Catalysis literature search skill. Given a user-provided catalyst topic, reaction type, or material system, retrieve and organize relevant catalysis research papers from the open web (ScienceDirect, arXiv, OpenAlex, Google Scholar, etc.) and output structured literature-review information (literatur
设计与多媒体
Catalyst Design
试用Catalyst design guidance skill. Based on a layered, traceable, and dynamically evolving methodology system (fusing catalyst-search retrieval results, user-acquired materials via AI/skills, and external channels), it provides advice on catalyst composition selection, structural design, synthesis stra
它能做什么
Catalyst design guidance skill. Based on a layered, traceable, and dynamically evolving methodology system (fusing catalyst-search retrieval results, user-acquired materials via AI/skills, and external channels), it provides advice on catalyst composition selection, structural design, synthesis strategy, and performance optimization. Runs standalone; also collaborates with catalyst-search — consuming its structured literature output (matrix) for sharper targeting and feeding new evidence back into the methodology base.
技能文档
Catalyst Design
When to use
- Users asking how to design a catalyst, which composition to pick, how to optimize performance, synthesis-route advice, catalyst formulation, electrocatalyst design, or how to choose synthesis conditions.
- Typical input: design goal (reaction type + material system / performance need). Optional: catalyst-search literature results.
- Covers HER, OER, ORR, PEMWE, overall water splitting, photocatalysis, and plastic upcycling, among other systems.
When NOT to use
- Pure literature search — use
catalyst-search; this skill does not re-search. - Non-catalysis material design (e.g., battery cathodes, semiconductor devices) — not applicable.
- Looking up a specific DOI or full text — use WebSearch / WebFetch directly.
Prerequisites
- Ships with its own knowledge base (
references/) and templates (templates/); runs with no external dependencies. - Optional: when WebSearch / WebFetch are available, the skill may trace a specific rule's origin (not required).
Input interface
- Required: design goal — reaction type plus material system or performance need.
- Optional: the structured literature output of
catalyst-search(theliterature_matrix.mdtable, supporting conclusions, and validation suggestions).- With literature — give targeted advice using its specific systems and metrics, and cite the support.
- Without literature — give general advice from the built-in methodology (see
references/design_methodology.md).
Methodology system (layered, multi-source, traceable, evolvable)
The methodology continuously fuses multi-source evidence, organized in four layers, and evolves dynamically with new literature.
- Full layered knowledge base:
references/design_methodology.md(each entry carries a source tag, confidence, and update date). - Dynamic update mechanism:
references/methodology_update_protocol.md. - Traceability registry:
references/methodology_registry.md(trace by ID to source / DOI).
Four-layer framework
- L1 — Theory: structure–property relations, d-band center, Sabatier principle, mechanism typing (AEM / LOM; Volmer–Heyrovsky), activity–stability trade-off, defects as activity, bifunctional synergy.
- L2 — Methods and tools: synthesis library (SEA, low-melting doping, ligand anchoring, single-source pyrolysis, Joule heating, templating, grain-boundary engineering), characterization and computation (XRD, STEM, XPS, EXAFS, DFT, ML), structural design (size, ordering, core–shell, support, single- and dual-atom sites).
- L3 — Parameters: annealing temperature (450–1150 °C), cooling rate (slow cooling ≤ 2 °C/min), atmosphere, particle size, doping level, composition ratio, post-treatment.
- L4 — Validation: RDE → MEA tiered evaluation, applicable standards (TCASMES 400-2024, T/CRES 0030-2025), per-system benchmarks, ordering / stability / scale-up validation.
Source tags (traceability)
[CS] catalyst-search retrieval (with DOI) · [AI] user-acquired via AI / skill · [EXT] external channel (conference, patent, standard, internal data) · [EXP] empirical guess (to verify). Confidence: ★–★★★.
When generating advice, surface the source tag of each cited entry and distinguish "literature-confirmed" from "empirical guess".
Workflow
- Parse input. Extract the design goal and collect multi-source evidence — catalyst-search matrix
[CS], user-provided[AI], external[EXT]. If the input is incomplete (missing reaction type or material system), ask the user to clarify first; do not guess. - Match rules by layer. Map the goal to L1 theory (mechanism direction) → L2 methods (synthesis / characterization) → L3 parameters (windows) → L4 validation (evaluation path).
- Generate advice. Output composition, structure, synthesis, conditions, and validation. Each citation must note its source tag (and DOI) and confidence, and distinguish confirmed from guessed.
