As a high school student, participating in a science fair can be an enriching experience as it allows you to learn about new concepts in scientific projects, experiments, or reports and present your project to a panel of experts.  

Preparing for a science fair involves working on a project from scratch, polishing skills like online research, basic data analysis, critical thinking, and more. Working on projects or experiments lets you gain experience with problem identification, literature surveys, experiment design, and documentation. If the fair invites reports, you will also be able to demonstrate and improve on soft skills like public speaking and presentation. 

Participating in a high school science fair will be a huge boost to your profile during college applications. Admission officers tend to look out for profiles that demonstrate hands-on experience either in the form of a science project or summer research. 

If you are considering participating in a science fair this year, then check out the 12 high school science projects listed in this blog! 

1. Exploring the relationship between music and plant growth

Did you know, according to research, music can also boost plant growth? 

This is a beginner-friendly project that involves discovering the impact of music on plant growth. You can find out the outcome of music and its impact by conducting an experiment on multiple saplings (up to 5) of the same plant. You will need to store these plants under similar conditions, that is with similar humidity and sunlight exposure, and place them under a heat lamp. However, since you will be looking at the impact of music on plant growth, you will also need a control sample, which will have no exposure to sound. 

You can decide on a fixed regimen and expose the plants to different musical genres for around two hours a day. The most common genres used in this project are classical, metal, jazz, and pop. Ideally, all your observations will need to be made during the first month of plant growth with music.

Field: Biology

Skill Level: Beginner

Prior Knowledge Required: Experience in basic gardening techniques. 

2. Testing the efficacy of biodegradable hydrogels in farming

Farming is highly water-intensive; as per the World Bank, roughly 70% of all of the world’s freshwater supply is used up in agriculture. While traditional irrigation methods are a good option for regions near a river or a lake, in regions where water is scarce, the use of hydrogels – materials that can absorb water up to 145 times their weight – has been proposed. However, while synthetic hydrogels exist, they can be harmful to the soil, so this study proposed biodegradable hydrogels.

In this project, you can test the efficiency of biodegradable hydrogels in farming by exploring three different types of hydrogel: agar-based, hydroxyethyl cellulose (HEC), and a combination of agar and HEC. The experiment should help you understand how well each hydrogel retains water when added to the soil and how much water is lost to the atmosphere. 

Field: Chemistry

Skill Level: Beginner

Prior Knowledge Required: Experience in basic gardening techniques. 

3. Build a robotic arm

Robotic arms have become a crucial tool in the modern medical field, especially during intricate surgeries. While researching their future applications can be a project on its own, you can also attempt to build robotic arms yourself!

This project will require a few simple steps; however, you should know coding to build a functional robotic arm. The first step would be to finalize the robot arm’s size and movement range. Once you have arranged all materials, you can begin by assembling a sturdy frame. This will require some trial and error and will be the most time-consuming part. 

This project will involve connecting wires, writing code, and testing your robot arm! Refer to this article for a detailed step-by-step guide.

Field: Robotic engineering

Skill Level: Advanced

Prior Knowledge Required: Coding experience and previous experience with Arduino is necessary. 

4. Plant disease prediction

With this project, you will create a plant disease detection model through a dataset that consists of images of leaves of different plant species. The model will compare these images with diseased plant leaf images from the dataset to determine the plants that have diseases. 

You will be using the dataset for this project from Kaggle, which has over 87k images of three plant species, namely potato, corn, and tomato. The AI model that you’ll build will make use of the convolutional neural network (CNN), a type of deep learning algorithm useful for making predictive analysis. 

Field: Machine Learning

Skill Level: Beginner

Prior Knowledge Required: Coding, familiarity with machine learning terminologies, and experience with Python libraries. 

5. Explore the nanotechnology containing oil spills  

Oil spills pose significant threats to ocean ecosystems and marine life. Cleaning up these spills demands considerable time and resources, and some of the chemicals used in the cleanup process can create additional environmental concerns. An innovative method for containing oil spills in water is the use of ferrofluids, which are fluids containing magnetic nanoparticles.

A simple experiment can demonstrate how ferrofluids work. You can either purchase commercially available ferrofluids or create your own. For your science fair project, you can do a comparative study to determine the efficacy of different oil spill control techniques. 

Field: Chemical Engineering

Skill Level: Intermediate

Prior Knowledge Required: Basic chemical mixing and lab etiquette. 

6. Determination of vitamin C in various fruit juices

For this project, you'll need to prepare a sample solution that you can test for vitamin C. It can be done using packaged juice or by extracting juice from fresh fruits or vegetables. You'll also need iodine solution and starch indicator solution. The titration is performed with the endpoint indicated by a color change from orange to blue.

For more detailed instructions and a step-by-step guide on the titration process, you can refer to this document.

Field: Chemical Engineering  

Skill Level: Intermediate  

Prerequisites: A solid understanding of chemical concepts and some experience in titration are required, along with basic lab skills, especially when handling precise weight measurements.

