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.
ScientificLoop · AI research intelligence · AI for Science
ScientificLoop
An AI for Science research intelligence workspace by Lu Zhang.
Tracking AI agents, scientific workflow automation, selected AI labs, and AI for Science startups — then turning the signals into cited notes, product ideas, and small agent prototypes.
Daily AI research radar Scientific agent workflows Cited sources when available Public-safe corpus
Daily AI Research Radar
A source-based working workflow for tracking selected AI labs, AI for Science startups, research preprints, and scientific-agent workflow signals.
Agent interfaceScientific Workflow Agent
A public-safe site agent that retrieves evidence, routes visitors to the right source, and exposes next actions instead of acting like a static portfolio search box.
Build trackAI for Science Lab
Small prototypes around RAG, evaluation, traceable decision support, redox-flow formulation, and scientific workflow automation.
AI & engineering
All projects → 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 — Azure-deployed RAG assistant for new-energy content
Deployed bilingual RAG assistant built on 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
AI scientist for redox flow battery formulation
A pre-v0.1 vertical-domain AI agent prototype designed to support redox-flow-battery electrolyte formulation. It aims to translate 14+ years of flow-battery chemistry intuition into structured reasoning, retrieval, and validation workflows.
In progress · pre-v0.1
AI research radar
All notes →A Public-Safe Site Agent as a Portfolio Interface
Why a personal technical site can be more useful when the homepage becomes a small, cited, public-safe agent.
Scientific RAG Needs Evaluation Before Confidence
RAG systems for technical work should be judged by retrieval quality, citation faithfulness, and decision usefulness, not only fluent answers.
Featured research
All publications → 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.
Recent
latest firstCo-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 vertical AI prototype for redox-flow-battery formulation support. The goal is to connect 14+ years of flow-battery intuition with structured retrieval, reasoning, and validation workflows.
Working on enterprise AI agent, RAG, and workflow tooling for the American Academy of Orthopaedic Surgeons.
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.