arXiv subjects

Zhufeng Hou

Publications and source records attributed to Zhufeng Hou.

At least 19 recordsLinked to original sources

arXiv2022

Potential high-$T_{c}$ superconductivity in YCeH$_{x}$ and LaCeH$_{x}$ under pressure

Lanthanum, yttrium, and cerium hydrides are the three most well-known superconducting binary hydrides (La-H, Y-H, and Ce-H systems), which have gained great attention in both theoretical and experimental studies. Recent studies have shown that ternary hydrides composed of lanthanum and yttrium can achieve high superconductivity around 253 K. In this study we employ the evolutionary-algorithm-based crystal structure prediction (CSP) method and first-principles calculations to investigate the stability and superconductivity of ternary hydrides composed of (Y, Ce) and (La, Ce) under high pressure. Our calculations show that there are multiple stable phases in Y-Ce-H and La-Ce-H systems, among which $P4/mmm$-YCeH$_{8}$, $P\bar{6}m2$-YCeH$_{18}$, $R\bar{3}m$-YCeH$_{20}$, $P4/mmm$-LaCeH$_{8}$, and $R\bar{3}m$-LaCeH$_{20}$ possessing H$_{18}$, H$_{29}$ and H$_{32}$ clathrate structures can maintain both the thermodynamic and lattice-dynamic stabilities. In addition, we also find that these phases also maintain a strong resistance to decomposition at high temperature. Electron-phonon coupling calculations show that only three of these five phases can exhibit high-temperature superconductivity. The superconducting transition temperatures ($T_\mathrm{c}$) of $R\bar{3}m$-YCeH$_{20}$, $R\bar{3}m$-LaCeH$_{20}$, and $P\bar{6}m2$-YCeH$_{18}$ are predicted using the Allen-Dynes-modified McMillan formula to be 122 K at 300 GPa, 116 K at 250 GPa, and 173 K at 150 GPa, respectively. Moreover, the pressure to stabilize $P\bar{6}m2$-YCeH$_{18}$ can be lowered to 150 GPa, suggesting an accessible condition for its high-pressure synthesis.

cond-mat.supr-con↗

arXiv2022

(La,Th)H$_{10}$: the potential high-$T_{c}$ superconductors stabilized thermodynamically below 200 GPa

The recent high-pressure experimental discovery of superconductivity in (La,Y)H$_{10}$, (La,Ce)H$_{9}$, (La,Ce)H$_{10}$, (Y,Ce)H$_{9}$, and (La,Nd)H$_{10}$ shows that the ternary rare-earth clathrate hydride can be promising candidate for high-temperature superconductor. In this work, we theoretically demonstrate that the combination of actinide-metal thorium (Th) and rare-earth-metal lanthanum (La) with hydrogen can also form some ternary hydrides with cage-like structures to be stable at 200 GPa. Using the evolutionary algorithms combined with the first-principles calculations, we have predicted the pressure-dependent ternary phase diagram of La$_{x}$Th$_{y}$H$_{z}$, particularly including the case of (La$_{1-x}$Th$_{x}$)H$_{n}$ [or designated as (La,Th)H$_{n}$ for simplicity]. Our calculations show that the hydrogen-rich phases such as (La,Th)H$_{9}$ (only including $P\bar{6}m2$-LaThH$_{18}$) and (La,Th)H$_{10}$ (including $I4/mmm$-La$_{3}$ThH$_{40}$, $R\bar{3}m$-LaThH$_{20}$, and $I4/mmm$-LaTh$_{3}$H$_{40}$) with H$_{29}$ and H$_{32}$ cages can be thermodynamically stable below 200 GPa. However, the phase decomposition can happen to only (La,Th)H$_{9}$ when the pressure is above 150 GPa. More importantly, the electron-phonon coupling (EPC) calculations show that the (La,Th)H$_{10}$ series could the potential superconductors, of which $I4/mmm$-La$_{3}$ThH$_{40}$ at 200 GPa exhibits the large EPC constant $λ$ = 2.46 with a highest transition temperature ($T_\mathrm{c}$) of 210 K. Since there are few previous studies on ternary hydrides composed of actinide metals, the present work would greatly stimulate the further discovery of this type of ternary hydrides and provide useful guidance for the high-pressure experimental studies on them.

