This paper introduces open-source contributions designed to accelerate research in volumetric multi-material additive manufacturing and metamaterial design. We present a flexible Python-based API facilitating parametric expression of multi-material gradients, integration with external libraries, multi-material lattice structure design, and interoperability with finite element modeling. Novel implicit multi-material modeling techniques enable detailed spatial grading at multiple scales within lattice structures. Additionally, our framework integrates with finite element analysis, offering predictive simulations via adaptive mesh sizing and direct import of simulation results to guide material distributions. Practical case studies illustrate the utility of these contributions, including functionally graded lattices, algorithmically generated structures, and simulation-informed designs, exemplified by a multi-material bicycle seat optimized for mechanical performance and rider comfort. Finally, we introduce a mesh export strategy compatible with standard slicing software, significantly broadening the accessibility and adoption of functionality graded computational design methodologies for multi-material fabrication.

翻译：本文介绍了旨在加速体素化多材料增材制造与超材料设计研究的开源贡献。我们提出了一种基于Python的灵活API，该接口支持多材料梯度的参数化表达、与外部库的集成、多材料晶格结构设计以及与有限元建模的互操作性。新颖的隐式多材料建模技术实现了晶格结构内多尺度精细空间梯度分布。此外，我们的框架集成了有限元分析功能，通过自适应网格划分提供预测性仿真，并支持直接导入仿真结果以指导材料分布。实际案例研究展示了这些贡献的实用性，包括功能梯度晶格、算法生成结构以及仿真驱动设计，例如以机械性能和骑行者舒适度为目标优化的多材料自行车座垫。最后，我们提出了一种兼容标准切片软件的网格导出策略，显著拓宽了面向多材料制造的功能梯度计算设计方法的可及性与应用范围。