PaperQA2 is a useful reminder for scientific RAG: leave an evidence trail
A SciencesLoop technical note on PaperQA2, citation precision, and reviewable scientific RAG artifacts.
Daily AI research radar Scientific agent workflows 可用时返回引用来源 公开安全语料
Daily AI Research Radar
基于公开来源跟踪选定 AI 实验室、AI for Science 创业公司、科研预印本和 scientific-agent workflow 信号。
智能体界面Scientific Workflow Agent
公开安全的站内 agent：检索证据、路由到相关来源，并给出下一步动作，而不是只做静态个人介绍。
构建路线AI for Science Lab
围绕 RAG、evaluation、可追踪决策支持、液流电池 formulation 和科研工作流自动化的小型原型。
AI 与工程
查看全部项目 → lu-zhang-site
lu-zhang-site
This site — academic homepage with structured data layer
Astro static site driven by curated JSON data extracted from a master research record. 99 publications (97 SCI + 2 book chapters), 28 patents (25 issued + 3 applications), 51 conference presentations (38 abstracts + 13 invited talks).
Live
meditation-study
meditation-study
Personal meditation learning platform
Web app for studying a meditation teacher-training course. Built around session JSON, polished script generation, and TTS audio playback. Daily-use product.
Live
guangnian-energy-agent
guangnian-energy-agent
光年新能源智能体 — RAG assistant demo for new-energy content
Bilingual RAG assistant demo/prototype built around Azure OpenAI and Azure AI Search patterns, with a Python aiohttp backend and lightweight web UI. Used as a practical AI x energy demo and workflow prototype.
Live demo
rfb-formulation-agent
rfb-formulation-agent
Redox-flow-battery formulation support prototype
A pre-v0.1 vertical-domain AI agent prototype for redox-flow-battery formulation support. It tests whether structured retrieval, reasoning, and validation workflows can help organize flow-battery formulation knowledge.
In progress · pre-v0.1
AI 研究雷达
全部笔记 →ChemGraph is a better first test for scientific agents
A SciencesLoop note on ChemGraph, computational chemistry agents, and why traceable workflows matter more than fluent chat.
Agentic Scientific Workflows: From Search to Traceable Decisions
A working model for scientific agents that retrieve evidence, plan the next step, preserve uncertainty, and leave a decision trail.
代表性论文
查看全部论文 → J. Mater. Chem. A — under revision
2026
2026
From machine learning to chemical insight: Darwinian chance and the stability of charge carriers in flow batteries
ML-driven insight into the stability of charge carriers in flow batteries. Submitted to JMCA (TA-ART-01-2026-000771); a direct extension of the JCESR DMB redoxmer line. With Robertson, Shkrob, Assary, J. Zhang.
ACS Applied Energy Materials
2025
2025
Automation-Accelerated Electrolyte Design Mitigates Solubility Competition between Redox-Active Molecules and Supporting Salts
2025 follow-up to the Nature Comm robotic platform — automated HTE + ML for paired BTZ/LiTFSI solubility (~3 M, surpassing the 2 M ceiling). With Robertson, Doan, Han.
Journal of Materials Chemistry A
2025
2025
A comparative computational and SECM study of factors influencing electron transfer at hydrogenated and pristine graphite-propylene carbonate interface
2025 SECM + computational study showing H-functionalization on graphitic electrodes increases electron-transfer kinetics. With Curtiss, Assary, Counihan, Rodríguez-López, J. Zhang.
An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations
Robotic platform + ML for electrolyte discovery — bridging chemistry and AI.
Angewandte Chemie
2015
2015
Radical Compatibility with Nonaqueous Electrolytes and Its Impact on an All-Organic Redox Flow Battery
Most-cited paper. Foundational radical-cation work for non-aqueous flow batteries.
Energy & Environmental Science
2012
2012
Molecular engineering towards safer lithium-ion batteries: a highly stable and compatible redox shuttle for overcharge protection
First-author EES paper on overcharge-protection redox shuttles — basis for R&D 100 Award (2014).
Scientific Reports
2016
2016
The lightest organic radical cation for charge storage in redox flow batteries
Systematic molecular trimming to find the smallest stable radical-cation core. Featured in Argonne Today.
近期动态
倒序Co-authored manuscript (lead: Lily Robertson; co-authors: Ilya Shkrob, Rajeev Assary, Jingjing Zhang) under revision at Journal of Materials Chemistry A (TA-ART-01-2026-000771). Bridges ML-driven insight to charge-carrier stability in non-aqueous flow batteries — direct extension of the JCESR DMB redoxmer line.
ML-guided HTE for paired BTZ/LiTFSI solubility — m-xylene/acetonitrile mixture dissolves ~3 M of both, surpassing the 2 M ceiling for neat acetonitrile. With Lily Robertson, Hieu Doan, Kee Sung Han.
H-functionalization on graphitic electrodes increases electron-transfer kinetics in non-aqueous redox media. With Curtiss, Assary, Counihan, Rodríguez-López, J. Zhang.
A pre-v0.1 AI prototype testing whether structured retrieval, reasoning, and validation workflows can help organize redox-flow-battery formulation knowledge.
Working on high-level enterprise data/AI workflow tooling at AAOS; public details intentionally limited.
Nature Communications — high-throughput robotic platform + active learning for electrolyte discovery
Co-authored work demonstrating an integrated robotic platform with active learning for accelerated discovery of optimal electrolyte formulations. The convergence of automation, ML, and battery chemistry.
Filed patent on selective ionic-species recovery membranes. Application of redox-flow membrane chemistry to lithium recovery.
After 14+ years at Argonne National Laboratory, started a new chapter in industrial data science, applied ML, and AI engineering.