低温共烧陶瓷(Low Temperature Co-fired Ceramics,LTCC)具有优异的介电性能、热稳定性和多功能集成能力,在5G/6G通信、毫米波雷达、卫星载荷、系统级封装等领域得到广泛应用。然而,传统工艺存在两方面显著局限:一是受成型方式制约,难...低温共烧陶瓷(Low Temperature Co-fired Ceramics,LTCC)具有优异的介电性能、热稳定性和多功能集成能力,在5G/6G通信、毫米波雷达、卫星载荷、系统级封装等领域得到广泛应用。然而,传统工艺存在两方面显著局限:一是受成型方式制约,难以实现曲面多层基板的高精度制造;二是工艺流程复杂且对批次规模依赖性强,难以满足单件、小批基板的快速验证需求。增材制造基于逐层堆叠、按需沉积的独特技术路径,为突破上述瓶颈提供了创新性解决方案。文中系统综述了LTCC增材制造所涉及的材料制备、成型工艺方面的研究动态,分析了当前存在的关键问题,并展望了未来发展方向。展开更多
The design of casting gating system directly determines the solidification sequence,defect severity,and overall quality of the casting.A novel machine learning strategy was developed to design the counter pressure cas...The design of casting gating system directly determines the solidification sequence,defect severity,and overall quality of the casting.A novel machine learning strategy was developed to design the counter pressure casting gating system of a large thin-walled cabin casting.A high-quality dataset was established through orthogonal experiments combined with design criteria for the gating system.Spearman’s correlation analysis was used to select high-quality features.The gating system dimensions were predicted using a gated recurrent unit(GRU)recurrent neural network and an elastic network model.Using EasyCast and ProCAST casting software,a comparative analysis of the flow field,temperature field,and solidification field can be conducted to demonstrate the achievement of steady filling and top-down sequential solidification.Compared to the empirical formula method,this method eliminates trial-and-error iterations,reduces porosity,reduces casting defect volume from 11.23 cubic centimeters to 2.23 cubic centimeters,eliminates internal casting defects through the incorporation of an internally cooled iron,fulfilling the goal of intelligent gating system design.展开更多
文摘低温共烧陶瓷(Low Temperature Co-fired Ceramics,LTCC)具有优异的介电性能、热稳定性和多功能集成能力,在5G/6G通信、毫米波雷达、卫星载荷、系统级封装等领域得到广泛应用。然而,传统工艺存在两方面显著局限:一是受成型方式制约,难以实现曲面多层基板的高精度制造;二是工艺流程复杂且对批次规模依赖性强,难以满足单件、小批基板的快速验证需求。增材制造基于逐层堆叠、按需沉积的独特技术路径,为突破上述瓶颈提供了创新性解决方案。文中系统综述了LTCC增材制造所涉及的材料制备、成型工艺方面的研究动态,分析了当前存在的关键问题,并展望了未来发展方向。
基金supported by the National Natural Science Foundation of China(Nos.52074246,52275390,52375394)the National Defense Basic Scientific Research Program of China(No.JCKY2020408B002)the Key R&D Program of Shanxi Province(No.202102050201011).
文摘The design of casting gating system directly determines the solidification sequence,defect severity,and overall quality of the casting.A novel machine learning strategy was developed to design the counter pressure casting gating system of a large thin-walled cabin casting.A high-quality dataset was established through orthogonal experiments combined with design criteria for the gating system.Spearman’s correlation analysis was used to select high-quality features.The gating system dimensions were predicted using a gated recurrent unit(GRU)recurrent neural network and an elastic network model.Using EasyCast and ProCAST casting software,a comparative analysis of the flow field,temperature field,and solidification field can be conducted to demonstrate the achievement of steady filling and top-down sequential solidification.Compared to the empirical formula method,this method eliminates trial-and-error iterations,reduces porosity,reduces casting defect volume from 11.23 cubic centimeters to 2.23 cubic centimeters,eliminates internal casting defects through the incorporation of an internally cooled iron,fulfilling the goal of intelligent gating system design.
