《商道创投网》2025年11月19日从官方获悉：苏州材科源图科技有限公司（以下简称"材科源图"）近日 完成了由中科创星领投，元禾控股与亿合资本跟投的数千万元天使轮融资。 《商道创投网》创业家会员·单位简介 材科源图是一家专注于"数据×智能双驱动的材料开发平台"的科技企业。公司坐落于中国苏州，与姑苏 实验室合作设立研发中心，汇聚了材料科学与人工智能领域的顶尖跨界人才。凭借独有的高质量数据库 与全链条智能材料开发平台，材科源图致力于为全球工业界提供革命性解决方案，加速能源材料技术的 研发与产业落地，推动材料产业迈向智能化、数字化的新时代。 《商道创投网》创业家会员·本轮融资用途是什么？ 材科源图创始人表示，本轮融资将重点用于核心技术研发，包括数据库扩建、模型开发、高通量平台搭 建，以及应用场景的商业化落地。通过这些投入，公司将巩固在"AI for Materials"领域的领先地位，进 一步提升材料研发效率，降低试错成本，为突破产业瓶颈提供更高效的解决方案。 《商道创投网》创投家会员·本轮投资原因是什么？ 中科创星相关负责人表示，投资材科源图是基于其开创性的"数据×智能双驱动的材料开发平台"。该平 台通过融合高保 ...

苏州材科源图科技有限公司（以下简称"材科源图"）近日宣布完成数千万元天使轮融资。本轮融资由中科创星领投，元禾控股与亿合资本共同参与。融资将 重点用于核心技术研发：数据库扩建、模型开发、高通量平台搭建，及应用场景商业化落地，进一步巩固公司在"AI for Materials"领域的领先地位。 作为专注于"投小、投早、投长期、投硬科技"的头部机构，中科创星表示，材科源图开创了"数据×智能双驱动的材料开发平台"，通过融合高保真材料数据 库、物理化学理论模型约束、大语言模型、以及高通量合成技术，实现先进功能材料的智能研发，将材料研发效率提升百倍以上，推动材料研发从传统"试 错型"实验转向"AI驱动"的智能设计新范式。 液相材料制备高通量全流程研发线 材科源图的创立初期秉持着 "愚公移山"的精神：投入超百名领域专家，历时七年，聚焦十余类关键能源材料领域，通过系统化的标注、挖掘与清洗，构建 了百万级真实材料数据库。同时，结合公司自主研发的120余项物理模型，开发出深度融合物理化学机理的材料AI智能体，搭建了"AI设计—智能合成—自 动测试—反馈优化"的全流程智能化材料研发平台，大幅缩短了先进功能材料的研发周期，显著降低了 ...

投资界11月18日消息，苏州材科源图科技有限公司（以下简称"材科源图"）近日宣布完成数千万元天使 轮融资。本轮融资由中科创星领投，元禾控股与亿合资本共同参与。融资将重点用于核心技术研发：数 据库扩建、模型开发、高通量平台搭建，及应用场景商业化落地，进一步巩固公司在"AI for Materials"领域的领先地位。 中科创星表示，材科源图开创了"数据×智能双驱动的材料开发平台"，通过融合高保真材料数据库、物 理化学理论模型约束、大语言模型、以及高通量合成技术，实现先进功能材料的智能研发，将材料研发 效率提升百倍以上，推动材料研发从传统"试错型"实验转向"AI驱动"的智能设计新范式。 材科源图的创立初期秉持着 "愚公移山"的精神：投入超百名领域专家，历时七年，聚焦十余类关键能 源材料领域，通过系统化的标注、挖掘与清洗，构建了百万级真实材料数据库。同时，结合公司自主研 发的120余项物理模型，开发出深度融合物理化学机理的材料AI智能体，搭建了"AI设计智能合成自动 测试反馈优化"的全流程智能化材料研发平台，大幅缩短了先进功能材料的研发周期，显著降低了试错 成本，为突破产业瓶颈提供了高效解决方案。 目前，材科源图已 ...

