Zhongtai: The AI wave is driving up demand, high-end MLCC ceramic powder is expected to see both quantity and price increase.
Sinotrans Securities released a research report stating that the penetration of AI terminals such as AI smartphones and AI PCs, combined with the increase in sales of new energy vehicles, is driving a steady increase in the shipment volume of MLCCs in the non-AI server field.
Zhongtai released a research report stating that the penetration of AI terminals such as AI smartphones and AI PCs, combined with the increase in sales of new energy vehicles, is driving a steady increase in shipments of MLCC in the non-AI server sector. In addition, the high computational power requirements are pushing AI server MLCC towards smaller size, higher capacity, and higher reliability upgrades. The design of multi-layer stacks increases the powder consumption, while ultra-fine high-purity processes increase the value of the powder, driving the demand for ceramic powder for AI server MLCC from 0.45 million tons in 2025 to 3.82 million tons in 2030, with a CAGR of 53.4%.
Key points from Zhongtai include:
Demand side: The AI wave is spurring high-end MLCC shipments, and high-end MLCC ceramic powder is expected to see a simultaneous increase in quantity and price.
Calculation of AI server MLCC ceramic powder demand: Due to the complex power supply architecture and increased GPU power consumption of AI servers, the usage of MLCC per machine has increased from around 2,000 pieces in traditional servers to tens of thousands. According to the calculations, the global demand for AI server MLCC is expected to increase from 64.2 billion pieces in 2025 to 381.6 billion pieces in 2030, with a CAGR of 42.8%. The high computational power requirements are driving AI server MLCC towards smaller size, higher capacity, and higher reliability upgrades. The demand for ceramic powder for AI server MLCC is expected to increase from 0.45 million tons in 2025 to 3.82 million tons in 2030, with a CAGR of 53.4%.
With a volume-price resonance, assuming an average price of 100,000 yuan/ton for ceramic powder for AI server MLCC in 2026, with a 10% annual increase, reaching 146,000 yuan/ton by 2030, the corresponding market size in 2030 would be 5.6 billion yuan, with a CAGR of 65%. If additional price increases due to tight supply and product iteration at 50%/100%/200%, the market size for ceramic powder for AI server MLCC in 2030 could potentially expand to 8.4/11.1/16.7 billion yuan.
Calculation of non-AI server MLCC ceramic powder demand: The increasing penetration of AI terminals such as AI smartphones and AI PCs, combined with the increase in sales of new energy vehicles, is driving a steady increase in shipments of MLCC in the non-AI server sector. According to calculations, the usage of non-AI server MLCC is expected to increase from 5.2 trillion pieces in 2025 to 7.1 trillion pieces in 2030, with a CAGR of 6.4%, including CAGRs of 2.7%, 5.4%, 11.9%, and 6.3% for smartphones, computers, cars, and regular servers, respectively.
Based on calculations of non-AI server MLCC usage, the corresponding demand for ceramic powder was further calculated. Different levels of MLCC products have different specifications, layers, and capacitance values. Assuming the consumption of ceramic powder per billion pieces is 0.8 tons for regular phones and computers, 1.8 tons for AI phones and computers, 1.5 tons for fuel-powered cars/new energy cars, 1.5 tons for regular servers, and 1.3 tons for household appliances and other applications, the demand for ceramic powder for non-AI server MLCC is projected to be 78,000 tons in 2030, with a CAGR of 10.5% from 2025 to 2030.
Supply side: Japanese manufacturers dominate the industry, with Shandong Sinocera Functional Material rising strongly.
The global market for MLCC ceramic powder is dominated by Japanese companies, with five Japanese enterprises including Sakai Chemical, Nippon Chemical, Fujita Titanium, Kyocera, and Toho accounting for a total of 65% market share. Shandong Sinocera Functional Material is a leading domestic manufacturer of ceramic powder, with a domestic market share of over 80%. They have also made breakthroughs in high-end powder production and have established stable supply relationships with international giants such as Samsung Electronics. In addition, some MLCC manufacturers such as Murata in Japan, Samsung Electronics, Sunlord Electronics, and Chaozhou Three-Circle (Group) in China, also have the ability to produce their own powder, but there is still a gap in supply, necessitating external procurement. The industry as a whole presents a coexistence of external procurement and in-house production.
Three weight-price opportunities for MLCC ceramic powder: supply-demand gap, rare earth control, and iterative upgrades.
1) Supply-demand gap: Based on the current situation of the NVIDIA AI server industry chain, the supply side mainly considers the external capacity of Japanese powder manufacturers and Shandong Sinocera Functional Material, as well as the self-supply capacity of Murata in Japan and Sunlord Electronics. The total capacity is estimated to be 17,000 tons by 2027. Considering the continued demand for AI servers, it is assumed that by 2028, Shandong Sinocera Functional Material (supplying Samsung Electronics), Sakai Chemical (supplying Murata), Kyocera (supplying Sunlord Electronics), Murata and other companies will continue to expand production by 60% based on their existing high-end powder production capacity, with new capacity gradually released starting in 2029. The results show that the supply-demand situation will start to tighten in 2028, with supply gaps of 2,900 and 13,100 tons in 2029 and 2030, respectively.
2) Rare earth control: Rare earth oxides (such as dysprosium oxide) are essential components of MLCC formula powders. Under the background of rare earth control, Japanese MLCC manufacturers are under pressure in supplying formula powders, while domestic manufacturers are expected to take over Japanese market share transfers by relying on rare earth resources and technological breakthroughs.
3) Iterative upgrades: MLCC ceramic powder benefits from the three-level amplification effect of the increasing demand for AI servers, the increasing amount of MLCC per machine, and the increasing consumption of ceramic powder. Furthermore, the value of high-end ceramic powder increases with the upgrades and iterations of MLCC, leading to a potential round of structural upward movement dominated by technical premiums, with price flexibility anticipated.
Shandong Sinocera Functional Material: A domestic leader in MLCC ceramic powder, expected to benefit from both the general economic upturn and supply chain restructuring.
Shandong Sinocera Functional Material is an absolute leader in domestic MLCC ceramic powder, with a domestic market share of over 80%. They are one of the few companies in China that have core technology in hydrothermal barium titanate production and can produce high-end powders in the range of 50-100nm. The company's current production capacity for conventional powders is 10,000 tons, and they are currently focusing on setting up 5,000 tons of production capacity for high-end powders for AI servers and automotive applications. They have already completed 2,000 tons of this capacity and are working on stabilizing bulk supply of high-end powders to international customers such as Samsung Electronics. With strong technical capabilities, the company has successfully broken the long-term monopoly of Japanese manufacturers in the high-end market, and their high-end powder products are expected to see growth driven by the AI trend. Additionally, under the background of rare earth control, leveraging domestic rare earth resources and high-end powder production capabilities, the company is positioned to capture the transition of market share for formula powders from overseas.
Risk warning: risks of lower-than-expected downstream demand, capacity expansion exceeding expectations, uncertainty in rare earth export policies, fluctuation in raw material prices, intensifying industry competition, risks of third-party data distortion and lagging information, and risks of deviations in data and results calculations.
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