>4</td>
                <td colspan="2">55.2700</td>
                <td>55.2700</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td colspan="2">.087</td>
                <td>.173</td>
                <td>.072</td>
                <td></td>
              </tr>
              <tr>
                <td>RW</td>
                <td></td>
                <td colspan="3"></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>B1</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td></td>
                <td>71.4850</td>
              </tr>
              <tr>
                <td>B2</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td>56.1225</td>
                <td></td>
              </tr>
              <tr>
                <td>B3</td>
                <td>4</td>
                <td></td>
                <td colspan="2">40.5225</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>B4</td>
                <td>24</td>
                <td></td>
                <td colspan="2"></td>
                <td></td>
                <td>71.9612</td>
              </tr>
              <tr>
                <td>B5</td>
                <td>8</td>
                <td>19.7463</td>
                <td colspan="2"></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>B6</td>
                <td>4</td>
                <td>20.7575</td>
                <td colspan="2"></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td>.859</td>
                <td colspan="2">.1000</td>
                <td>1.000</td>
                <td>.933</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>a. Uses Harmonic Mean Sample Size = 5.143</p>
      </sec>
      <sec id="sec10">
        <title>Evaluation of Limited Oxygen Index (LOI)</title>
        <p>The Limited Oxygen Index (LOI) test is commonly used to evaluate the flammability and flame retardancy of materials. It is regarded as one of the key screening and quality control techniques in flame-retardant research and development (<xref ref-type="bibr" rid="ref-r3">Birck <italic>et al.</italic> 2014</xref>). A higher LOI value indicates that a material is more resistant to ignition and combustion (<xref ref-type="bibr" rid="ref-r27">Zhang <italic>et al.</italic> 2018</xref>). Figure 3 presents the LOI results for a comparative study of OPT and RW particleboards.</p>
        <fig id="fig3">
          <label>Figure 3</label>
          <caption><p>Limited Oxygen Index (LOI) result for comparative study between OPT and RW particleboards</p></caption>
          <graphic xlink:href="obj/54/47/54479e70a93db3d855dcfdfba6713bb983a34b25e851f47b3a189ace1ccab5b2"/>
        </fig>
        <p>As shown in Fig. 3, the LOI of OPT particleboards increased with the addition of CaCO₃ and NaCl fillers. The highest value was obtained for sample A6, which consisted of OPT with 20% PVA, 10% CaCO₃, and 30% NaCl. Wang et al. (<xref ref-type="bibr" rid="ref-r24">2017</xref>) reported that CaCO₃ enhances flame retardancy by delaying ignition, reducing the heat of combustion, and improving the overall fire resistance of particleboards. While OPT boards generally exhibited higher LOI improvements with additive incorporation, RW-based boards also demonstrated notable flame-retardant enhancement, achieving values above 27%, comparable to OPT. The slightly lower values in RW composites may reflect differences in density and inherent lignin content, which influence char formation during combustion. Compared with conventional flame-retardant systems such as ammonium polyphosphate, borates, and halogen-free mineral fillers, the NaCl/CaCO₃ approach demonstrates competitive LOI values above 26% while maintaining lower toxicity and cost (<xref ref-type="bibr" rid="ref-r17">Rajaei <italic>et al.</italic> 2017</xref>; <xref ref-type="bibr" rid="ref-r19">Schirp and Su 2016</xref>). While APP- or phosphorus-based systems often yield higher LOI values, they may involve higher cost or environmental concerns, highlighting the novelty of adopting NaCl as a low-cost, sustainable alternative in wood composites.</p>
        <p>The ANOVA results for LOI in Table 10 revealed a clear distinction between OPT and RW composites. OPT boards showed significant differences among formulations (F = 42.882, p &lt; 0.001), indicating that NaCl and CaCO₃ loadings had a strong influence on flame resistance. By contrast, RW composites exhibited no significant differences (p = 0.206), suggesting a more uniform flame-retardant performance across formulations. This discrepancy highlights the stronger responsiveness of OPT to additive incorporation, likely due to its more porous structure and higher moisture affinity.</p>
        <p>The Duncan post-hoc test in Table 11 identified A6 as having the highest LOI, indicating that it falls into a distinct subset with superior flame-retardant performance. In contrast, A1 showed the lowest value, underscoring the necessity of filler incorporation for fire safety. For RW, although differences were not statistically significant, a gradual increase in LOI with higher filler content was observed, with B5 and B6 showing slightly better fire resistance than B1. Overall, the statistical analysis validates that mineral fillers, particularly in OPT boards, substantially enhance flame retardancy, positioning NaCl/CaCO₃ systems as viable, eco-friendly alternatives to conventional halogenated flame retardants.</p>
        <table-wrap id="tbl10">
          <label>Table 10</label>
          <caption><p>ANOVA for the LOI of OPT and RW particleboard with different ratio</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>LOI</bold></th>
                <th></th>
                <th><bold>Sum of Squares</bold></th>
                <th><bold>df</bold></th>
                <th><bold>Mean Square</bold></th>