7. Create Sustainable Bioplastics 

Bioplastics, as the name suggests, are plastic-like materials derived from plant materials. You can read more about them here.

As a science fair project, you can make your own bioplastics, mold them in various household items, and present them at the fair. To create a simple bioplastic base, you’ll need ingredients that can be easily found at home, like cornstarch or corn flour, vegetable oil or glycerin, a wooden spoon, white vinegar, a whisk, a bowl, water, food coloring, and a microwave oven. 

This project is a fun, hands-on method of learning more about the importance of preserving the environment and generating interest in environmentally safer alternatives to plastic. 

Field: Chemical Engineering  

Skill Level: Intermediate  

Prerequisites: Basic mixing and precautions when dealing with hot equipment. 

8. Optical Character Recognition (OCR) project

Optical Character Recognition (OCR) has been around since the 1950s, with IBM leading the early development of the technology, though it only became commercially available in the 1990s. Today, OCR refers to the process of converting images of typed, handwritten, or printed text into machine-readable text. This can be done from scanned documents, photos of documents, scene images, or even subtitles embedded in an image.

In this project, the goal is to use a pre-existing dataset to extract text from images using OCR technology. If done correctly, under guidance from an experienced computer science mentor, this can be a great science fair project, as it provides live character recognition demonstrations.

Field: Computer Science

Skill Level: Beginner                              

Prerequisites: Introductory Python programming, understanding of machine learning algorithms, and knowledge of TensorFlow and OpenCV.

9. Using data visualization in stroke risk prediction 

This project involves building a machine learning model to assess stroke risk based on patient factors like age, lifestyle, and medical history. This type of project will make use of data visualization techniques. Using the McKinsey & Company Electronic Health Records dataset from Kaggle, you'll identify key risk factors and preventive measures. The next step will be to conduct an Exploratory Data Analysis to clean the data and visualize findings.

Finally, you will develop a predictive model using algorithms such as random forests and decision trees on a balanced dataset of stroke and non-stroke cases. This project explores the intersection of healthcare and data science, showcasing its potential in medical applications.

Field: Computer Science

Skill Level: Intermediate

Prior Knowledge Required: Coding, familiarity with machine learning terminologies, and experience with Python libraries. 

10. Smart Plant Watering System

Smart watering systems have a wide range of applications, as they can help manage our home gardens, and on a large scale, they can help regulate irrigation for farms. One of the most basic smart watering systems makes use of Arduino UNO and batteries. This setup works well on a small scale and dispenses water depending on the moisture level in the soil. 

For this project, you will need an Arduino UNO, a moisture sensor, a 6V mini water pump with a small pipe, connecting wires, a 5V relay module, and a 5V battery. This is the requirement for a basic demonstration. 

For detailed instructions on coding Arduino and assembling the setup, refer to this document. To understand how a functional smart watering system can be controlled via an app, check out this explanation. 

Field: Computer Science

Skill Level: Intermediate

Prior Knowledge Required: Coding, experience with Arduino UNO, and understanding of basic circuits.

11. Mini Tesla Coil

Did you know that just by using simple materials, it is possible to make a mini Tesla coil? You can even demonstrate the principle of resonance by lighting up an LED or CFL bulb!

For this project, you will need enameled copper wire – usually found in old motors – a 22K resistor, 2N2222A transistor, LED, breadboard wire, a PVC pipe or cardboard roll (any cylindrical nonconductive object will work), a 9V battery, and a breadboard. 

You can check out this circuit diagram for reference. For detailed information on the basics of a mini Tesla coil, take a look at this article. 

Field: Physic, Electrical engineering

Skill Level: Intermediate

Prior Knowledge Required: Understanding of basic circuits and experience of working with batteries. 

12. Sign Language Recognition

Developing a sign language recognizer using machine learning is not only a fun project but is also one that has real-world significance. American Sign Language (ASL) is widely used in deaf communities across the U.S. This project focuses on building a model to identify which of the 24 ASL letters (excluding the gesture-based J and Z) are present in the provided images. 

You can execute this project using Python's OpenCV, Keras libraries, and this dataset from Kaggle. Like most image-related tasks, it will be completed in two phases: first, image processing, and second, training the model, which in this case will be developing a CNN (Convolutional Neural Networks) Keras model.

 While the project is good enough to detect alphabets from a set of images, under the guidance of an experienced computer scientist, you can demonstrate live translations at science fairs. 

Field: Computer Science

Skill Level: Advanced

Prior Knowledge Required: Coding, familiarity with machine learning terminologies, and experience with Python libraries and OpenCV.

If you’re interested in building a unique, personal project in AI & ML, consider applying to Veritas AI! 

Founded by Harvard graduate students, Veritas AI gives students the chance to learn the fundamentals of computer science and AI. You get a chance to work 1-on-1 with mentors from universities like Harvard, Stanford, MIT, Oxford, and more to write research papers or build unique projects. Last year, we had over 1000 students apply to do AI work with us, and our alums went on to study computer science and AI at top universities. You can find the application form here.

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