Band engineering is an effective strategy to improve the electronic transport properties of semiconductors. In thermoelectric materials research, density‐of‐states effective mass is an undoubted key factor in verifying the band engineering effect and establishing a strategy for enhancing thermoelectric performance. However, estimation of the effective mass is demanding or inaccurate depending on the methods taken. A simple equation is proposed, valid for all degeneracy: Log10 (md*T/300) = (2/3) Log10 (n) − (2/3) [20.3 − (0.00508 × |S|) + (1.58 × 0.967|S|)] that utilizes experimentally determined Seebeck coefficient (S) and carrier concentration (n) to determine the effective mass (md*) at a temperature (T). This straightforward equation, which gives an accurate analysis of the band modulation in terms of md*, is indispensable in designing thermoelectric materials of maximized performance.

The density-of-states effective mass (m d*) is commonly obtained by fitting the equation, S = (8π2 k B 2/3eh 2)m d*T(π/3n)2/3 (S, T, and n are the Seebeck coefficient, temperature, and the carrier concentration, respectively), to n-dependent S measurement. However, n is not a measurable parameter. It needs to be converted from the measured Hall carrier concentration (n H) using the Hall factor (r H = n/n H). The r H of material can be estimated by Single Parabolic Band (SPB) model if the band that contributed to transport is approximated to be parabolic and acoustic phonons dominantly scatter its carriers. However, the measurable n H is often used instead of n when utilizing the above equation due to the complex Fermi integrals involved in the SPB model calculation. Consequently, the m d* estimated from the above equation while using n H would be inaccurate. We propose the equation r H = 1.17 – [0.216 / {1 + exp­(( |S| – 101) / 67.1)}] as a simple and accurate method to obtain the r H from the measured S to facilitate the conversion from n H to n and eventually increase the accuracy of m d* estimated from the above equation.

Using thermoelectric refrigerators can address climate change because they do not utilize harmful greenhouse gases as refrigerants. To compete with current vapor compression cycle refrigerators, the thermoelectric performance of materials needs to be improved. However, improving thermoelectric performance is challenging because of the trade-off relationship between the Seebeck coefficient and electrical conductivity. Here, we demonstrate that decreasing conductivity effective mass by engineering the shape of the Fermi surface pocket (non-parabolicity factor) can decouple electrical conductivity from the Seebeck coefficient. The effect of engineering the non-parabolicity factor was shown by calculating the electronic transport properties of a state-of-the-art Bi-Sb-Te ingot via two-band model with varying non-parabolicity. The power factor (the product of the Seebeck coefficient squared and electrical conductivity) was calculated to be improved because of enhanced electrical conductivity, with an approximately constant Seebeck coefficient, using a non-parabolicity factor other than unity. Engineering the non-parabolicity factor to achieve lighter conductivity effective mass can improve the electronic transport properties of thermoelectric materials because it only improves electrical conductivity without decreasing the Seebeck coefficient (which is directly proportional to the band mass of a single Fermi surface pocket and not to the conductivity effective mass). Theoretically, it is demonstrated that a thermoelectric figure-of-merit <i>zT</i> higher than 1.3 can be achieved with a Bi-Sb-Te ingot if the non-parabolicity factor is engineered to be 0.2. Engineering the non-parabolicity factor is another effective band engineering approach, similar to band convergence, to achieve an effective improvement in power factor.

Semiconducting Metal Oxide (SMO) gas sensors have attracted considerable attention to analyze gases in exhaled breath and monitor air quality. This paper reports a recent research trend for enhancing sensing properties of WO 3 (tungsten oxide), a representative n-type gas sensing material. Firstly, the operating principle of WO 3 based gas sensors is explained. Secondly, various nanostructures of WO 3 from zerodimensional to three-dimensional are reviewed. Thirdly, doping and decoration as effective strategies to enhance gas sensing properties are introduced. We summarize recent progress and provide an insight for enhancing gas sensing properties of WO 3 based gas sensors.