                <th><bold>F</bold></th>
                <th><bold>Sig.</bold></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>391.792</td>
                <td>5</td>
                <td>78.358</td>
                <td>42.882</td>
                <td>&lt;.001</td>
              </tr>
              <tr>
                <td>OPT</td>
                <td>Within Group</td>
                <td>76.746</td>
                <td>42</td>
                <td>1.827</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>468.538</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Between Groups</td>
                <td>71.590</td>
                <td>5</td>
                <td>14.318</td>
                <td>1.515</td>
                <td>.206</td>
              </tr>
              <tr>
                <td>RW</td>
                <td>Within Groups</td>
                <td>396.948</td>
                <td>42</td>
                <td>9.451</td>
                <td></td>
                <td></td>
              </tr>
              <tr>
                <td></td>
                <td>Total</td>
                <td>468.538</td>
                <td>47</td>
                <td></td>
                <td></td>
                <td></td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <table-wrap id="tbl11">
          <label>Table 11</label>
          <caption><p>Duncan Post-Hoc for LOI</p></caption>
          <table>
            <thead>
              <tr>
                <th><bold>LOI</bold></th>
                <th></th>
                <th colspan="3"><bold>Subset for alpha= 0.05</bold></th>
                <th colspan="3"></th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td><bold>OPT</bold></td>
                <td><bold>N</bold></td>
                <td><bold>1</bold></td>
                <td colspan="2"><bold>2</bold></td>
                <td colspan="2"><bold>3</bold></td>
                <td><bold>4</bold></td>
              </tr>
              <tr>
                <td>A1</td>
                <td>4</td>
                <td>23.9400</td>
                <td colspan="2"></td>
                <td colspan="2"></td>
                <td></td>
              </tr>
              <tr>
                <td>A2</td>
                <td>4</td>
                <td></td>
                <td colspan="2">25.7725</td>
                <td colspan="2"></td>
                <td></td>
              </tr>
              <tr>
                <td>A3</td>
                <td>4</td>
                <td></td>
                <td colspan="2">27.3000</td>
                <td colspan="2"></td>
                <td></td>
              </tr>
              <tr>
                <td>A4</td>
                <td>24</td>
                <td colspan="2"></td>
                <td></td>
                <td>30.2871</td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>A5</td>
                <td>8</td>
                <td colspan="2"></td>
                <td></td>
                <td></td>
                <td colspan="2">33.2763</td>
              </tr>
              <tr>
                <td>A6</td>
                <td>4</td>
                <td colspan="2"></td>
                <td></td>
                <td></td>
                <td colspan="2">33.7650</td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td colspan="2">1.000</td>
                <td>.077</td>
                <td>1.00</td>
                <td colspan="2">.565</td>
              </tr>
              <tr>
                <td>RW</td>
                <td></td>
                <td colspan="3">Subset for alpha= 0.05</td>
                <td colspan="3"></td>
              </tr>
              <tr>
                <td>B1</td>
                <td>4</td>
                <td>28.2800</td>
                <td colspan="2"></td>
                <td></td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>B2</td>
                <td>4</td>
                <td>28.9225</td>
                <td colspan="2">28.9225</td>
                <td></td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>B3</td>
                <td>4</td>
                <td>29.1725</td>
                <td colspan="2">29.1725</td>
                <td></td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>B4</td>
                <td>24</td>
                <td>29.5550</td>
                <td colspan="2">29.5550</td>
                <td></td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>B5</td>
                <td>8</td>
                <td>31.1438</td>
                <td colspan="2">31.1438</td>
                <td></td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>B6</td>
                <td>4</td>
                <td></td>
                <td colspan="2"></td>
                <td></td>
                <td colspan="2"></td>
              </tr>
              <tr>
                <td>Sig.</td>
                <td></td>
                <td>.191</td>
                <td colspan="2">.059</td>
                <td></td>
                <td colspan="2"></td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>b. Uses Harmonic Mean Sample Size = 5.143</p>
      </sec>
      <sec id="sec11">
        <title>Evaluation of the thermal stability of particleboard</title>
        <p>Thermogravimetric analysis (TGA) is a widely applied technique for assessing the thermal stability of materials and identifying the decomposition behavior of polymers within composite systems, such as OPT and RW-based particleboards (<xref ref-type="bibr" rid="ref-r25">Younis 2017</xref>). Figures 4a and 4b display the thermogravimetric (TG) weight-loss curves and derivative thermogravimetric (DTG) profiles, respectively, for comparative particleboards made from OPT and RW. In this evaluation, the specimens were subjected to a controlled increase in temperature to assess their heat resistance and decomposition patterns.</p>
