Руководство по научной иллюстрации с ИИ для заявок на исследовательские гранты (NSFC, NSSFC, MOE)
Освойте методы научной иллюстрации с помощью ИИ для заявок на исследовательские гранты. Быстро создавайте технологические дорожные карты, исследовательские схемы и диаграммы механизмов, чтобы повысить качество вашей заявки.
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Тысячи исследователей используют SciDraw AI, чтобы за минуты создавать готовые к публикации иллюстрации для статей, заявок на гранты и подачи в журналы — без навыков дизайна.
In major research grant applications such as the National Natural Science Foundation of China (NSFC), National Social Science Foundation of China (NSSFC), and Ministry of Education Humanities and Social Sciences Fund, high-quality scientific diagrams are often a key factor in determining success.
Reviewers need to read numerous proposals in a short time. A clear, professional technical roadmap or research framework can:
Quickly convey research ideas: Help reviewers understand your research design within seconds
Demonstrate professionalism: Reflect the applicant's academic proficiency and project planning capabilities
Highlight innovations: Visually emphasize the unique value of your research
Enhance persuasiveness: Proposals with well-integrated graphics are more readable and attractive
However, traditional scientific illustration methods have many pain points:
Pain Point
Description
⏱️ Time-consuming
Manual drawing with Visio or PPT takes hours or even days
🎨 High design skills required
Color schemes, layouts, and typography require professional design knowledge
🔄 High revision costs
Significant rework needed when advisors or team members suggest changes
📐 Inconsistent formatting
Difficult to maintain consistent chart styles in collaborative work
SciDraw AI's AI scientific illustration feature was designed to solve these problems. Simply describe your research content, and AI can generate professional scientific charts in seconds, with SVG vector format export for free editing in PowerPoint or Adobe Illustrator.
NSFC focuses on basic research and applied basic research, with reviewers particularly concerned about scientific validity, innovation, and feasibility.
Common Diagram Types:
Diagram Type
Purpose
Recommended Section
Technical Roadmap
Show timeline and task breakdown of research plan
Research Proposal
Research Scheme Diagram
Present overall research design and methodology framework
Research Content
Mechanism Diagram
Explain scientific hypotheses and mechanisms
Project Rationale
Experimental Flowchart
Describe specific experimental steps and methods
Research Methods
Prompt Template - Technical Roadmap:
NSFC Technical Roadmap, 16:9 landscape format.Research Topic: [Your research topic]Three-Year Research Plan:- Year 1 (Foundation Phase): [Task 1], [Task 2], [Task 3]- Year 2 (Core Research Phase): [Task 1], [Task 2], [Task 3]- Year 3 (Application & Validation Phase): [Task 1], [Task 2], [Task 3]Use different colored modules for each phase, connect with arrows, annotate key milestones and expected outcomes.Blue-green color scheme, academic professional style, clear timeline layout.
NSFC Technical Roadmap, 16:9 landscape format.Research Topic: Deep Learning-based Medical Image Intelligent Diagnosis SystemThree-Year Research Plan:- Year 1: Dataset construction, model architecture design, benchmark experiments- Year 2: Multi-modal fusion, clinical validation, performance optimization- Year 3: System integration, multi-center validation, technology transferTimeline from left to right, each phase represented by different colored rounded rectangles.Blue-purple gradient color scheme, modern tech style.
Research Topic: Key Technologies for AI-based Early Tumor Diagnosis
Prompt:
NSFC General Project Technical Roadmap, 16:9 landscape format.Research Topic: Key Technologies for AI-based Early Tumor DiagnosisFour-Year Research Plan:- Year 1 (Data & Foundation): Multi-center data collection, annotation standards, benchmark dataset construction- Year 2 (Algorithm Development): Deep learning model design, feature extraction optimization, preliminary validation- Year 3 (System Integration): Diagnosis system development, clinical testing, performance evaluation- Year 4 (Promotion & Application): Multi-center validation, technology transfer, outcome disseminationMark key milestones with diamonds, distinguish each year with different colors.Medical technology style, blue-green color scheme, professional and rigorous.
Research Topic: Pathways to Enhance SME Innovation Capability in the Digital Economy
Prompt:
NSSFC Research Framework Diagram, 4:3 aspect ratio.Research Topic: Pathways to Enhance SME Innovation Capability in the Digital EconomyFramework Structure:- Core Question: How does digital transformation promote SME innovation?- Theoretical Foundation: Innovation ecosystem theory, Dynamic capabilities theory, Resource-based view- Research Dimensions: Digital infrastructure, Innovation resource acquisition, Organizational learning, External network embeddedness- Research Methods: Survey (500 enterprises), Case studies (10 typical enterprises), Econometric analysis- Expected Outcomes: Theoretical model, Policy recommendations, Practical guidelinesRadial layout from center, interactive arrows between dimensions.Business blue as main color, accented with warm orange.
The quality of diagrams in research grant applications directly impacts reviewer impressions. With SciDraw AI's AI scientific illustration feature, you can:
✅ Generate in minutes: Say goodbye to hours of manual drawing
✅ Professional quality: AI understands research contexts and generates academic-style diagrams
✅ Free editing: SVG vector format allows fine-tuning in any design software
✅ Consistent style: Multiple diagrams for the same project maintain unified visual style
Whether it's technical roadmaps for NSFC, research frameworks for NSSFC, or curriculum system diagrams for MOE projects, SciDraw AI helps you quickly generate professional, beautiful scientific illustrations.
Simply input your research content description, and AI instantly generates professional scientific diagrams. Supports technical roadmaps, research frameworks, mechanism diagrams, flowcharts, and more to help your research grant application succeed!
Davie Chen is a researcher at the Faculty of Animation and Intermedia, University of Arts in Poznan, studying generative AI for scientific figure creation, patent illustration, and manuscript drafting. SciDraw AI is one of the research-to-product tools built from this work.