cond-mat.supr-con↗

arXiv2021

High-pressure Mg-Sc-H phase diagram and its superconductivity from first-principles calculations

In this work, global search for crystal structures of ternary Mg-Sc-H hydrides (Mg$_x$Sc$_y$H$_z$) under high pressure ($100 \le P \le 200$ GPa) were performed using the evolutionary algorithm and first-principles calculations. Based on them, we computed the thermodynamic convex hull and pressure-dependent phase diagram of Mg$_x$Sc$_y$H$_z$ for $z/(x+y) < 4$. We have identified the stable crystal structures of four thermodynamically stable compounds with the higher hydrogen content, i.e., $R\bar{3}m$-MgScH$_{6}$, $C2/m$-Mg$_{2}$ScH$_{10}$, $Immm$-MgSc$_{2}$H$_{9}$ and $Pm\bar{3}m$-Mg(ScH$_{4}$)$_{3}$. Their superconducting transition temperatures were computationally predicted by the McMillan-Allen-Dynes formula combined with first-principles phonon calculations. They were found to exhibit superconductivity; among them, $R\bar{3}m$-MgScH$_{6}$ was predicted to have the highest $T_{c}$ (i.e. 23.34 K) at 200 GPa.

cond-mat.supr-con↗

arXiv2021

The systematic study on the stability and superconductivity of Y-Mg-H compounds under high pressure

Motivated by recent discovery of yttrium-based high-temperature ternary superconducting hydrides (e.g., CaYH$_{12}$, LaYH$_{12}$, and ScYH$_{6}$), we have employed evolutionary algorithm and first-principles calculations to comprehensively examine the structural stability and superconductivity of the YMgH$_{x}$ system at high pressure. The hydrogen content $x$ and the pressure are both important factors in the stability of these candidate structures. We find that the stability of hydrogen-rich materials frequently necessitates higher pressure. For instance, the pressures to stabilize $P4/mmm$-YMgH$_{8}$ and $Cmmm$-YMgH$_{12}$ are both more than 250 GPa. Hydrogen-less materials, such as $I4_{1}/amd$-YMgH$_{2}$ and $P6_{3}/mmc$-YMgH$_{3}$, can be stable at pressures as low as 100 GPa. In addition, we find a metastable structure for YMgH$_{6}$ with the same space group as the $P4/mmm$-YMgH$_{8}$. A metastable sodalite-like face-centered cubic (FCC) structure is also found in YMgH$_{12}$. These four clathrate structures of $P4/mmm$-YMgH$_{6}$, $P4/mmm$-YMgH$_{8}$, $Cmmm$-YMgH$_{12}$, and $Fd\bar{3}m$-YMgH$_{12}$ is made up of H14, H18, H24, and H24 cages, respectively, in which the H-H pair exhibits weak covalent bonding. According to phonon calculations, $P4/mmm$-YMgH$_{6}$ and $P4/mmm$-YMgH$_{8}$ require a pressure of 300 GPa to maintain dynamic stability, however $Cmmm$-YMgH$_{12}$ and $Fd\bar{3}m$-YMgH$_{12}$ can maintain dynamic stability at pressures of 200 GPa and 250 GPa, respectively. Electron-phonon coupling calculations indicate that they might be potential high-temperature superconductors, with superconductivity intimately linked to the H cage structure. The sodalite structure $Fd\bar{3}m$-YMgH$_{12}$ has a $T_\mathrm{c}$ value of 190 K and a strong electron-phonon coupling constant of 2.18.

