## 1 Introduction
From this perspective, when the number of 3D virtual items in the sensory input exceeds the number of items that can be stored, the excess virtual items will not be stored. Therefore, based on slot-based theory, the presentation form of 3D virtual objects should not have an effect on the VWM capacity of MAR interfaces, regardless of the complexity. On the other side, the resource-based theory assumes that VWM capacity is a flexible and divisible resource that is affected by both visual information load and the number of objects [31]. Extant research has shown that both internal and external variability can lead to changes in VWM capacity [32; 33]. For example, [PERSON] et al. found that more meaningful stimuli recruit additional working memory resources, thus making them better remembered [34]. According to the flexible resource model, as the complexity of 3D virtual objects increases in the MAR interface, the amount of resources allocated to each item also should decrease, resulting in reduced memory capacity and lower memory accuracy. Figure 1 shows how a display of four 3D virtual objects would be represented in MAR according to these two theory classes. Regardless of these differences in the two theoretical models, most researchers would agree that VWM capacity is measured as Cowan's K [35]. Given that no prior studies have experimentally examined the impact of virtual 3D elements on VWM capacity in AR interface for mobile phones, it is unclear whether the AR virtual-reality fusion nature of 3D virtual objects would affect VWM capacity. In addition, previous studies on the cognition of AR information indicated conflicting results: on the one hand, some prior studies have shown that some AR characteristics (e.g., environmental embedding and simulated physical control) can reduce consumers' cognitive load while enhancing the cognitive fluency and service experiences [36; 37]. For example, [PERSON] et al. have shown that MAR technology would help reduce the cognitive load of the user [17]. [PERSON] et al. have found that the AR display method can provide better spatial knowledge acquisition [38]. Based on these studies, it can be assumed that the visual processing of 3D virtual objects in the MAR interface may have positive encoding advantages. On the other hand, some other studies argued that AR is cognitively demanding and can lead to poorer performance [39; 40; 41]. For example, [PERSON] et al. observed that perceiving 3D virtual objects in AR interfaces requires remembering perspective depth information, the graphical alterations of angles and virtual environments at the same time [42]. [PERSON] et al. have found that the negative characteristics of AR include a reduced field of view and visual distortions in the peripheral areas of the field of view [43]. These studies tend to suggest that the AR-related properties in 3D virtual objects are distracting and provide too much information at once [44; 45]. From this perspective, as the complexity of the AR-related information contained in a 3D virtual object increases, the difficulty of recognising and remembering this object also increases. Moreover, while the notion that relatively fixed VWM capacity (i.e., a single-center capacity limit of about four chunks) seems intuitive [46; 47], the stimuli used in these previous studies were usually meaningless one- or two-dimensional shapes or abstract graphics, which have little in common with AR information. The VWM capacity in the traditional digital interfaces may not be applicable to the MAR interface. Based on the above statements, the present study attempted to answer the following research questions:  
Question 1: Is the user's behaviour in MAR interfaces influenced by the complexity and quantity of 3D virtual objects displayed? Question 2: Do highly complex 3D virtual objects reduce the VWM capacity and memory precision? Question 3: Is the VWM capacity for 3D virtual objects in MAR interfaces fixed?