Improving the Thermal Conductivity of Clay Bricks through the Addition of Industrial Waste

The amount of energy used to manage the thermal environment of buildings can account for upwards of 40% of the total energy use of developed countries. As building codes and regulations become more stringent in order to promote energy efficiency, the construction industry is engaged in developing sustainable materials with improved thermal properties. Using industrial waste materials to create building supplies is one method of producing a more sustainable product; it results in less raw material use, and negates the need for expensive waste management solutions. In 2015, Santos et al. completed a project in which they used nano-crystalline aluminum sludge as an additive during the production of clay bricks used for external wall construction (Figure 1). The goal of the research was not only to produce a material incorporating industrial waste, but to also improve the thermal performance of the product in construction applications.

Figure 1. A clay brick of a similar design to what was measured by Santos et al. (2015).¹

Santos et al. (2015) used a combination of experimental testing in a laboratory setting and numerical simulations using 3-D finite element models. Laboratory testing consisted of thermal conductivity, density, water absorption, porosity, and thermal transmittance measurements. These values were then used to validate the numerical models. Experimental bricks created with the addition of aluminum sludge were compared against commercially available bricks.

Thermal conductivity testing was performed using the Hot Disk Transient Plane Source 2500 S, a top of the line thermal conductivity instrument capable of performing absolute thermal conductivity measurements along a range of 0.005 to 1000 W/mK. The Hot Disk system uses sensors composed of nickel foil insulated by a thin film of Kapton that act as both the heat source and a temperature measurement device. These sensors are available in two-sided and one-sided forms. The versatility of these sensors enables the TPS system to perform measurements on samples of an unlimited size. Tests performed using the two-sided sensor involve sandwiching the sensor between two identical pieces of the sample to be tested (Figure 2). The one-sided TPS-S only requires one sample piece and is excellent for tests involving samples that are expensive or hard to cut (Figure 2).

Figure 2. The sample set up used for thermal conductivity testing with the two-sided sensor is on the left, while the use of the TPS-S is shown on the right.

Thermal Conductivity Results of Ecological Bricks

Thermal conductivity values obtained from original and ecological bricks using the Hot Disk TPS 2500 S confirmed that the addition of the aluminum sludge had created a product with an improved thermal performance. Santos et al. (2015) reported that the U-value (which is representative of how a building transmits heat) was nearly 10% lower than that the conventional brick. Materials with lower thermal conductivities are better insulators, and help to reduce the amount of heat gained or lost by buildings. The researchers followed the collection of these experimental results with extensive numerical modelling of wall structures composed of the sample bricks and the values obtained through these methods were in line with the laboratory data. For comprehensive results and discussion, please follow the link to the scientific paper in the reference section.

The results obtained in this study indicate that nano-crystalline sludge produced by the aluminum industry can be recycled into building materials that will better manage the thermal environments of buildings. Through efficient thermal management, the energy needed to maintain a comfortable environment can be reduced, helping nations to reach sustainability goals. This study is an excellent example of how the Hot Disk TPS equipment can be a valuable tool to aid comprehensive thermal modelling. The accuracy and consistency of this method in producing results means that it is a trusted resource for reference data when designing experimental models.