cond-mat.supr-con↗

arXiv2021

High-$T_c$ superconducting hydrides formed by LaH$_{24}$ and YH$_{24}$ cage structures as basic blocks

Based on recent studies regarding high-temperature (high-$T_c$) La-Y ternary hydrides (e.g., $P{\bar{1}}$-La$_2$YH$_{12}$, $Pm{\bar{3}}m$-LaYH$_{12}$, and $Pm{\bar{3}}m$-(La,Y)H$_{10}$ with a maximum $T_c \sim 253$ K), we examined the phase and structural stabilities of the (LaH$_6$)(YH$_6$)$_y$ series as high-$T_c$ ternary hydride compositions using a genetic algorithm and $\it ab$ $\it initio$ calculations. Our evaluation showed that the $Pm\bar{3}m$-LaYH$_{12}$ reported in the previous study was unstable during decomposition into $R\bar{3}c$-LaH$_{6}$ + $Im\bar{3}m$-YH$_{6}$. We also discovered new crystal structures, namely $Cmmm$-LaYH$_{12}$ ($y=1$), $R\bar{3}c$-LaYH$_{12}$ ($y=1$), $Cmmm$-LaY$_3$H$_{24}$ ($y=3$), and $R\bar{3}$-LaY$_3$H$_{24}$ ($y=3$), showing stability against such decomposition. While $R\bar{3}c$ ($y=1$) and $R\bar{3}$ ($y=3$) did not exhibit superconductivity owing to the extremely low density of states at the Fermi level, $Cmmm$ phases exhibited a $T_{c}$ of approximately 140~K at around 200~GPa owing to the extremely high electron--phonon coupling constant ($λ$ = 1.876 for LaYH$_{12}$). By the twice longer stacking for $Cmmm$-LaY$_3$H$_{24}$, the coupling constant increased owing to the chemical pressure of Y, leading to a slightly increased $T_{c}$.

cond-mat.supr-con↗

arXiv2021

High-$T_c$ ternary metal hydrides, YKH$_{12}$ and LaKH$_{12}$, discovered by machine learning

The search for hydride compounds that exhibit high $T_c$ superconductivity has been extensively studied. Within the range of binary hydride compounds, the studies have been developed well including data-driven searches as a topic of interest. Toward the search for the ternary systems, the number of possible combinations grows rapidly, and hence the power of data-driven search gets more prominent. In this study, we constructed various regression models to predict $T_c$ for ternary hydride compounds and found the extreme gradient boosting (XGBoost) regression giving the best performance. The best performed regression predicts new promising candidates realizing higher $T_c$, for which we further identified their possible crystal structures. Confirming their lattice and thermodynamical stabilities, we finally predicted new ternary hydride superconductors, YKH$_{12}$ [$C2/m$ (No.12), $T_c$=143.2 K at 240 GPa] and LaKH$_{12}$ [$R\bar{3}m$ (No.166), $T_c$=99.2 K at 140 GPa] from first principles.

cond-mat.supr-con↗

arXiv2020

Pressure-Induced Superconductivity in Layered Transition-metal Chalcogenides (Zr,Hf)GeTe$_{4}$ Explored by Data-driven Approach

Layered transition-metal chalcogenides (Zr,Hf)GeTe$_{4}$ were screened out from database of Atomwork as a candidate for pressure-induced superconductivity due to their narrow band gap and high density of state near the Fermi level. The (Zr,Hf)GeTe$_{4}$ samples were synthesized in single crystal and then the compositional ratio, crystal structures, and valence states were investigated via energy dispersive spectrometry, single crystal X-ray diffraction, and X-ray photoelectron spectroscopy, respectively. The pressure-induced superconductivity in both crystals were first time reported by using a diamond anvil cell with a boron-doped diamond electrode and an undoped diamond insulating layer. The maximum superconducting transition temperatures of ZrGeTe$_{4}$ and HfGeTe$_{4}$ were 6.5 K under 57 GPa and 6.6 K under 60 GPa, respectively.