1. 【中国通号中标青藏铁路无人机反制示范项目】近日，中国通号成功中标青藏铁路无人机反制示范 项目。项目采用通号低空公司自主研发的铁路专用无人机智能防护系统，构建起覆盖远、中、近全距 离的立体防护网。该系统融合了无线电侦测、AI光电跟踪、多点协同反制三大核心技术架构。（新浪 财经） 2.【谷歌计划在美国得州投资400亿美元新建三座数据中心】当地时间11月14日，谷歌宣布计划在美 国得州投资400亿美元新建三座数据中心，这项投资将持续到2027年。Alphabet首席执行官皮查伊 表示，这项投资将创造数千个就业岗位，为大学生和电工学徒提供技能培训，并加快得州各地能源可 负担性计划的推进。（界面新闻） 3. 【杭州湾跨海铁路桥北航道桥钢梁开始架设】11月15日，在浙江杭州湾海盐侧离岸约0.4公里的海 面上，重达626吨的钢梁在浮吊船的吊装下，精准架设到8号主墩上，标志着由沪杭客专公司建设管 理、中铁大桥局承建的杭州湾跨海铁路桥北航道桥钢梁开始架设，桥梁正式进入上部结构施工阶段。 杭州湾跨海铁路桥是南通至宁波高速铁路（简称通甬高铁）控制性工程，位于既有杭州湾跨海公路大 桥上游约7公里处，全长29.2公里，由北、中、 ...

Core Insights - The event highlighted the transformative role of AI in the materials industry, emphasizing its potential to drive innovation and reshape research paradigms [1][3]. Group 1: AI's Impact on Material R&D - AI is fundamentally changing the way materials are developed, moving from imitation to independent innovation [3]. - Key challenges in material R&D include identifying suitable molecular structures for specific applications and optimizing synthesis routes [3]. - Companies are investing in AI capabilities, such as establishing computational simulation labs and collaborating with universities and software developers, aiming to create industry-specific models and databases by 2026 [3]. Group 2: Investment Opportunities - Investment opportunities in the materials sector are identified in two areas: materials with significant production value and import substitution potential, and those leveraging AI for breakthroughs in performance and cost efficiency [3][4]. - The integration of AI and big data is expected to unlock vast potential in biomedicine and new materials development [4]. Group 3: Future Trends and Expectations - The next five years are anticipated to mark the beginning of "AI for Science," progressing towards a cycle of AI-driven research and applications [5]. - The industry is expected to reach a tipping point in four to five years, leading to a surge in material innovation as data accumulates [4].

Core Points - The 9th International Forum on Materials Gene Engineering will be held from November 19-23, 2025, in Xi'an, Shaanxi Province, China, aiming to promote the development of foundational theories, cutting-edge technologies, and key equipment in the field of materials gene engineering [1][2]. Group 1: Forum Overview - The forum has successfully held 8 sessions since 2017, attracting over 310 academicians and more than 8,000 domestic representatives, significantly impacting the development and application of disruptive technologies in materials science [1]. - The event is co-hosted by the National New Materials Big Data Innovation Alliance and the Chinese Materials Research Society, with several universities and research institutes as co-organizers [2]. Group 2: Themes and Topics - Key themes include efficient material computation and intelligent design, transformative experimental technologies, AI applications in materials science, big data in materials, and the intelligent development and application of the materials industry [2][12][15][18][20]. Group 3: Event Schedule - Important dates include online registration and poster submission by November 9, 2025, on-site registration on November 19, and various sessions and meetings scheduled from November 20 to 23 [2][5]. Group 4: Organizational Structure - The organizing committee includes prominent figures from various institutions, with a focus on advancing materials science through collaboration and innovation [3][4]. Group 5: Registration Information - Registration fees are set at RMB 2,800 (approximately USD 400) for formal representatives and RMB 1,800 (approximately USD 260) for student representatives, with accommodation and meals arranged during the forum [5]. Group 6: Academic Reports - The forum will feature a range of academic reports from distinguished speakers, including members of the Chinese Academy of Engineering and international experts, covering various aspects of materials science and engineering [8][9][10]. Group 7: Supporting Institutions - Numerous supporting institutions, including universities and research centers, are involved in the forum, highlighting the collaborative effort in advancing materials gene engineering [3][4]. Group 8: Future Directions - The forum aims to accelerate the integration of artificial intelligence in materials research and development, fostering innovation and collaboration across the industry [1][2][20].

Group 1 - Shenzhen Xinyan Zhichai Technology Co., Ltd. has undergone a business change, with new shareholders including Jingrui Electric Materials (300655) [1] - The registered capital of Xinyan Zhichai has increased to 1.1666 million yuan [1] - Xinyan Zhichai is identified as an innovative company focused on AI-driven material research and development [1]

Core Insights - A Russian technical university has developed a waste-free recycling process for used car tires and has applied for a patent for this technology [1] - The new method allows for 100% conversion of old tires into raw materials for resin production, addressing the issue of waste generated in traditional tire recycling methods [1] Group 1: Technology and Process - Traditional tire recycling methods typically involve shredding tires into rubber granules, which generates waste in the form of tire cord fabric [1] - The new process treats rubber and polyester simultaneously in the same reaction unit, utilizing carbon black released during the process as a stabilizer to prevent premature curing of the resin [1] - The mechanical properties of the materials produced through this new process are significantly enhanced [1] Group 2: Applications and Market Potential - The resin produced from this process exhibits high strength and hardness after curing, making it suitable for the production of composite materials and construction materials [1] - The university claims that this innovation has broad application prospects in various industries [1]

