Kernel died when loading a dataset in Python: why does it happen?

I am trying to load a dataset of 7000 .mat files in Python as a 7000-d tensor with each entry of shape 100 x 100 x 100 x 3. The whole dataset is less than 80 MB. I am using Spyder. The code is as follows

dataDir = "/Users/..."data= []x_train = np.empty([7165, 100*100*100*3])x_train = x_train.reshape([7165, 100, 100, 100, 3])i = 0;for file in sorted_alphanumeric(os.listdir( dataDir )):    data = scipy.io.loadmat( dataDir+file )   #store data as LIST    x_train[i] = np.array(data['tensor'])    i = i + 1

However after about 2300 lines read, the kernel dies and the program stops running. Why does the kernel die? How can I store the dataset? It seems to me that the dataset is not that huge and the "Memory" key in the Console is always around 76%.