cond-mat.supr-con↗

arXiv2020

Machine Learning Guided Discovery of Gigantic Magnetocaloric Effect in HoB$_{2}$ Near Hydrogen Liquefaction Temperature

Magnetic refrigeration exploits the magnetocaloric effect which is the entropy change upon application and removal of magnetic fields in materials, providing an alternate path for refrigeration other than the conventional gas cycles. While intensive research has uncovered a vast number of magnetic materials which exhibits large magnetocaloric effect, these properties for a large number of compounds still remain unknown. To explore new functional materials in this unknown space, machine learning is used as a guide for selecting materials which could exhibit large magnetocaloric effect. By this approach, HoB$_{2}$ is singled out, synthesized and its magnetocaloric properties are evaluated, leading to the experimental discovery of gigantic magnetic entropy change 40.1 J kg$^{-1}$ K$^{-1}$ (0.35 J cm$^{-3}$ K$^{-1}$) for a field change of 5 T in the vicinity of a ferromagnetic second-order phase transition with a Curie temperature of 15 K. This is the highest value reported so far, to our knowledge, near the hydrogen liquefaction temperature thus it is a highly suitable material for hydrogen liquefaction and low temperature magnetic cooling applications.

cond-mat.mtrl-sci↗

arXiv2019

Leveraging Legacy Data to Accelerate Materials Design via Preference Learning

Machine learning applications in materials science are often hampered by shortage of experimental data. Integration with legacy data from past experiments is a viable way to solve the problem, but complex calibration is often necessary to use the data obtained under different conditions. In this paper, we present a novel calibration-free strategy to enhance the performance of Bayesian optimization with preference learning. The entire learning process is solely based on pairwise comparison of quantities (i.e., higher or lower) in the same dataset, and experimental design can be done without comparing quantities in different datasets. We demonstrate that Bayesian optimization is significantly enhanced via addition of legacy data for organic molecules and inorganic solid-state materials.

cond-mat.mtrl-sci↗

arXiv2019

Pressure-induced superconductivity in SnSb2Te4

We report the discovery of a new superconductor from phase change materials SnSb2Te4. Single crystals of SnSb2Te4 were grown using a conventional melting-growth method. The sample resistance under pressure was measured using an originally designed diamond anvil cell with boron-doped diamond electrodes. The pressure dependence of the resistance has been measured up to 32.6 GPa. The superconducting transition of SnSb2Te4 appeared at 2.1 K(Tconset) under 8.1 GPa, which was further increased with applied pressure to a maximum onset transition temperature 7.4K under 32.6 GPa.

cond-mat.mtrl-sci↗

arXiv2019

Bayesian optimization of chemical composition: a comprehensive framework and its application to $R$Fe$_{12}$-type magnet compounds

We propose a framework for optimization of the chemical composition of multinary compounds with the aid of machine learning. The scheme is based on first-principles calculation using the Korringa-Kohn-Rostoker method and the coherent potential approximation (KKR-CPA). We introduce a method for integrating datasets to reduce systematic errors in a dataset, where the data are corrected using a smaller and more accurate dataset. We apply this method to values of the formation energy calculated by KKR-CPA for nonstoichiometric systems to improve them using a small dataset for stoichiometric systems obtained by the projector-augmented-wave (PAW) method. We apply our framework to optimization of $R$Fe$_{12}$-type magnet compounds (R$_{1-α}$Z$_α$)(Fe$_{1-β}$Co$_β$)$_{12-γ}$Ti$_γ$, and benchmark the efficiency in determination of the optimal choice of elements (R and Z) and ratio ($α$, $β$ and $γ$) with respect to magnetization, Curie temperature and formation energy. We find that the optimization efficiency depends on descriptors significantly. The variable $β$, $γ$ and the number of electrons from the R and Z elements per cell are important in improving the efficiency. When the descriptor is appropriately chosen, the Bayesian optimization becomes much more efficient than random sampling.