        <p>As shown in Fig. 4a, the TGA curves of both OPT and RW composites revealed two distinct stages of weight loss occurring between 50–150 °C and 200–250 °C. The first stage corresponds to the evaporation of moisture and volatile compounds (<xref ref-type="bibr" rid="ref-r11">Lamaming <italic>et al.</italic> 2015</xref>), while the second stage reflects polymer decomposition leading to carbonaceous char formation (<xref ref-type="bibr" rid="ref-r28">Zuo <italic>et al.</italic> 2018</xref>). For both OPT and RW particleboards bonded with PVA, weight loss began around 200 °C, with complete decomposition observed at approximately 543 °C, consistent with Schirp and Su (<xref ref-type="bibr" rid="ref-r19">2016</xref>). This behavior is expected, as PVA undergoes dehydration at the onset of thermal degradation, producing unsaturated compounds (<xref ref-type="bibr" rid="ref-r25">Younis 2017</xref>).</p>
        <fig id="fig4">
          <label>Figure 4</label>
          <caption><p>a) Thermogravimetric (TG) and, b) derivative thermogravimetric (DTG) curves of selected comparative particleboard of OPT and RW.</p></caption>
          <graphic xlink:href="obj/3c/27/3c27699d2b0f430f46047ec7bc8eb921c50c459b7f972b32573e337de512274d"/>
        </fig>
        <p>Moreover, particleboards containing 10% PVA, 10% CaCO₃, and 30% NaCl (samples A5 and B5) demonstrated greater thermal resistance. This improvement can be attributed to the decomposition of CaCO₃ into carbon dioxide at elevated temperatures, which contributes to thermal stabilization (<xref ref-type="bibr" rid="ref-r19">Schirp and Su 2016</xref>). Each additive displayed a distinct degradation pathway (<xref ref-type="bibr" rid="ref-r8">Jiang <italic>et al.</italic> 2017</xref>), and Lamaming et al. (<xref ref-type="bibr" rid="ref-r12">2017</xref>) further noted that the incorporation of inorganic materials enhances crystallinity, thereby improving thermal stability. The DTG results presented in Fig. 4b provide a detailed view of mass loss across distinct temperature ranges (<xref ref-type="bibr" rid="ref-r2">Amini <italic>et al.</italic> 2013</xref>). In both OPT and RW composites, the addition of CaCO₃ and NaCl shifted decomposition onset to higher temperatures. However, RW composites consistently retained slightly higher residual mass at 600 °C compared to OPT, suggesting greater thermal stability, likely due to their denser microstructure and lower porosity.</p>
      </sec>
      <sec id="sec12">
        <title>Evaluation in functional group</title>
        <p>Figure 5 shows the FTIR spectra of OPT and RW particleboards. A broad band near 3415 cm⁻¹ corresponds to O–H stretching vibrations, characteristic of hydroxyl groups in cellulose and hemicellulose. Absorption bands between 2800–3000 cm⁻¹ reflect C–H stretching vibrations associated with polysaccharides and lignin, while peaks around 1104–1110 cm⁻¹ and 1155–1159 cm⁻¹ indicate cellulose contributions from both crystalline and amorphous domains (<xref ref-type="bibr" rid="ref-r13">Lee <italic>et al.</italic> 2018</xref>). The pronounced O–H band also supports hydrogen bonding between PVA and lignocellulosic surfaces, which underpins the enhanced dimensional stability and bonding strength observed at moderate PVA contents. In CaCO₃-filled boards, carbonate-related bands further suggest its contribution to flame retardancy, as thermal decomposition releases CO₂ that dilutes flammable volatiles and delays ignition.</p>
        <fig id="fig5">
          <label>Figure 5</label>
          <caption><p>FTIR spectra of selected particleboards from OPT and RW</p></caption>
          <graphic xlink:href="obj/09/58/09584783e95a1e31b44fcde75fbc48d6912cff9f136b19a316d9e78435db9f1b"/>
        </fig>
      </sec>
    </sec>
    <sec id="sec13">
      <title>Conclusion</title>
      <p>This study confirms the feasibility of producing flame-retardant particleboards from OPT and RW using PVA as a formaldehyde-free binder and CaCO₃/NaCl as eco-friendly additives. All formulations, except the OPT control, achieved LOI values above 26%, classifying them as self-extinguishing. OPT composites generally exhibited higher flame resistance, whereas RW boards showed superior internal bonding and dimensional stability, reflecting the influence of inherent material properties. These results confirm the viability of both biomass types as sustainable feedstocks for engineered wood products. Future work should focus on optimizing additive ratios to balance flame retardancy with mechanical performance, thereby supporting the development of low-emission, value-added materials for a circular, carbon-conscious economy.</p>
    </sec>
  </body>
  <back>
    <ack><p>The authors are grateful to the University of Technology Sarawak (UTS) and Universiti Sains Malaysia (USM) for providing access to their research opportunities, facilities and laboratory, which were required for conducting and analyzing various aspects of this study.</p></ack>
    <fn-group>
      <fn fn-type="con"><p>Madihan Yusof: Conceptualization, Writing- Origional Draft Preparation; Junidah Lamaming: Data Curation, Supervision; Mohamad Saiful Sulaiman: Software, Validation; Ros Syazmini Mohd Ghani: Writing-Reviewing and Editing; Sofiyah Mohd Razali: Methodology, Validation.</p></fn>
      <fn fn-type="conflict"><p>The author(s) has/have no competing interests to declare.</p></fn>
      <fn fn-type="data-availability"><p>The datasets generated and analyzed during the current study are available from the corresponding author.</p></fn>
    </fn-group>
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