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科學

AI驅動材料開發

CuspAI 利用自主AI加快材料開發

AI 驅動的材料研發技術,正協助 CuspAI 透過連結人工智能、科學數據、運算資源及實體實驗室,加速先進材料的開發進程。其 AI Materials Foundry 平台,運用 MIRA 代理式平台,生成候選材料、預測其特性、開發合成路徑,並協調實驗測試工作。相關結果其後回饋至系統之中,改善後續的研發週期。此平台已透過為 Kemira 篩選 300 萬億種分子結構,並於六個月內產出 20 個經驗證候選材料,展現其實際潛力。

對企業而言,此方式有望大幅減少開發專用材料所需的時間及資源。半導體、清潔能源及先進製造業企業,可共用 AI、數據及實驗室基礎設施,而毋須自行構建每一項能力。這種協作模式,有望加快商業化進程,同時協助企業更迅速地應對不斷變化的材料需求。

英文原文

AI-powered materials discovery is helping CuspAI accelerate the development of advanced materials by connecting artificial intelligence, scientific data, computing resources and physical laboratories. Its AI Materials Foundry uses the MIRA agentic platform to generate material candidates, predict their properties, develop synthesis routes and coordinate experimental testing. Results are then fed back into the system to improve subsequent discovery cycles. The platform has already demonstrated its potential by screening 300 trillion molecular structures for Kemira and producing 20 validated candidates within six months.

For businesses, this approach could significantly reduce the time and resources required to develop specialized materials. Companies in semiconductors, clean energy and advanced manufacturing can access shared AI, data and laboratory infrastructure rather than building every capability internally. This collaborative model could accelerate commercialization while helping businesses respond more quickly to changing material requirements.

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AI驅動材料開發
來源
Trend Hunter
發布
2026-08-10
品類
Science
出處
fool, businesswire

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