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市場調查報告書
商品編碼
1660645
化學和材料研發虛擬模擬和建模技術的成長機會（2024-2029）Growth Opportunities in Virtual Simulation and Modeling Technologies for Chemicals and Materials R&D, 2024-2029 |
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虛擬模擬和建模技術正在透過增強設計、最佳化流程和永續性來改變化學和材料的研究與開發
虛擬模擬和建模技術正在透過精確設計、測試和最佳化材料和工藝，改變化學和材料的研究與開發（R&D）。這些技術使得複雜化學反應的建模變得更加容易，並且能夠準確預測材料特性，從而使生產過程更加高效，並減少了昂貴且耗時的物理實驗的需要。
這份 Frost & Sullivan 報告檢驗了這些技術的變革潛力，特別關注實現永續性、效率和成本效益的創新。本報告全面分析了化學和材料研究與開發中面臨的關鍵挑戰，這些挑戰可以透過虛擬模擬和建模技術來緩解。本報告探討了模擬建模的最新進展，包括人工智慧（AI）和機器學習（ML）。此外，它還檢驗了這些技術在汽車、航太、製藥和建築等各個領域的應用。該報告概述了更廣泛的生態系統，重點介紹了推動發展和採用的關鍵公司、學術貢獻、專利狀況和投資活動。它還強調了該行業的促進因素和限制因素以及市場相關人員和相關人員可以利用的潛在成長機會。
目錄
戰略問題
- 成長為何變得越來越艱難？
- The Strategic Imperative 8（TM）
- 三大策略挑戰對化學和材料研發產業虛擬模擬和建模技術的影響
- 成長機會推動Growth Pipeline Engine（TM）™
- 調查方法
成長機會分析
- 分析範圍
- 調查細分
成長要素
- 關鍵問題
- 成長動力
- 成長抑制因素
技術分析
- 技術進步
專利和研究論文
- 專利概覽
- 研究論文概述
相關人員分析
- 主要企業
- 學術機構的重要研究貢獻與突破
- 主要相關人員之間的顯著合作
案例研究
- 案例研究1：Dotmatics 與BASF農業解決方案合作推出「數據到價值」舉措
- 案例研究2：Kebotix 利用 AI 驅動的結構功能關係建模加速潤滑劑開發
- 案例研究3：Schrödinger 和 Evonik 利用 MD 模擬增強可回收輪胎材料的開發
- 案例研究4：使用 BosonQ Psi 和 materialsIN Quantum ML 最佳化混凝土表面裂紋檢測
資金籌措和投資
- 重大投資
分析師觀點與未來展望
- 未來趨勢
- 影響分析
- 分析師觀點
成長機會領域
- 成長機會1：用於 MD 模擬的量子啟發演算法
- 成長機會二：基於人工智慧的材料研發永續性評估工具
- 成長機會3：機器人增強自動化，實現預測材料發現
- 成長機會4：化學和材料製造流程最佳化的數位雙胞胎
附錄
- 技術就緒程度 (TRL)：描述
後續步驟Next steps
- 成長機會的好處和影響
- 後續步驟Next steps
- 免責聲明
Virtual simulation and modeling technologies are revolutionizing chemicals and materials R&D by enhancing design, optimizing processes, and driving sustainability
Virtual simulation and modeling technologies are transforming chemicals and materials research and development (R&D) by enabling precise design, testing, and optimization of materials and processes. These technologies facilitate the modeling of complex chemical reactions, allow for accurate predictions of material properties, and make production processes more efficient while curtailing the need for costly and time-consuming physical experiments.
This Frost & Sullivan report examines the transformative potential of these technologies, focusing particularly on innovations that enable sustainability, efficiency, and cost-effectiveness. The report provides a comprehensive analysis of the critical challenges faced in chemicals and materials R&D that can be mitigated through virtual simulation and modeling technologies. It explores the latest advancements in simulation and modeling, including artificial intelligence (AI) and machine learning (ML). Additionally, it examines the application of these technologies across various sectors, such as automotive, aerospace, pharmaceuticals, and construction. The report provides an overview of the broader ecosystem, highlighting the key players, academic contributions, patent landscapes, and investment activities driving development and adoption. It identifies the factors boosting and restraining the industry and the potential growth opportunities arising from this space for market players and stakeholders to leverage.
Table of Contents
Strategic Imperatives
- Why Is It Increasingly Difficult to Grow?
- The Strategic Imperative 8™
- The Impact of the Top 3 Strategic Imperatives on Virtual Simulation and Modeling Technologies in the Chemicals and Materials R&D Industry
- Growth Opportunities Fuel the Growth Pipeline Engine™
- Research Methodology
Growth Opportunity Analysis
- Scope of Analysis
- Research Segmentation
Growth Generator
- Key Challenges
- Growth Drivers
- Growth Restraints
Technology Analysis
- Technology Advances
Patent and Research Publications
- Overview of Patents
- Overview of Research Publications
Stakeholder Analysis
- Key Companies
- Important Research Contributions and Breakthroughs from Academic Institutions
- Notable Collaborations Between Key Stakeholders
Case Studies
- Case Study 1: Dotmatics Deploys 'Data to Value' Initiative with BASF Agricultural Solutions
- Case Study 2: Kebotix Accelerates Lubricant Development with AI-driven Structure-Function Relationship Modeling
- Case Study 3: Schrodinger and Evonik Enhance Recyclable Tire Materials Development with MD Simulations
- Case Study 4: BosonQ Psi and materialsIN Optimize Surface Crack Detection in Concrete with Quantum ML
Funding and Investments
- Key Investments
Analyst Perspective and Future Outlook
- Future-looking Trends
- Impact Analysis
- Analyst Perspective
Growth Opportunity Universe
- Growth Opportunity 1: Quantum-inspired Algorithms for MD Simulations
- Growth Opportunity 2: AI-powered Sustainability Assessment Tools for Materials R&D
- Growth Opportunity 3: Robotics-enhanced Automation for Predictive Materials Discovery
- Growth Opportunity 4: Digital Twins for Process Optimization in Chemicals and Materials Manufacturing
Appendix
- Technology Readiness Levels (TRL): Explanation
Next Steps
- Benefits and Impacts of Growth Opportunities
- Next Steps
- Legal Disclaimer
