Professionals in the building industry make material decisions on an almost daily basis – decisions that require a foundational understanding of how those materials are made. That’s where a degree in Materials Science and Building Construction comes in.
Material scientists study everything from atoms to large manufactured parts, and combine knowledge from physics, chemistry and engineering.
Materials Selection
In the field of materials science, engineers develop and study new ways to use existing materials as well as find more environmentally friendly methods to produce and create those materials. They also research ways to recycle those materials when the time comes. This work is essential to the industrial society, as it allows buildings and other structures to be built with safe and reliable materials that will perform as expected.
Developing a comprehensive material selection system will help designers make better decisions when choosing the appropriate materials for construction projects. These systems typically consider a wide range of factors or variables to assess the potential impact of each choice on different issues, such as cost and durability. The system then compares the alternatives based on these criteria to select the best one.
The system will include a method to rank the importance of each factor or variable, with higher-ranked priorities considered more important than lower ones. This will allow users to evaluate the overall impact of the alternative materials on different aspects of the project, including resiliency and energy efficiency.
A pilot survey conducted by the authors indicated that most participants regarded environmental and social criteria as more important than economic or performance considerations when selecting appropriate building materials. The development of a material-selection system will provide an opportunity to address these concerns and encourage the use of local or recycled materials in mainstream design and construction.
Materials Testing
When materials are used in the construction of products, it is crucial to ensure that they meet strict quality standards set by UK and international bodies. In order to achieve these quality standards, materials must be tested. Testing can include non-destructive and destructive tests which measure the material’s exact composition and assess its strength. Testing can also be performed in an investigative sense to find out why a material failed whilst in use.
Testing can be done on a variety of length scales, from the molecular level to the macro-level of the material’s structure and how it has been processed. Using information on how the atoms, ions and molecules within a material interact, materials scientists can then design materials for a specific purpose.
The test results can also provide a clear definition of a material’s properties, which allows for a comparison between different materials. This information is incredibly valuable to manufacturers, as it can help them optimize their production process and develop new materials with superior qualities.
Materials science is inherently interdisciplinary, and as such it has strong links to the fields of physics, chemistry and engineering. Many of the tools and techniques used by materials scientists are derived from other scientific disciplines, such as metallurgy and mineralogy. This multidisciplinary approach is essential for understanding the complex interplay between the material’s atomic and molecular structures, their micro-scale features and the resulting properties.
Materials Database Development
Materials scientists play an important role in the construction industry by improving the strength and durability of building structures. They also develop new materials that are lighter in weight, which helps reduce the cost of building and maintenance. In addition, material science advances allow for more environmentally-friendly buildings by reducing the amount of chemicals used in construction.
The development of materials databases is a key tool for researchers seeking to design new and improved materials for use in a variety of applications. These databases provide researchers with a wealth of information regarding existing materials, and they can be used to identify the most promising candidate materials for specific applications. Using advanced technologies like integration with machine learning and open access, materials databases are poised to continue to advance in the future.
Material databases have a number of distinct challenges that must be addressed in order to be effective tools for research and design. These challenges include data standardization, continuous curation, integration with artificial intelligence, and collaboration.
One example of a successful effort to address these challenges is the development of a functionally graded materials database system developed by NASA. The system organizes the existing body of additive manufacturing (AM) build data in a meaningful way and makes it easier to compare properties between AM builds and conventionally manufactured parts.
Materials Simulation
Materials modeling and simulation tools have accelerated the development of materials, enabling scientists and engineers to design new products and optimize processes, thus eliminating expensive and time-consuming physical tests. However, the complexity of material systems makes it difficult to predict their behavior at a wide range of length and time scales.
Computational methods have been adapted to address this challenge, combining modeling and simulation techniques at multiple levels of resolution with advanced data analytics. These techniques allow the characterization of structural and chemical properties from molecular to macroscale. The emergence of the integrated computational materials engineering (ICME) paradigm has proven its value in accelerating materials development and discovery, reducing prototyping and testing times, and facilitating path finding.
All simulation methods require an underlying model to describe materials behavior. The model determines the sensitivity of the simulation to variations in the governing equations and the accuracy level of the result. Some models are explicitly physics-based, while others rely on empirical correlations and assumptions to emulate physical phenomena. The physics-based models are less biased with respect to unverified assumptions and spurious correlations, but they impose high computational costs.
Some hybrid models, also known as Reduced Order Models (ROMs), Surrogate Models, or Metamodels, provide a balance between fidelity and required computational resources. ROMs include models of structural properties, such as dislocation pile-up mechanisms, and atomistic thermodynamics, such as the Hall-Petch relationship.