- Dynamic backfill (evolve, opt-in). Only when the user explicitly asks to update the knowledge base (e.g., "update your methodology" / "remember this"): validate new rules per
methodology_update_protocol.mdand backfill the skill's ownreferences/design_methodology.mdandreferences/methodology_registry.md(source, DOI, confidence, status). Otherwise keep the built-in methodology read-only and do not modify any skill files. For under-evidenced (only[EXP]) directions, proactively suggest a catalyst-search re-check to upgrade to[CS]. - Output. Write the design proposal per
templates/design_proposal.mdand cite in GB/T 7714 (see catalyst-search'stemplates/citation_gb7714.mdor this skill's own copy).
Output interface
- Design proposal covering composition, structure, synthesis, conditions, and validation; format per
templates/design_proposal.md. - When citing literature, give a GB/T 7714 citation and label each item "literature-supported" or "empirical guess".
Division of labor
- Literature search is
catalyst-search's job; this skill does not re-search, only consumes that output or uses its built-in knowledge. - To trace a specific rule's origin, WebSearch / WebFetch may be used (optional).
Notes
- Advice must be grounded in the built-in methodology or supplied literature; no ungrounded claims.
- Clearly distinguish "literature-confirmed" from "empirical guess".
- Advice must include an actionable validation path (characterization, testing) for user verification.
- Safety and permissions: by default this skill only reads its own
references/andtemplates/; it runs no system commands and makes no network requests beyond optional WebSearch / WebFetch; it collects or exfiltrates no user data. Optional self-update: step 4 ("Dynamic backfill") can write to the skill's ownreferences/design_methodology.mdandreferences/methodology_registry.md— but only when you explicitly enable it (e.g., "update your methodology"). It never writes to your own files or project directories.
Example
- Input: design an acidic OER catalyst with η₁₀ < 200 mV and stability > 500 h.
- Output:
- Composition: Ru@IrOₓ core–shell (high-activity Ru core, dissolution-resistant IrOₓ shell).
[CS]★★★ - Structure: core–shell interfacial charge redistribution, optimizing oxygen-intermediate adsorption on Ru.
[CS]★★★ - Synthesis: Adams fusion for the IrOₓ shell, followed by reductive Ru deposition.
[CS]★★ - Conditions: anneal at 400–500 °C (too high drives Ru into the shell, too low gives insufficient ordering).
[EXP]★ - Validation: RDE for η₁₀ and Tafel slope; ICP-MS for Ru / Ir dissolution monitoring; 30 000-cycle ADT.
[CS]★★★
- Composition: Ru@IrOₓ core–shell (high-activity Ru core, dissolution-resistant IrOₓ shell).
Project home
- GitHub: https://github.com/ANDYPENG09/catalyst-design-skill — source, updates, and issue tracker.
- Companion skill: https://github.com/ANDYPENG09/catalyst-search-skill — catalysis literature search.
催化剂设计指导
何时使用
- 用户咨询:催化剂怎么设计、选什么组分、怎么优化性能、合成路线建议、催化剂配方、电催化剂设计、合成条件怎么选等。
- 典型输入:设计目标(反应类型 + 材料体系 / 性能诉求)。可选:catalyst-search 的文献检索结果。
