Search for high-capacity oxygen storage materials by materials informatics

Ohba, Nobuko; Yokoya, Takuro; Kajita, Seiji; Takechi, Kensuke

doi:10.1039/c9ra09886k

Cited by 12 publications

(8 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Let us now demonstrate how the results and approaches described above can be employed to evaluate the performance of complex oxides in some real-life thermochemical applications related to solar energy conversion and storage. − Thermal energy input, in this specific case produced by concentrated solar power, is stored in oxides in accordance with the following equation: where Δ H sens ◦ = ∫ T 0 T 1 C p d T , so-called “sensible” energy, ,,, denotes the specific heat storage capacity, which is a purely thermal contribution to Δ H total ◦ , excluding any heat effects resulting from the changes in the oxide composition. In turn, Δ H red ◦ in eq is the “chemical”, oxygen exchange-related energy storage capacity .…”

Section: Resultsmentioning

confidence: 99%

“…The overall efficiency of a temperature and pressure swing adsorption device based on eq will depend to a great extent on the efficiency of the other parts of the system such as pumps and heat exchangers . As for the material performance, while neither SrFeO 3−δ nor RBaCo 2 O 6−δ (R = Pr, Eu, Sm, or Gd) demonstrates a record equilibrium OSC, especially at lower temperatures (below ∼773 K), their OSC is nevertheless comparable with that of many other oxides, including those with perovskite-like ,, and non-perovskite structure . Among the latter, a much higher equilibrium OSC and a much higher energy storage capacity characterize primarily stoichiometric oxides that undergo phase changes with abrupt O 2 loss or gain, such as Co 3 O 4 or CoO, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Solar energy can be harvested in different ways, either directly, using photovoltaic systems, or indirectly, in the form of heat that can be used, in turn, to drive some industrial processes. Among them, thermochemical methods involving redox-active oxides have received a great deal of attention. − Various perovskite oxides, especially those possessing a wide oxygen homogeneity range, have been studied as promising materials for oxygen storage or chemical looping (solar-to-fuel conversion). ,, However, until now, double perovskites RBaCo 2 O 6−δ (R = rare-earth metal or Y) have been studied mainly as cathode materials for solid oxide fuel cells rather than oxygen storage materials and, moreover, data on their redox thermodynamics are scarce.…”

Section: Introductionmentioning

confidence: 99%

“…1−11 Various perovskite oxides, especially those possessing a wide oxygen homogeneity range, have been studied as promising materials for oxygen storage or chemical looping (solar-to-fuel conversion). 1,8,9 However, until now, double perovskites RBaCo 2 O 6−δ (R = rare-earth metal or Y) have been studied mainly as cathode materials for solid oxide fuel cells rather than oxygen storage materials and, moreover, data on their redox thermodynamics are scarce.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Redox Thermochemistry, Thermodynamics, and Solar Energy Conversion and Storage Capability of Some Double Perovskite Cobaltites

et al. 2021

View full text Add to dashboard Cite

The oxygen nonstoichiometry, δ, and oxidation enthalpy, ΔH ox , of double perovskites RBaCo 2 O 6−δ (R = Sm or Eu) were simultaneously measured depending on the temperature and oxygen partial pressure, p O 2 . Theoretical equations for ΔH ox (T, δ) and p O 2 (T, δ) were derived from the defect structure model based on the oxygen exchange and cobalt disproportionation reactions. These equations were fitted independently to each of the experimental ΔH ox (T, δ) and p O 2 (T, δ) data sets. The resulting enthalpies of defect reactions were found to be almost the same irrespective of the calculation method. In other words, the models, describing satisfactorily the data, can be used to calculate both compositional dependences and redox thermodynamics of RBaCo 2 O 6−δ (R = Sm or Eu). In addition, from the previously published data and the data presented here, trends were determined in the defect reaction thermodynamics of RBaCo 2 O 6−δ (R = La, Pr, Nd, Sm, Eu, Gd, or Y). Drop calorimetric measurements were performed in air to obtain enthalpy increments for RBaCo 2 O 6−δ (R = Sm or Eu) with variable oxygen content because the samples lost oxygen upon being heated in the calorimetric cell. As-obtained data were used to calculate the functional dependences of enthalpy increments of EuBaCo 2 O 5.56 and SmBaCo 2 O 5.6 with a constant oxygen content. In addition, as an example of practical application-oriented calculations for solar energy conversion and oxygen storage, the performances at equilibrium of RBaCo 2 O 6−δ (R = Pr, Sm, Eu, or Gd) were evaluated and compared to those of SrFeO 3−δ as a reference material.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Redox Thermochemistry, Thermodynamics, and Solar Energy Conversion and Storage Capability of Some Double Perovskite Cobaltites

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Then, the ab initio calculations precisely examine this subset of the candidates. These virtual screenings have been increasingly employed for materials discoveries in catalysis 10,11 , organic light-emitting diodes 7 , thermoelectric compounds 12 , photovoltaic materials 13 , and Li-ion cathodes 3,14,15 .…”

Section: Introductionmentioning

confidence: 99%

Discovery of superionic conductors by ensemble-scope descriptor

et al. 2020

Self Cite

View full text Add to dashboard Cite

Machine learning accelerates virtual screening in which material candidates are selected from existing databases, facilitating materials discovery in a broad chemical search space. Machine learning models quickly predict a target property from explanatory material features called descriptors. However, a major bottleneck of the machine learning model is an insufficient amount of training data in materials science, especially data with non-equilibrium properties. Here, we develop an alternative virtual-screening process via ensemble-based machine learning with one handcrafted and two generic descriptors to maximize the inference ability even using a small training dataset. A joint representation with the three descriptors translates the physical and chemical properties of a material as well as its underlying short-and long-range atomic structures to describe a multifaceted perspective of the material. As an application, the ensemble-scope descriptor learning model was trained with only 29 entries in the training dataset, and it selected potential oxygen-ion conductors from 13,384 oxides in the inorganic crystal structure database. The experiments confirmed that we successfully discovered five compounds that have not been reported, to the best of our knowledge, as oxygen-ion conductors.

show abstract