cond-mat.mtrl-sci↗

arXiv2019

Data-driven Exploration of Pressure-Induced Superconductivity in AgIn$_{5}$Se$_{8}$

Candidates compounds for new thermoelectric and superconducting materials, which have narrow band gap and flat bands near band edges, were exhaustively searched by a high-throughput first-principles calculation from an inorganic materials database named AtomWork. We focused on AgIn$_{5}$Se$_{8}$ which has high density of state near the Fermi level. AgIn$_{5}$Se$_{8}$ was successfully synthesized as single crystals using a melt and slow cooling method. The single-crystal X-ray diffraction analysis revealed the obtained crystal is high quality without deficiencies. The valence states in AgIn$_{5}$Se$_{8}$ were determined to be Ag1+, In3+ and Se2- in accordance with a formal charge by the core level X-ray photoelectron spectroscopy analysis. The electrical resistance was evaluated under high pressure using a diamond anvil cell with boron-doped diamond electrodes. Although the sample was insulator with a resistance of above 40 MΩ at ambient pressure, the resistance markedly decreased with increase of the pressure, and a pressure-induced superconducting transition was discovered at 3.4 K under 52.5 GPa. The transition temperature increased up to 3.7 K under further pressure of 74.0 GPa.

cond-mat.supr-con↗

arXiv2018

Data-driven Exploration of New Pressure-induced Superconductivity in PbBi$_2$Te$_4$ with Two Transition Temperatures

Candidates compounds for new thermoelectric and superconducting materials, which have narrow band gap and flat bands near band edges, were exhaustively searched by the high-throughput first-principles calculation from an inorganic materials database named AtomWork. We focused on PbBi$_2$Te$_4$ which has the similar electronic band structure and the same crystal structure with those of a pressure-induced superconductor SnBi2Se4 explored by the same data-driven approach. The PbBi$_2$Te$_4$ was successfully synthesized as single crystals using a melt and slow cooling method. The core level X-ray photoelectron spectroscopy analysis revealed Pb2+, Bi3+ and Te2- valence states in PbBi$_2$Te$_4$. The thermoelectric properties of the PbBi$_2$Te$_4$ sample were measured at ambient pressure and the electrical resistivity was also evaluated under high pressure using a diamond anvil cell with boron-doped diamond electrodes. The resistivity decreased with increase of the pressure, and two pressure-induced superconducting transitions were discovered at 3.4 K under 13.3 GPa and at 8.4 K under 21.7 GPa. The data-driven approach shows promising power to accelerate the discovery of new thermoelectric and superconducting materials.

cond-mat.supr-con↗

arXiv2018

Two Pressure-induced Superconducting Transitions in SnBi$_2$Se$_4$ Explored by Data-driven Materials Search: New Approach to Develop Novel Functional Materials Including Thermoelectric and Superconducting Materials

Candidates for new thermoelectric and superconducting materials, which have narrow band gap and flat bands near band edges, were searched by the high-throughput first-principles calculation from an inorganic materials database. The synthesized SnBi$_2$Se$_4$ among the target compounds showed a narrow band gap of 354 meV, and a thermal conductivity of 1 W/Km at ambient pressure. The sample SnBi$_2$Se$_4$ showed a metal-insulator transition at 11.1 GPa, as predicted by a theoretical estimation. Furthermore, the two pressure-induced superconducting transitions were discovered at under 20.2 GPa and 47.3 GPa. The data-driven search is a promising approach to discover new functional materials.

cond-mat.supr-con↗

arXiv2018

Stability Engineering of Halide Perovskite via Machine Learning

Perovskite stability is of the core importance and difficulty in current research and application of perovskite solar cells. Nevertheless, over the past century, the formability and stability of perovskite still relied on simplified factor based on human knowledge, such as the commonly used tolerance factor t. Combining machine learning (ML) with first-principles density functional calculations, we proposed a strategy to firstly calculate the decomposition energies, considered to be closely related to thermodynamic stability, of 354 kinds halide perovskites, establish the machine learning relationship between decomposition energy and compositional ionic radius and investigate the stabilities of 14,190 halide double perovskites. The ML-predicted results enable us to rediscover a series of stable rare earth metal halide perovskites (up to ~1000 kinds), indicating the generalization of this model and further provide elemental and concentration suggestion for improving the stability of mixed perovskite.

