We have determined the full magnetic dispersion relations of multiferroic ${\mathrm{BiFeO}}_{3}$. In particular, two excitation gaps originating from magnetic anisotropies have been clearly observed. The direct observation of the gaps enables us to accurately determine the Dzyaloshinskii-Moriya (DM) interaction and the single ion anisotropy. The DM interaction supports a sizable magnetoelectric coupling in this compound.

10.1103/physrevlett.109.067205

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Citations (93)

Superconductivity above 50 K in LnFeAsO_1-y (Ln = Nd, Sm, Gd, Tb, and Dy) Synthesized by High-Pressure Technique

Journal of the Physical Society of Japan (2009)

Kiichi Miyazawa Kunihiro Kihou Parasharam M. Shirage Chul‐Ho Lee T. Ito

We have succeeded in synthesizing single-phase polycrystalline samples of oxygen-deficient oxypnictide superconductors, Ln FeAsO 1- y ( Ln : lanthanide elements) with Ln = La, Ce, Pr, Nd, Sm, Gd, Tb, and Dy using high-pressure technique. It is found out that the synthesis pressure is a key parameter for synthesizing samples, in particular for the heavier Ln 's, such as Tb and Dy. The lattice parameters systematically decrease with the atomic number of Ln , reflecting the shrinkage of Ln ionic radius. For the lighter Ln 's (La, Ce, Pr, Nd), T c increases monotonously with decreasing the lattice parameters from 26 K for Ln = La to 54 K for Ln = Nd, then stays at the constant value around 53 K for the heavier counterpart (Nd, Sm, Gd, Tb, and Dy). The results suggest the intimate relationship between the crystal structural parameters and the superconductivity, as well as the possible existence of the inherent maximum T c , which is located around 50 K in the Ln FeAsO based materials.

Ionic radius

Lattice constant

10.1143/jpsj.78.034712

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Citations (103)

CATGNN: Cost-Efficient and Scalable Distributed Training for Graph Neural Networks

arXiv (Cornell University) (2024)

Xin Huang Weipeng Zhuo Minh Vuong Shiju Li Jongryool Kim

Graph neural networks have been shown successful in recent years. While different GNN architectures and training systems have been developed, GNN training on large-scale real-world graphs still remains challenging. Existing distributed systems load the entire graph in memory for graph partitioning, requiring a huge memory space to process large graphs and thus hindering GNN training on such large graphs using commodity workstations. In this paper, we propose CATGNN, a cost-efficient and scalable distributed GNN training system which focuses on scaling GNN training to billion-scale or larger graphs under limited computational resources. Among other features, it takes a stream of edges as input, instead of loading the entire graph in memory, for partitioning. We also propose a novel streaming partitioning algorithm named SPRING for distributed GNN training. We verify the correctness and effectiveness of CATGNN with SPRING on 16 open datasets. In particular, we demonstrate that CATGNN can handle the largest publicly available dataset with limited memory, which would have been infeasible without increasing the memory space. SPRING also outperforms state-of-the-art partitioning algorithms significantly, with a 50% reduction in replication factor on average.

10.48550/arxiv.2404.02300

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Citations (1)

Incommensurate Spin Fluctuations in Hole-Overdoped SuperconductorKFe2As2

Physical Review Letters (2011)

Chul‐Ho Lee Kunihiro Kihou H. Kawano‐Furukawa Taku Saito Akira Iyo

A neutron scattering study of heavily hole-overdoped superconducting ${\mathrm{KFe}}_{2}{\mathrm{As}}_{2}$ revealed a well-defined low-energy incommensurate spin fluctuation at [$\ensuremath{\pi}(1\ifmmode\pm\else\textpm\fi{}2\ensuremath{\delta}),0$] with $\ensuremath{\delta}=0.16$. The incommensurate structure differs from the previously observed commensurate peaks in electron-doped $A{\mathrm{Fe}}_{2}{\mathrm{As}}_{2}$ ($A=\mathrm{Ba}$, Ca, or Sr) at low energies. The direction of the peak splitting is perpendicular to that observed in $\mathrm{Fe}(\mathrm{Te},\mathrm{Se})$ or in $\mathrm{Ba}(\mathrm{Fe},\mathrm{Co}{)}_{2}{\mathrm{As}}_{2}$ at high energies. A band structure calculation suggests interband scattering between bands around the $\ensuremath{\Gamma}$ and $X$ points as an origin of this incommensurate peak. The perpendicular direction of the peak splitting can be understood within the framework of multiorbital band structure. The results suggest that spin fluctuation is more robust in hole-doped than in electron-doped samples, which can be responsible for the appearance of superconductivity in the heavily hole-doped samples.

10.1103/physrevlett.106.067003

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Citations (79)

Thermodynamic Study of Nodal Structure and Multiband Superconductivity of KFe₂As₂

Journal of the Physical Society of Japan (2013)

Shunichiro Kittaka Yuya Aoki Naoki Kase Toshiro Sakakibara Taku Saito

The temperature, field, and field-orientation dependences of the electronic specific heat Ce of the ironpnictide superconductor KFe2As2 have been investigated. Thermodynamic evidence of the presence of line nodes is obtained from the T and $\sqrt{H}$ linear dependences of Ce/T in the low-T and low-H region. Under a magnetic field rotated within the tetragonal ab plane, a fourfold oscillation is observed in Ce with a sign change at 0.08Tc. On the basis of the Doppler-shift analysis, the observed Ce minima in H // [100] at low T indicate the presence of line nodes somewhere on the Fermi surface where the Fermi velocity is parallel to the [100] direction; this is consistent with the octet-line-node scenario proposed recently by a photoemission experiment. In addition, the low-T Ce/T exhibits an unusual upturn on cooling at moderate fields only for H // ab, which is understood in terms of the strong Pauli paramagnetic effect on multiband superconductivity.

