Best thermoelectric efficiency of ever-explored materials.

A thermoelectric device is a heat engine that directly converts heat into electricity. Many materials with a high figure of merit Z T have been discovered in the anticipation of a high thermoelectric efficiency. However, there has been a lack of investigations on efficiency-based material evaluation, and little is known about the achievable limit of thermoelectric efficiency. Here, we report the highest thermoelectric efficiency using 12,645 published materials. The 97,841,810 thermoelectric efficiencies are calculated using 808,610 device configurations under various heat-source temperatures ( T h ) when the cold-side temperature is 300 K, solving one-dimensional thermoelectric integral equations with temperature-dependent thermoelectric properties. For infinite-cascade devices, a thermoelectric efficiency larger than 33% (≈⅓) is achievable when T h exceeds 1400 K. For single-stage devices, the best efficiency of 17.1% (≈1/6) is possible when T h is 860 K. Leg segmentation can overcome this limit, delivering a very high efficiency of 24% (≈1/4) when T h is 1100 K.

Electric Transport Properties of NaAlB14 with Covalent Frameworks.

A synthetic protocol was developed for obtaining a single phase of polycrystalline NaAlB14 with strongly connected intergrain boundaries. NaAlB14 has a unique crystal structure with a tunnel-like covalent framework of B that traps monovalent Na and trivalent Al ions. Owing to the atmospheric instability and volatility of Na, the synthesis of polycrystalline NaAlB14 and its physical properties have not been reported yet. This study employed a two-step process to achieve single-phase polycrystalline NaAlB14. As a first step, a mixture of Al and B with excess Al was sintered in the Na vapor atmosphere followed by HCl treatment to remove excess Al as a second step. For obtaining bulk samples with strong grain connection, vacuum or high-pressure (HP) annealing was employed. HP annealing promoted bandgap shrinkage due to the crystal strain and defect levels and suppressed intergranular resistance. As a result, the HP-annealed sample achieved superior transport properties (0.1 kΩ cm at 300 K) to the vacuum-annealed sample (260 kΩ cm). Furthermore, from the viewpoint of its crystal structure and DFT calculations, the most probable site for the defect was suggested to be the Na site.

Na3MgB37Si9: an icosa-hedral B12 cluster framework containing {Si8} units.

Single crystals of a novel sodium-magnesium boride silicide, Na3MgB37Si9 [a = 10.1630 (3) Å, c = 16.5742 (6) Å, space group R m (No. 166)], were synthesized by heating a mixture of Na, Si and crystalline B with B2O3 flux in Mg vapor at 1373 K. The Mg atoms in the title compound are located at an inter-stitial site of the Dy2.1B37Si9-type structure with an occupancy of 0.5. The (001) layers of B12 icosa-hedra stack along the c-axis direction with shifting in the [-a/3, b/3, c/3] direction. A three-dimensional framework structure of the layers is formed via B-Si bonds and {Si8} units of [Si]3-Si-Si-[Si]3.

Machine Learning to Predict Quasicrystals from Chemical Compositions.

Quasicrystals have emerged as the third class of solid-state materials, distinguished from periodic crystals and amorphous solids, which have long-range order without periodicity exhibiting rotational symmetries that are disallowed for periodic crystals in most cases. To date, more than one hundred stable quasicrystals have been reported, leading to the discovery of many new and exciting phenomena. However, the pace of the discovery of new quasicrystals has lowered in recent years, largely owing to the lack of clear guiding principles for the synthesis of new quasicrystals. Here, it is shown that the discovery of new quasicrystals can be accelerated with a simple machine-learning workflow. With a list of the chemical compositions of known stable quasicrystals, approximant crystals, and ordinary crystals, a prediction model is trained to solve the three-class classification task and its predictability compared to the observed phase diagrams of ternary aluminum systems is evaluated. The validation experiments strongly support the superior predictive power of machine learning, with the overall prediction accuracy of the phase prediction task reaching ≈0.728. Furthermore, analyzing the input-output relationships black-boxed into the model, nontrivial empirical equations interpretable by humans that describe conditions necessary for stable quasicrystal formation are identified.

Phase stability and thermoelectric properties of semiconductor-like tetragonal FeAl2.

Tetragonal FeAl2 is a high-pressure phase and is predicted to exhibit semiconductor-like behavior. We investigated the pressure and temperature synthesizing conditions of tetragonal FeAl2, supported by in situ X-ray diffractions, using synchrotron radiation during heating the sample under a pressure of 20 GPa. Based on the determined optimal conditions, we synthesized the bulk polycrystalline samples of tetragonal FeAl2 at 7.5 GPa and 873 K, using a multi-anvil press and measured its thermoelectric properties. The Seebeck coefficient of tetragonal FeAl2 showed a large negative value of - 105 µV/K at 155 K and rapidly changed to a positive value of 75 µV/K at 400 K. Although these values are the largest among those of Fe-Al alloys, the maximum power factor remained at 0.41 mW/mK2 because the carrier concentration was not tuned. A comparison of the Gibbs free energy of tetragonal FeAl2, triclinic FeAl2 and FeAl+Fe2Al5 revealed that tetragonal FeAl2 became unstable as the temperature increased, because of its smaller contribution of vibrational entropy.

Rechargeable magnesium-ion battery based on a TiSe2-cathode with d-p orbital hybridized electronic structure.

Rechargeable ion-batteries, in which ions such as Li(+) carry charges between electrodes, have been contributing to the improvement of power-source performance in a wide variety of mobile electronic devices. Among them, Mg-ion batteries are recently attracting attention due to possible low cost and safety, which are realized by abundant natural resources and stability of Mg in the atmosphere. However, only a few materials have been known to work as rechargeable cathodes for Mg-ion batteries, owing to strong electrostatic interaction between Mg(2+) and the host lattice. Here we demonstrate rechargeable performance of Mg-ion batteries at ambient temperature by selecting TiSe2 as a model cathode by focusing on electronic structure. Charge delocalization of electrons in a metal-ligand unit through d-p orbital hybridization is suggested as a possible key factor to realize reversible intercalation of Mg(2+) into TiSe2. The viewpoint from the electronic structure proposed in this study might pave a new way to design electrode materials for multivalent-ion batteries.