Alternative protein sources: growing the next generation computational modelling framework

替代蛋白质空间是目前最具活力的科学领域之一。即使考虑到农业的进步，可用土地面积的缩小也意味着可持续的未来与我们创造和支持清洁食物来源的能力密切相关。计算建模具有巨大的（而且在很大程度上尚未开发的）潜力，可以创新仍处于起步阶段的技术空间。我们将使用最先进的技术-多物理流体力学，高性能计算和数据驱动方法-来设计一个由来自世界各地的优秀实验和工业合作者支持的多功能开源建模框架。

The alternative protein space represents one of the most dynamic scientific areas at present. Shrinking usable land mass, even accounting for agricultural advances, means a sustainable future is tightly linked with our ability to create and support clean food sources. Computational modelling has an immense (and largely untapped) potential to innovate a technological space still in its infancy. We will use a combination of state-of-the-art techniques - multi-physics fluid mechanics, high performance computing and data-driven approaches - to design a versatile open-source modelling framework supported by fantastic experimental and industrial collaborators from around the world.