Author Profile

Comparative discharge characterization of button-cell batteries in an introductory physics CURE

Patrick B. Greene, St. Marys University, San Antonio, TX
Sigrid Greene, Northwest Vista College, Alamo Colleges District, San Antonio, TX
Location: Texas

Abstract

This Course-based Undergraduate Research Experience (CURE) engages students in an algebra-based introductory physics laboratory in a year-long investigation of the discharge behavior of commercial button-cell batteries. Working in teams, students construct simple DC circuits, collect time-resolved voltage and current data under controlled resistive loads, and analyze discharge curves to characterize battery performance, variability, and uncertainty across brands and experimental conditions.

The project is designed for students with no prior electronics experience. Instruction in circuit construction, Ohm's law, computer-based data acquisition, and uncertainty analysis is embedded directly into laboratory time. A shared baseline protocol enables replication across multiple lab sections, while later extensions allow students to explore variations in load resistance, cutoff criteria, and performance metrics such as delivered energy and charge capacity.

Iteration and protocol refinement are central features of the CURE, including explicit treatment of outliers, data rejection, and method revision informed by background research. Data are aggregated across semesters, enabling longitudinal analysis and reinforcing the cumulative nature of scientific research. The CURE scales across multiple sections and is well suited for life science and pre-health majors.

 

Student Goals

  1. Apply fundamental DC electronics concepts—voltage, current, resistance, power, and energy—in a research context.
  2. Develop skills in computer-based data acquisition, replication, and experimental refinement through iterative measurement.
  3. Analyze and compare datasets using graphical methods, uncertainty estimation, and statistical tools such as t-tests and ANOVA.

Research Goals

  1. To characterize the discharge behavior of button-cell batteries under controlled and replicated electrical loads, comparing performance and variability across individual batteries and brands.
  2. To aggregate and analyze student-generated datasets across lab sections and semesters to produce graphical, tabular, and statistical summaries of discharge behavior and uncertainty.

 

Context

 

St. Mary's University is a private, Catholic liberal arts institution in San Antonio, Texas, serving approximately 3,000 undergraduates and designated as a Hispanic-Serving Institution. The CURE is embedded in a two-semester, algebra-based General Physics laboratory sequence primarily serving junior-level life science and pre-health majors and functions as a required core laboratory experience.

Each laboratory section enrolls 12–20 students and meets for three hours weekly. Students work in teams of 3–5. Typically, three lab sections are offered in the fall and two in the spring. The CURE spans both semesters, with approximately twelve weeks per semester devoted to research-centered activities including data collection, analysis, replication, and presentation.

Students are not expected to have prior experience with electronics or instrumentation. All required skills—including circuit construction, data collection, uncertainty estimation, and data management—are taught during scheduled lab time. Students typically have prior exposure to introductory statistics (including t-tests and ANOVA), which are applied in the analysis of student-generated datasets.

Target Audience:Non-major
CURE Duration:Multiple terms

 

CURE Design

 

The research theme centers on the discharge behavior of commercial button-cell batteries under controlled electrical loads. Students conduct an observational study of how battery voltage and current evolve over time and how derived quantities—such as discharge time, delivered energy, charge capacity, and variability—depend on battery brand, load resistance, and analysis criteria.

The CURE proceeds in structured phases that mirror experimental research practice. Early activities focus on circuit construction, safe battery handling, and data acquisition using a shared apparatus configuration. Students then implement a common baseline discharge protocol, enabling replication across teams and lab sections and facilitating identification of typical sources of error and variability.

As the project progresses, students extend the baseline study by varying experimental parameters, comparing brands, and refining analysis choices such as cutoff voltage definitions and performance metrics. These refinements are driven by observed data behavior and background research. Data are aggregated within and across semesters, allowing students to distinguish systematic trends from natural variability.

Equity and inclusion are supported by teaching all technical and analytical skills during lab time, rotating team roles, and embedding troubleshooting and analysis within scheduled sessions.

Stakeholders include consumers interested in battery performance, physics instructors seeking scalable introductory research experiences, educational researchers studying CURE models, and campus communities interested in sustainability and consumer technology.

Student work is shared through end-of-semester poster or presentation sessions and through a shared course data archive supporting reuse by future cohorts.

Core Competencies:Analyzing and interpreting data
Nature of Research:Applied Research

 

Tasks that Align Student and Research Goals

Research Goals →
Student Goals ↓
Research Goal 1: To characterize the discharge behavior of button-cell batteries under controlled and replicated electrical loads, comparing performance and variability across individual batteries and brands.
Research Goal 2: To aggregate and analyze student-generated datasets across lab sections and semesters to produce graphical, tabular, and statistical summaries of discharge behavior and uncertainty.

