Against the backdrop of the continuously increasing demand for data transmission speed in AI robots, the performance of flexible copper-clad laminate (FCCL), as the core substrate of soft hard junction board (R-FPC), directly determines the transmission quality of high-frequency signals between the robot's "brain" and "limbs", becoming a key carrier to break through the bottleneck of signal delay.

In high-frequency scenarios, the control commands and multi-sensor data (such as LiDAR and high-definition images) of AI robots need to interact in real-time at a rate of 10Gbps or more. Traditional FCCL, due to large fluctuations in substrate dielectric constant (Dk) and high dielectric loss (Df), is prone to signal attenuation and crosstalk, affecting the accuracy of robot actions. FCCL, designed specifically for high frequencies, uses low loss substrates such as modified polyimide (PI) and liquid crystal polymer (LCP) to stabilize Dk between 2.2-3.0 and reduce Df to 0.001-0.003, significantly reducing energy loss in high-frequency signal transmission. Taking the industrial sorting AI robot as an example, equipped with LCP substrate FCCL soft hard bonding board, the transmission delay of image recognition data can be shortened to less than 5ms, ensuring that the robot accurately grasps target items in high-speed sorting.

In addition, the structural design of high-frequency FCCL is also continuously being optimized. To reduce signal interference, the industry has launched a symmetrical structure FCCL of "copper foil low loss substrate copper foil", which reduces impedance fluctuations in signal transmission by controlling the uniformity of substrate thickness (deviation ≤ 5%); Some products are also subjected to micro roughening treatment on the surface of the copper foil to enhance the adhesion with the substrate, avoid delamination under high-frequency vibration, and ensure the signal stability of the AI robot during continuous operation. At present, high-frequency FCCL has become a standard configuration for high-end AI robots (such as precision assembly robots and medical surgical robots) with soft and hard joint boards, and its performance iteration is driving robots to upgrade to "higher response speed and higher control accuracy".