Tetragonal crystal system

Brillouin zone

Line (geometry)

10.7566/jpsj.83.013704

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Citations (26)

Low-Frequency Noise Characterizations of Back-gate ZnO Nanorod Field-Effect Transistor Structure

IEICE technical report. Electron devices (2007)

Jungil Lee Byung Yong Yu Chul‐Ho Lee Gyu‐Chul Yi Gyu‐Tae Kim

Nanorod

Source

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Carbon Emissions and the Search for Renewable Energy Technology: Information and Communication Technology (ICT) Firms’ Environmental Responsibility

Production and Operations Management (2024)

Hyun‐Soo Kim Hyun Ju Jung Chul‐Ho Lee

The literature in sustainability has emphasized external pressures as a main driver of firms’ environmental responsibility. However, under similar external pressures, some firms search for environmental technology, while others do not. By focusing on information and communication technology (ICT) firms, we try to answer the question of when firms are motivated to search for renewable energy technology. Drawing on the framework of the behavioral theory of the firm, we propose that a mismatch between ICT firms’ CO 2 emissions performance and their aspiration to a certain level of emissions induce firms to evaluate their environmental performance status—whether they are aligned well with environmental requirements and their peer firms—and their technology status—whether they possess sufficient technologies to reduce emissions—which in turn affects their search for renewable energy technology. We corroborate our hypotheses using data on CO 2 emissions and renewable energy patents of U.S. ICT firms from 2010 to 2018. When we compare two groups of firms—one group whose emissions performance is poor and the other group whose emissions performance is good compared to their own past emissions—we find that the former is more likely to search for renewable energy technology compared to the latter. When we focus on each of the two groups, we find that firms decrease their search for renewable energy technology as the degree of poor emissions performance exacerbates (firms’ emissions increase above aspiration) or the degree of good emissions performance increases (firms’ emissions decrease below aspiration). Our findings have implications for public policy as well as firms’ environmentally sustainable operations.

Green Computing

10.1177/10591478241240126

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Static and Dynamical Incommensurate Spin Correlations in High-Tc Cuprates of La2−xSrxCuO4+y

Springer series in solid-state sciences (1999)

K. Yamada R. J. Birgeneau Y. Endoh T. Fukase M. Greven

10.1007/978-3-642-60041-8_17

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Possible Multiple Gap Superconductivity with Line Nodes in Heavily Hole-Doped Superconductor KFe₂As₂ Studied by ⁷⁵As Nuclear Quadrupole Resonance and Specific Heat

Journal of the Physical Society of Japan (2009)

Hideto Fukazawa Yuji Yamada Kenji Kondo Taku Saito Yoh Kohori

We report the 75As nuclear quadrupole resonance (NQR) and specific heat measurements of the heavily hole-doped superconductor KFe2As2 (Tc = 3.5 K). The spin-lattice relaxation rate 1/T1 in the superconducting state exhibits quite gradual temperature dependence with no coherence peak below Tc. The quasi-particle specific heat C_QP/T shows small specific heat jump which is about 30% of electronic specific heat coefficient just below Tc. In addition, it suggests the existence of low-energy quasi-particle excitation at the lowest measurement temperature T = 0.4 K \simeq Tc/10. These temperature dependence of 1/T1 and C_QP/T can be explained by multiple nodal superconducting gap scenario rather than multiple fully-gapped s_\pm-wave one within simple gap analysis.

Specific heat

10.1143/jpsj.78.083712

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Citations (134)

Motivation for firm ECSR: Firm’s CO2 emissions and Search for Renewable Energy Technology

Academy of Management Proceedings (2021)

Hyun‐Soo Kim Hyun Ju Jung Chul‐Ho Lee

Research in environmental corporate social responsibility has mainly focused on external pressures as determinants of firms to engage in eco-friendly behaviors. However, firms are heterogeneous in executing environmental behaviors, which cannot be explained solely by external factors. What motivates firms to engage in proactive environmental behavior, in particular, searching for environmental technology? This study tries to answer this question using the difference between the firm’s CO2 emissions and their aspiration levels, and examines how this gap affects a firm’s renewable energy technology search behavior. By testing our hypotheses within renewable energy technology search behavior of U.S. Fortune 500 information, communication, and technology firms from 2010 to 2018, we find that firms are more likely to search for renewable energy technology as the gap between firms’ CO2 emissions and aspiration levels widens. When a firm’s CO2 emissions is greater than aspirations, the impact of social gap on searching behavior is greater than the impact of historical gap. On the contrary, when a firm’s CO2 emissions is less than aspirations, the impact of historical gap on searching behavior is greater than the impact of social gap.

10.5465/ambpp.2021.14144abstract

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