Designing for dopability in semiconducting AgInTe₂

Abstract

Ternary chalcogenide semiconductors (e.g., CuInTe2, AgInTe2, AgGaTe2, Hg2GeTe4) have significant potential for excellent thermoelectric performance if appropriately doped. However, the efficacy of extrinsic dopants in these materials varies widely based...

Harnessing the unusually strong improvement of thermoelectric performance of AgInTe2 with nanostructuring

“…57) and AgInTe 2 . 58 This information is particularly critical for AgInTe 2 because previous experimental work had reported very low carrier concentration, well below the optimal calculated concentrations which are above 10 19 cm −3 at 700 K. Promisingly, Adamczyk et al found p-type AgInTe 2 samples with carrier concentrations around 10 18 cm −3 at 323 K which were synthesized at In- and Te-rich conditions. These results suggest that it might be possible to achieve carrier concentrations near the optimal value above 10 19 cm −3 at 700 K for p-type AgInTe 2 in order to maximize ZT.…”

Breaking AgInTe2 Quantum Dot Chain to Fabricate AgInTe2–ZnS Janus Nanocrystals

“…Further, inverse fast Fourier transformation (IFFT) of the HRTEM image confirmed the presence of this (131) plane with a plane distance of 0.328 nm (inset Figure c). Upon addition of the Ag-DDT precursor, initially, the reaction passes through the AgInTe 2 –AgIn 5 Te 8 mix phase due to the incomplete diffusion of Ag + ions in the In 4 Te 3 matrix . Finally, the slow nucleation of the metastable AgInTe 2 hexagonal NCs was started, and with a reaction time of 80 min, we obtained the metastable pure hexagonal AgInTe 2 MR.…”

“…Upon addition of the Ag-DDT precursor, initially, the reaction passes through the AgInTe 2 −AgIn 5 Te 8 mix phase due to the incomplete diffusion of Ag + ions in the In 4 Te 3 matrix. 35 Finally, the slow nucleation of the metastable AgInTe 2 hexagonal NCs was started, and with a reaction time of 80 min, we obtained the metastable pure hexagonal AgInTe 2 MR. The shoulders at 23 and 26°for the planes (100) and (101), respectively, are the characteristic XRD features of the hexagonal crystal structure, as appeared in earlier literature via simulation (Figures 2d and S1).…”

Harnessing GPT-3.5 for text parsing in solid-state synthesis – case study of ternary chalcogenides

“…One interesting fact is that the interpolation is able to suggest quenching as cooling state which is related to phase precipitation tendency during the synthesis. 40 For extrapolating to predict a synthesis recipe for AgSbTe 2 , the GPT-3.5 model was not able to yield a proper synthesis recipe, by merely guessing that the recipe for AgSbTe 2 is similar to that of AgInTe 2 or AgInSe 2 . This result is only because the ChExSp dataset was provided to the GPT-3.5 API as an input – else, GPT-3.5 responds with response with three sequential melt times going from low to high temperatures, which we know is inaccurate based on domain expertise.…”