Scientific Model

Cave paintings made by the people of the Aurignacian Culture of Europe as early as 32,000 BC marked the lunar cycle, which showed the first-ever record of humans attempting to understand the motion of celestial objects. The ancient Babylonians who rose to prominence sometime around 1,600 BC (centred in modern-day Iraq) kept detailed records of the motions of the stars and planets, which contributed to later models of the solar system.

The earliest models of the solar system were geocentric - models in which the Sun, Moon and planets orbited the Earth. Heliocentric models - models with the Sun at the centre of the solar system - were introduced as early as 280 BC by the Greek philosopher Aristarchus, but all of these models were rejected until the 17^th century when the Copernican model became the most popular view of the solar system, with the Sun at its centre. Copernicus published his work on his model in 1543, which consisted of a model with a rotating Earth. Unfortunately, he died in the same year and did not live to see his model gain recognition - it took nearly 100 years for the heliocentric model to become widely accepted. The model we currently use is fundamentally based on the Copernican model.

Scientific models play a key role in our understanding of the many natural phenomena of our universe. It is important that they agree with experimental data and make predictions that can be tested. Scientific models can change a lot over time, such as the model of the solar system, often due to new discoveries being made. In this article, will learn about the different types of scientific models, as well as their uses and limitations.

Definition of a scientific model

Scientific models are simpler representations of systems that are used for explaining or visualising scientific processes and natural phenomena, as well as for making predictions. Models show the key features of the system being represented and they demonstrate how these features connect with each other. Models must be consistent with observations and experimental results. Useful scientific models will have the following properties:

• Explanatory power - the model is able to explain an idea or process.
• Predictive power - the model makes predictions that can be tested by experimentation.
• Consistency - the model does not contradict other scientific models.

Scientific models are important as they help us to understand the world around us. They help to picture something that we cannot see or is hard to understand. A good model has little to no assumptions and agrees with data and evidence gained from scientific experiments.

Types of scientific models

There are lots of different types of scientific models. They can be split up into five main categories.

Scientific models can also be split up into three other categories: physical, conceptual and mathematical models. Physical models consist of physical objects that you can touch, such as a globe. Physical models often represent systems that are too large or too small to see directly.

Fig. 2 - A globe is a physical model of the Earth.

On the other hand, conceptual models use known concepts to help you visualise systems that could be impossible to see or difficult for a human mind to comprehend. An example of this is the Bohr model of the atom, which shows electrons orbiting around the nucleus just like how the planets orbit around the sun. This allows us to picture what is happening at the atomic scale.

Fig. 3 - The Bohr model consists of electrons orbiting around the nucleus of an atom.

Scientific model examples

All of this talk about scientific models might have seemed a bit abstract up to now, so let us explore some examples of the different types of models in order to understand exactly what they are.

Particle model of matter

The particle model of matter is a representational model. It states that all matter consists of small particles that are in constant motion. The model helps us to understand why the different states of matter behave as they do and also how changes of state occur.

Lock and key model

The lock and key model is another example of a representational model and is used to visualise enzyme-substrate interactions. For an enzyme to catalyse a reaction, it must bind to a specific substrate. The lock and key model draws on the analogy of a key fitting into a specific lock in order to understand this process!

Fig. 5 - The lock and key model describes the interaction between enzymes and substrates.

Models of classification

Models of classification are descriptive models - they use words to describe a system. The first model of classification of the species of life on Earth was made by Carl Linnaeus in 1735. His model consisted of three groups - animals, vegetables and minerals - which he called 'kingdoms'. He also sorted organisms into smaller groups within these kingdoms. His model has been modified over time and the groups are now:

• Kingdom
• Phylum
• Class
• Order
• Family
• Genus
• Species

Topographic maps

Topographic maps are examples of spatial models. They use colours and contour lines to represent changes in elevation. Topographic maps are able to show a three-dimensional landscape on a two-dimensional piece of paper.

Fig. 6 - A topographic map of the baltic. These maps can be used to represent three-dimensional surfaces.

Mathematical modelling and scientific computing

Mathematical and computational might not be the types of models that first come to mind when you think of a scientific model. In this section, we will look at an example of both a mathematical model and how scientific computing can be used to produce models relevant to all disciplines of science.

Newton's law of gravitation

Isaac Newton formulated his famous law of gravitation in 1687. It is an example of a mathematical model and describes the effects of the force of gravity through the language of mathematics. For instance, on the surface of the Earth, Newton's law states that the weight of an object (the downward force due to gravity) is given by

$$W=mg,$$

where \( W \) is the weight in \( \mathrm N \), \( m \) is the mass in \( \mathrm{kg} \) and \( g \) is the gravitational field strength on the Earth's surface measured in \( \mathrm m/\mathrm{s^2} \).

Climate changes

When the calculations involved in a mathematical model become too complicated, scientific computing is used to carry them out. The model becomes a computational model. For example, scientists use computational models to predict how the Earth's climate will change in the future. They are able to do this through complex calculations that use past data and consider how climate events relate to each other. The more computing power that goes into a model, the more accurate it becomes.

Limitations of scientific models

Scientific models often have limitations as they are by necessity simpler than the real systems or processes that they are describing, due to us having to be able to understand them.

Scientific models sometimes have to be changed when a discovery is made which contradicts the current model. In this instance, the model either has to be updated so that it agrees with the new experimental data or sometimes the model has to be completely replaced!

A famous example of this is how it was discovered Newton's law of gravitation did not perfectly describe gravity and was actually only an approximation. Newton's law explains how the planets orbit around the sun, but it gives the wrong prediction for the orbit of Mercury. Einstein formulated his general theory of relativity in 1915 to explain this and showed that Newton's law becomes inaccurate when the gravitational forces become very large (like when an object or body is very close to the sun).

Most scientific models are approximations. They are useful for most situations but they can become inaccurate under certain conditions or when extreme detail is required. A scientific model may also be limited when the system that the model is attempting to describe is impossible to visualise. As we have already discussed, the Bohr model of the atom consists of electrons orbiting around the nucleus in a solar system-type model. However, electrons do not actually orbit around the nucleus, the model is inaccurate.

In 1913 Niel's Bohr did not take wave-particle duality into account in his model of the atom. You might already be aware that light can act as both a particle and a wave, but this holds true for electrons too! A more accurate model of the atom would be the Schrödinger model which takes wave-particle duality into account. You will learn more about this model and its implications if you choose to study physics at A-level.

The main reason Bohr's model is useful is that it clearly demonstrates the underlying structure of the atom and it is relatively neat and accurate. Furthermore, Bohr's model is an important fundamental step at GCSE level to understanding the physics that governs the world.