ABSTRACT
In the production of 3D printable mortar (3DPM), numerous efforts have been made globally to effectively utilise various cementitious materials, admixtures, and fibres. The determination of rheological and material strength properties is crucial for successful 3D concrete printing because the materials used in 3DPM must possess the unique characteristic of making mortar flowable while being strong enough to support the weight of subsequent layers in both fresh and hardened states. The complexity of the required characteristics makes it challenging to develop an optimised mix composition that satisfies both the rheological and material strength requirements, given the wide range of available admixtures, supplementary cementitious materials, and fibres. Fly ash, basalt fibre and superplasticiser when blended with cement can help to improve the overall performance of 3DPM. The objective of this research is to optimise the rheological properties and material strength of 3D printable mortars (3DPM) containing cement, fly ash, basalt fibre, and superplasticiser. This study aims to produce 3DPM with an optimised mix composition to meet the requirements of both rheological and material strength characteristics using the factorial design approach and desirability function. Different dosages of cement, fly ash, basalt fibre, and superplasticiser are chosen as the primary design parameters to develop statistical models for the responses of rheological and material strength properties at 7 and 28 days. The results expressed in terms of the measured properties are valid for mortars made with cement ranging from 550 to 650 kg/m3, fly ash from 5% to 20% (of cement), superplasticiser from 2 to 4 kg/m3, and basalt fibre from 1 to 3 kg/m3. The rheological properties are evaluated using slump flow, cone penetrometer, and cylindrical slump tests, while the mechanical strength is evaluated using a three-point bending test and compressive test. A full factorial design experiment (FoE) is used to determine the significant parameters effecting the measured properties. Prediction models are developed to express the measured properties in terms of the primary parameters. The influence of cement, fly ash, basalt fibre, and superplasticiser is analysed using polynomial regression to determine the main effects and interactions of these primary parameters on the measured properties. The results show that the regression models established by the factorial design approach are effective and can accurately predict the performance of 3DPM. Cement, fly ash, and superplasticiser dosages have significant effects on the rheological and mechanical properties of mortar, while basalt fibre is able to influence the static yield stress and flexural strength of 3DPM. The utilisation of regression models and isoresponse curves allows for the identification of significant trends and provides valuable insight into the behaviour of the material, while desirability function is useful to optimise overall performance of mix proportions to meet the desired performance objective at fresh and hardened states.
ABSTRACT
AIM: The aim of the study is to compare the microleakage of three different direct restorative materials (amalgam [AA], glass ionomer cements [GICs], and Cention N [CN]) in Class II restorations using stereomicroscope. MATERIALS AND METHODS: A standardized Class II cavity preparation was made involving the proximal and occlusal surfaces. All prepared samples were randomly divided into 3 experimental groups, with 10 teeth each according to the restoration material used: Group I-AA; Group II-GICs; and Group III-CN. The restored teeth were stored for 24 h in distilled water and thermocycled for 500 cycles between 5°C and 55°C with a dwell time of 30 s in each bath. Samples were immersed in 0.5% basic fuchsin dye for 24 h. The teeth were sectioned along the mesiodistal direction. The dye penetration of the occlusal and gingival margins of each section was evaluated independently by the observer using a stereomicroscope. RESULTS: Statistical analysis revealed lower microleakage scores in GIC and CN. Higher microleakage was observed in Group AA. Mean microleakage score of Group-I (AA) was the highest of all groups. Mean microleakage score of Group-III (CN) was the lowest of all groups. As per the critical differences (CD), the mean microleakage score of Group-III CN) was significantly lower than that of Group-I (AA), Group-II (GIC) (P < 0.01). There is no significant difference between the mean microleakage score of Group-I (AA) and Group-II (GIC). CONCLUSION: Out of all the restorative materials, CN a newer restorative material displayed minimum microleakage compared to AA and GICs.
