How might we help researchers efficiently find, contribute, and preserve Cyclic Voltammetry (CV) experimental data?
Project Overview
Client: Lin Lab @ Cornell U
0 – 1 Web Application
Duration: 6 months
Team of 2 PrD, 1 Dev
Project Overview
Client: Lin Lab @ Cornell University
0 – 1 Web Application
Duration: 6 months
Team of 2 PrD, 1 Dev
My Role
UI, UX Design
Prototyping
User Research
User Testing


Context
CV is a fundamental technique in electrochemistry. We apply voltage and measure current to understand how compounds behave in reactions. This data is essential for academic & pharmaceutical research. However, there’s currently no way to search or share CV data.
Our client at Cornell University approached us to help design and build an MVP for a centralized CV database.
CV Experiment Process
User Research
To better understand our users’ relationship with CV data, we conducted user research focusing on these objectives:
01
Understand users’ current workflow
02
Uncover pain points and frustrations when it comes to CV data
03
Understand users’ expectations around CV database
Profiles
3 Men, 1 Woman
Ages 25 - 48
Academic researchers
Parameters
Qualitative
Stakeholder interviews
60 min via Google Meet
Problem Statement
How might we help researchers efficiently find, contribute, and preserve CV experimental data?
Benchmarking
We benchmarked existing academic databases to understand what works & what doesn’t
Priority Guide
Using priority guides, we worked with our stakeholders to quickly validate what content mattered most before jumping into wireframes.


Wireframing
We put into wireframes key elements and interactions:
1. Three ways to search: Keyword, Structure, and Redox Property
2. Search results and filters
3. Search result detail
1. Upload file
2. Experiment parameters
3. Attribution
4. Submission
User Testing
We tested our wireframes with users to achieve the following objectives:
🔍 Search
Validate that users can efficiently find CV data using multiple search methods
📊 Results
Validate that search results are clear, and users can compare multiple CV plots easily
📤 Data Upload
Validate that the upload process is comprehensive & easy to complete
📈 Data Visualization
Validate that CV plots are easy to interpret
Profiles
3 Men, 2 Women
Ages 25 - 55
Academic researchers
Familiar w/ CV experiments
Parameters
Qualitative
Self-paced via remote recording
Tasks-based testing w/ think-aloud protocol
Design System
As we fine-tuned the UX, we also built the design system of the app, laying the groundwork for future components and product scaling.


Final Design (Under Development)
