在合金凝固枝晶生长元胞自动机(CA)模型中，正方形元胞、邻胞构造、尖锐界面模型固有特性引起的各向异性，给枝晶择优取向生长的模拟研究带来了诸多限制，特别是难以模拟六重对称合金的枝晶生长行为。本工作在借鉴相场弥散界面模型中相场变量梯度能项建模与求解方法的基础上，构建和推导了考虑元胞状态变量的场变量梯度泛函及场变量扩散方程，提出了一种新的场变量扩散元胞自动机(FCA)模型。模型考虑了成分过冷和Gibbs-Thomson效应，采用“浓度势法”处理溶质扩散和再分配，依据杠杆定理处理界面凝固的生长动力学，通过引入场变量扩散项修正界面元胞的生长速率，并利用不同条件下Mg-6%Al (质量分数)合金的枝晶生长结果对模型进行了验证。在正方形网格离散方式下，六重对称Mg-6%Al合金的枝晶尖端稳态特征和生长动力学与LGK模型的预测结果基本吻合，模型能够呈现多重合金枝晶形貌的对称性以及枝晶的随机择优取向生长，还原凝固过程的枝晶臂生长、竞争和粗化等行为。

The cellular automaton (CA) model exhibits a notable disadvantage of substantial anisotropy, triggered by the square cells, adjacent cell structures, and intrinsic features of the sharp interface model. This disadvantage leads to limitations in simulating dendritic growth with random preferred orientations during the solidification of alloys, particularly in the context of sixfold symmetric alloys. In the present study, drawing inspiration from the processing concept of diffuse interfaces and the gradient energy term in the phase field model, a function concerning the gradient of the field variable associated with the cell state is constructed and the diffusion equation for the field variable is derived. Consequently, a novel field-variable diffusion CA (FCA) model is proposed, which addresses the growth kinetics of the solid-liquid interface in accordance with the lever rule. The proposed model considers constitutional supercooling and the Gibbs-Thomson effect, employing the concentration potential method to manage solute diffusion and redistribution. The growth rate of interface cells is modulated by introducing a field-variable diffusion term. The analysis reveals that within the square-grid discretization mode, the model demonstrates validation under various conditions, focusing on the steady-state characteristics of the dendritic tip and growth kinetics of the sixfold symmetric Mg-6%Al (mass fraction) alloy. The findings are consistent with the predictions of the LGK model, suggesting that the FCA model can effectively emulate dendritic morphology with multifold symmetry and random preferred orientations, and elucidate critical dendritic arm behaviors, such as competitive dendritic growth and coarsening.