Hossain Md Sakhawat, Rabi Sazid Noor, Mohammad Sakib, Cook Kaden, Chowdhury Farhan, Nilufar Sabrina
School of Mechanical, Aerospace, and Materials Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.
School of Electrical, Computer, and Biomedical Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.
Polymers (Basel). 2025 May 28;17(11):1495. doi: 10.3390/polym17111495.
Stereolithography (SLA) is a popular additive manufacturing (AM) method frequently used in research and various industrial sectors. The acrylate resin used in this research is renowned for its flexibility and durability, enabling the creation of flawless 3D-printed parts with exceptional mechanical properties. This study aims to enhance the thermomechanical properties of 3D-printed hollow glass microballoon (HGM)-filled composite materials by adding minimal HGM into the acrylate resin. We investigated the material properties through uniaxial compression tests, dynamic mechanical analysis (DMA), and scanning electron microscopy (SEM). To validate the results, a numerical investigation and a machine learning (ML) approach were carried out and compared with the experimental results. Adding a small number of microballoons increases compressive strength and stiffness. The viscoelastic behavior of the samples also provides an estimate of resilience at higher temperatures, considering the addition of filler material into the resin. Our study shows that the addition of 0.04% of HGM increased compressive strength by around 99.30% compared to the neat sample, while the stiffness increased by around 31.42% compared to the neat sample at 0.05% of HGM. It can also be estimated that the suitable range of HGM addition for the resin we used exists between 0.04% and 0.05%, where the materials achieve their maximum strength and stiffness. In addition, a predictive machine learning (ML) model, namely Random Forest Regressor (RFR), shows low mean squared error (MSE), mean absolute error (MAE), and excellent R scores, demonstrating the goodness of the model's performance. This modern approach can guide us to selecting a suitable filler percentage for the photopolymer resin for 3D printing and making it applicable to different engineering prospects.
立体光刻（SLA）是一种常用的增材制造（AM）方法，常用于研究和各个工业领域。本研究中使用的丙烯酸酯树脂以其柔韧性和耐用性而闻名，能够制造出具有出色机械性能的完美3D打印部件。本研究旨在通过向丙烯酸酯树脂中添加少量空心玻璃微球（HGM）来提高3D打印的含HGM复合材料的热机械性能。我们通过单轴压缩试验、动态力学分析（DMA）和扫描电子显微镜（SEM）研究了材料性能。为了验证结果，进行了数值研究和机器学习（ML）方法，并与实验结果进行了比较。添加少量微球可提高抗压强度和刚度。考虑到向树脂中添加了填充材料，样品的粘弹性行为还提供了在较高温度下的弹性恢复估计。我们的研究表明，添加0.04%的HGM与纯样品相比，抗压强度提高了约99.30%，而在添加0.05%的HGM时，刚度比纯样品提高了约31.42%。还可以估计，我们使用的树脂添加HGM的合适范围在0.0（4）%和0.05%之间，此时材料达到其最大强度和刚度。此外，一种预测性机器学习（ML）模型，即随机森林回归器（RFR），显示出低均方误差（MSE）、平均绝对误差（MAE）和出色的R分数，证明了模型性能的良好性。这种现代方法可以指导我们为3D打印的光聚合物树脂选择合适的填充百分比，并使其适用于不同的工程前景。