Student Goal 1: Apply fundamental DC electronics concepts—voltage, current, resistance, power, and energy—in a research context.

Construct a battery discharge circuit and verify connections using a multimeter.
Use Ohm's law to predict discharge current for a given load.
Define and apply a consistent cutoff voltage for "end of discharge."

Interpret discharge curves using concepts of voltage, current, power, and energy.


Student Goal 2: Develop skills in computer-based data acquisition, replication, and experimental refinement through iterative measurement.

Collect multiple discharge trials per battery brand using a shared protocol.
Troubleshoot circuit and data acquisition issues and repeat measurements.
Document protocol changes and outcomes in a lab notebook.

Upload cleaned datasets with required metadata to a shared repository.
Replicate another team's analysis and reconcile discrepancies.


Student Goal 3: Analyze and compare datasets using graphical methods, uncertainty estimation, and statistical tools such as t-tests and ANOVA.

Produce discharge curves with uncertainty estimates.
Calculate summary metrics such as discharge time and delivered energy.
Perform statistical comparisons between batteries or brands.

Create cross-team summary figures and tables.
Write a results narrative discussing uncertainty, variability, and limitations.
Present findings in a poster or slide presentation.


 

Instructional Materials

 

Required materials include button-cell batteries from multiple brands, compatible battery holders, resistors providing a range of electrical loads, alligator-clip leads, digital multimeters, and Vernier computer-based voltage and current probes. Students use data-logging software for time-resolved data collection and spreadsheet software for analysis and visualization.

Instructional materials include a week-by-week laboratory schedule, a shared baseline discharge protocol, data templates with required metadata fields, analysis worksheets, and safety guidelines. Written setup and analysis resources are revisited throughout the semester. All data analysis is conducted during scheduled laboratory time to support equitable participation and immediate feedback.

As the CURE lasted 6 semesters, worksheets and instructions evolved over time.

Definitions of Physical Quantities Worksheet and Solutions (Zip Archive 36kB Jan11 26)
Worksheets and Example Data File for Data Analysis (Zip Archive 47kB Jan12 26)

Assessment

 

Reflective Video Journal Resources (Zip Archive 33kB Jan11 26)

 

Instructional Staffing

 

The CURE is implemented by the course instructor, with support from a laboratory teaching assistant when available. The instructor provides instruction in electronics, data acquisition, analysis, and research design, while the teaching assistant assists with troubleshooting and in-lab feedback. The project is designed to be sustainable with minimal staffing and does not require specialized technical support or external collaborators.

Author Experience

Patrick Greene, St. Marys University, San Antonio, TX

This CURE was developed to provide students in an introductory, algebra-based physics laboratory with an authentic research experience that goes beyond traditional verification experiments. The project leverages a conceptually accessible system—battery discharge in simple DC circuits—while intentionally building on the background knowledge of junior-level students, including prior exposure to statistics and the scientific method. By engaging students in extended data collection, replication, uncertainty analysis, and evidence-based method refinement across multiple weeks and semesters, the CURE demonstrates that meaningful, cumulative physics research can be implemented at scale for life science and pre-health majors with diverse academic backgrounds.


 

Advice for Implementation

 

Common challenges include circuit construction errors, inconsistent protocol application, and spreadsheet mistakes. These are mitigated through standardized protocols with required metadata, in-lab analysis, and peer and instructor review of calculations. Instructors are advised to begin with a moderate discharge current so that complete datasets can be collected within a single lab session. As students gain confidence, longer-duration measurements and refined analyses can be introduced. Explicitly framing early errors as expected supports engagement and reinforces the iterative nature of research.

 

Iteration

 

Iteration is an explicit component of the CURE. Students troubleshoot during data collection, repeat failed or inconsistent measurements, and refine protocols in response to observed results. Time is built into the schedule for repeating experiments and revising methods. At the methodological level, students revisit analysis choices—such as cutoff voltage definitions and integration intervals—by comparing replicated datasets across teams and semesters. Unexpected results are treated as drivers of scientific learning rather than as failures.

 

Using CURE Data

 

Student-generated data are aggregated into a shared dataset organized by semester, battery brand, and experimental condition. Data quality is ensured through standardized protocols, required metadata, acceptance checks, and cross-team verification. Measurements failing to meet criteria are documented and replaced through replication. Aggregated datasets are reused by subsequent cohorts, supporting longitudinal analysis and reinforcing reproducibility, transparency, and evidence-based revision of methods.

 

Resources

 

Faculty-facing resources include literature on CURE pedagogy and introductory electronics, as well as documentation for voltage probes and data-logging software. Student-facing resources include short readings on battery discharge behavior, measurement techniques, and uncertainty analysis.




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