Core Viewpoint - The article highlights the achievements of 35 innovators under the age of 35 in various fields such as climate and energy, artificial intelligence, biotechnology, computing, and materials science, showcasing their groundbreaking contributions and potential impact on their respective industries [6][11][60]. Climate and Energy - Innovators in this sector are developing advanced technologies for decarbonization, with applications across shipping, fashion, and other industries. They are also exploring new methods for sustainable energy and innovative uses for carbon capture [11]. - Iwnetim Abate is working on producing ammonia using underground heat and pressure, aiming to reduce carbon emissions associated with traditional ammonia production, which contributes 1% to 2% of global CO2 emissions [13]. - Sarah Lamaison's company, Dioxycle, is developing a method to produce chemicals using electricity instead of fossil fuels, significantly reducing greenhouse gas emissions [16][17]. - Gaël Gobaille-Shaw's Mission Zero focuses on direct air capture technology to extract CO2 from the atmosphere, while his second company, Supercritical, aims to produce hydrogen efficiently [19][20]. Artificial Intelligence - Aditya Grover has developed ClimaX, an AI model that predicts weather and climate events, utilizing extensive datasets for improved accuracy [22][23]. - Neel Nanda is researching the interpretability of AI models to ensure their safe and beneficial development, focusing on understanding the decision-making processes of these models [34][35]. - Mark Chen has led advancements in AI models for image processing and code generation, contributing to the development of OpenAI's DALL·E and Codex [38][39]. - Akari Asai is working on retrieval-augmented generation technology to reduce AI hallucinations by allowing models to reference stored data before generating responses [51][52]. Biotechnology - Christian Kramme's company, Gameto, is developing artificial ovarian technology to assist IVF patients, aiming to reduce hormonal injections and stress during the process [62][63]. - Kevin Eisenfrats founded Contraline to create a long-lasting male contraceptive gel, with ongoing clinical trials to validate its effectiveness [64][65]. Computing and Materials Science - Pierre Forin's company, Calcarea, is developing a system to capture and store CO2 emissions from ships, with plans for commercial deployment by 2027 or 2028 [28][29]. - Neeka Mashouf's Rubi Laboratories is innovating a method to produce textiles by extracting CO2 directly from the atmosphere, aiming for sustainable fashion solutions [25][26].

Core Insights - Shenzhen Xinyan Smart Materials Technology Co., Ltd. has completed a seed round financing of tens of millions, led by semiconductor materials leader Jingrui Electric Materials and cornerstone investor Pujiang Capital [1][4] - The company focuses on integrating materials informatics with artificial intelligence, aiming to apply AI for Science technology in semiconductor core materials and new energy-related materials [3][4] - The proprietary "SynMatAI" system significantly reduces material performance prediction time to under 10 minutes with an accuracy rate exceeding 95%, while lowering R&D costs by over 70% [3][4] Company Overview - Xinyan Smart Materials is positioned as a technological pioneer in the fusion of materials informatics and AI, with a core team comprising members from leading institutions such as Huawei, ByteDance, and AIST Japan, boasting an 80% ratio of master's and doctoral degrees [3][4] - The company has successfully launched its intelligent R&D platform's V1 version and has been recognized as a "leading talent" in Yuhang District, indicating strong growth momentum [3][4] Investment and Strategic Partnerships - Jingrui Electric Materials will collaborate with Xinyan Smart Materials to develop joint solutions for photoresist formula optimization and advanced packaging materials [3][4] - Pujiang Capital aims to provide comprehensive post-investment support to help the company overcome technical bottlenecks and market barriers, enhancing its competitiveness and influence in the tech sector [4] Industry Context - The financing coincides with the release of the State Council's opinion on implementing "Artificial Intelligence +" actions, which emphasizes the acceleration of scientific discovery and innovation in technology development, particularly in new materials and semiconductors [4] - The AI-driven R&D model of Xinyan Smart Materials aligns well with policy directions, serving as a practical response to the challenges in high-end materials intelligent R&D [4] Future Goals - The company aims to compress the new material development cycle to one-third of the traditional model through AI-assisted design for semiconductor materials [5] - Xinyan Smart Materials is developing a "SaaS subscription + private customization" business model to efficiently meet the needs of both small laboratories and large enterprises, aligning its technological path with the intelligent upgrade of the materials industry [5]