cond-mat.mtrl-sci↗

arXiv2017

New Insight into the Ground State of FePc: A Diffusion Monte Carlo Study

We have applied DMC to evaluate relative stability of the possible electronic configurations of an isolated FePc under $D_{4h}$ symmetry, considering some fixed nodes generated from different methods. They predict $A_{2g}$ ground state consistently, supporting preceding DFT studies, with confidence overcoming the ambiguity about exchange-correlation (XC) functionals. By comparing DMC with several XC, we clarified the importance of the short range exchange to describe the relative stability. We examined why the predicted $A_{2g}$ is excluded from possible ground states in the recent ligand field based model. Simplified assumptions made in the superposition model are identified to give unreasonably less energy gain for $A_{2g}$ when compared with the reality. The state is found to have possible reasons for the stabilization, reducing the occupations from an unstable anti-bonding orbital, avoiding double occupation of a spatially localized orbital, and gaining exchange energy by putting a triplet spin pair in degenerate orbitals.

physics.chem-ph↗

arXiv2016

Designing nanostructures for interfacial phonon transport via Bayesian optimization

We demonstrate optimization of thermal conductance across nanostructures by developing a method combining atomistic Green's function and Bayesian optimization. With an aim to minimize and maximize the interfacial thermal conductance (ITC) across Si-Si and Si-Ge interfaces by means of Si/Ge composite interfacial structure, the method identifies the optimal structures from calculations of only a few percent of the entire candidates (over 60,000 structures). The obtained optimal interfacial structures are non-intuitive and impacting: the minimum-ITC structure is an aperiodic superlattice that realizes 50% reduction from the best periodic superlattice. The physical mechanism of the minimum ITC can be understood in terms of crossover of the two effects on phonon transport: as the layer thickness in superlattice increases, the impact of Fabry-Pérot interference increases, and the rate of reflection at the layer-interfaces decreases. Aperiodic superlattice with spatial variation in the layer thickness has a degree of freedom to realize optimal balance between the above two competing mechanism. Furthermore, aperiodicity breaks the constructive phonon interference between the interfaces inhibiting the coherent phonon transport. The present work shows the effectiveness and advantage of material informatics in designing nanostructures to control heat conduction, which can be extended to other interfacial structures.

cond-mat.mtrl-sci↗

arXiv2013

Electronic Structures of N-doped Graphene with Native Point Defects

Nitrogen doping in graphene has important implications in graphene-based devices and catalysts. We have performed the density functional theory calculations to study the electronic structures of N-doped graphene with vacancies and Stone-Wales defect. Our results show that monovacancies in graphene act as hole dopants and that two substitutional N dopants are needed to compensate for the hole introduced by a monovacancy. On the other hand, divacancy does not produce any free carriers. Interestingly, a single N dopant at divacancy acts as an acceptor rather than a donor. The interference between native point defect and N dopant strongly modifies the role of N doping regarding the free carrier production in the bulk pi bands. For some of the defects and N dopant-defect complexes, localized defect pi states are partially occupied. Discussion on the possibility of spin polarization in such cases is given. We also present qualitative arguments on the electronic structures based on the local bond picture. We have analyzed the 1s-related x-ray photoemission and adsorption spectroscopy spectra of N dopants at vacancies and Stone-Wales defect in connection with the experimental ones. We also discuss characteristic scanning tunneling microscope (STM) images originating from the electronic and structural modifications by the N dopant-defect complexes. STM imaging for small negative bias voltage will provide important information about possible active sites for oxygen reduction reaction.

cond-mat.mtrl-sci↗