- 覆盖反应:HER、OER、ORR、PEMWE、全解水、光催化、塑料升级回收等。
何时不使用
- 纯文献检索任务 —— 用
catalyst-search,本技能不重复检索。 - 非催化领域的材料设计(如电池正极、半导体器件)—— 不适用。
- 仅需查一个具体 DOI 或论文全文 —— 直接用 WebSearch / WebFetch。
前置条件
- 本技能自带知识库(
references/)与模板(templates/),无需外部依赖即可运行。 - 可选:当 WebSearch / WebFetch 可用时,可补查特定规律的出处(非必需)。
输入接口
- 必填:设计目标,含反应类型 + 材料体系或性能诉求。
- 可选:
catalyst-search的结构化文献输出,即literature_matrix.md格式的文献矩阵表 + 支撑结论 + 验证建议。- 提供了文献 —— 结合文献中的具体体系与指标,给出针对性建议并标注文献支撑。
- 未提供文献 —— 基于内置设计方法论(见
references/design_methodology.md)给出通用建议。
设计方法论体系(分层、多来源、可追溯、可演进)
方法论持续融合多来源证据,按四层体系组织,并可随新增文献动态更新。
- 完整分层知识库:
references/design_methodology.md(每条带来源标签 + 置信度 + 更新日期)。 - 动态更新机制:
references/methodology_update_protocol.md。 - 可追溯条目台账:
references/methodology_registry.md(编号 → 出处 / DOI 逐级溯源)。
四层体系
- L1 基础理论层:构效关系、d 带中心、Sabatier 原理、反应机理分型(AEM / LOM;Volmer–Heyrovsky)、活性–稳定性权衡、缺陷即活性、双功能协同。
- L2 方法工具层:合成方法库(SEA、低熔点掺杂、配体锚定、单源热解、Joule heating、模板、晶界工程等);表征与计算工具(XRD、STEM、XPS、EXAFS、DFT、ML);结构设计手段(尺寸、有序化、核壳、载体、单/双原子)。
- L3 技术参数层:退火温度(450–1150 °C)、降温速率(慢冷 ≤ 2 °C/min)、气氛、粒径、掺杂量、组分配比、后处理。
- L4 实践验证层:RDE → MEA 分级评测、相关标准(TCASMES 400-2024、T/CRES 0030-2025)、各体系性能基准、有序度 / 稳定性 / 放大验证。
来源标签(可追溯性)
[CS] catalyst-search 检索文献(含 DOI) · [AI] 用户经 AI / skill 获取 · [EXT] 外部渠道(会议、专利、标准、内部数据) · [EXP] 经验推测(待验证)。置信度:★–★★★。
生成建议时须带出所引条目的来源标签,区分"文献已证实"与"经验推测"。
工作流
- 解析输入。提取设计目标(反应类型 / 体系 / 性能),并收集多来源证据——catalyst-search 文献矩阵
[CS]、用户经 AI / skill 提供的资料[AI]、外部渠道[EXT]。输入不完整(缺反应类型或材料体系)时,先向用户澄清,不臆测。 - 按四层匹配规律。目标映射到 L1 理论(选机理方向)→ L2 方法工具(选合成 / 表征手段)→ L3 参数(定参数窗口)→ L4 验证(定评测路径)。
- 生成建议。输出组分选择 + 结构设计 + 合成策略 + 条件优化 + 验证建议。每条引用注明来源标签(及 DOI)与置信度,区分"文献已证实"与"经验推测"。
- 动态回填(演进,需显式启用)。仅当用户明确要求更新知识库时(例如"更新你的方法论 / 记住这条"),才按
references/methodology_update_protocol.md校验后回填本技能自身的references/design_methodology.md与references/methodology_registry.md(含来源、DOI、置信、状态)。否则保持内置方法论只读,不修改任何技能文件。证据不足(仅[EXP])的方向,主动建议调用 catalyst-search 补检以升级为[CS]。 - 输出。按
templates/design_proposal.md输出设计建议书,引用采用 GB/T 7714(格式见 catalyst-search 的templates/citation_gb7714.md,本技能自带同名模板亦可)。
输出接口
- 设计建议书(组分 / 结构 / 合成 / 条件 / 验证),格式见
templates/design_proposal.md。 - 若引用文献,给出 GB/T 7714 引用,并标明"文献支撑"或"经验推测"。
与其他能力分工
- 文献检索由
catalyst-search负责;本技能不重复检索,仅消费其输出或基于内置知识给建议。 - 如需补查特定设计规律的出处,可用 WebSearch / WebFetch(可选,非必需)。
注意事项
- 建议须有据(内置方法论或所提供文献),不凭空断言。
- 明确区分"文献已证实"与"经验推测"。
- 设计建议须附带可执行的验证路径(表征 / 测试),便于用户复核。
- 安全与权限:默认情况下本技能仅读取自带
references/、templates/;不执行系统命令,除可选的 WebSearch / WebFetch 外不发起网络请求,不收集或外传用户数据。可选的自更新:工作流第 4 步"动态回填"可写入本技能自身的references/design_methodology.md与references/methodology_registry.md以演进知识库——但仅在您显式启用时(例如"更新你的方法论")才会发生,且绝不会写入您自己的文件或项目目录。
示例
- 输入:设计一个酸性 OER 催化剂,要求 η₁₀ < 200 mV、稳定 > 500 h。
- 输出:
- 组分:Ru@IrOₓ 核壳(Ru 核活性高、IrOₓ 壳抗溶)。
[CS]★★★ - 结构:核壳界面电荷重分布,优化 Ru 的含氧中间体吸附。
[CS]★★★ - 合成:Adams Fusion 制 IrOₓ 壳 + 还原沉积 Ru 核。
[CS]★★ - 条件:退火 400–500 °C(过高致 Ru 溶入壳,过低有序度不足)。
[EXP]★ - 验证:RDE 测 η₁₀ / Tafel;ICP-MS 监测 Ru / Ir 溶解;30k 圈 ADT。
[CS]★★★
- 组分:Ru@IrOₓ 核壳(Ru 核活性高、IrOₓ 壳抗溶)。
项目主页
- GitHub:https://github.com/ANDYPENG09/catalyst-design-skill —— 源码、更新与 Issue 反馈。
- 配套技能:https://github.com/ANDYPENG09/catalyst-search-skill —— 催化文献检索。
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