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Abstract In this article, we propose a query-and-learn active learning approach combined with first-principles calculations to rapidly search for potentially stable crystal structure via elemental substitution, to clarify their stabilization mechanism, and integrate this approach to SmFe$$_{12}$$ 12 -based compounds with ThMn$$_{12}$$ 12 structure, which exhibits prominent magnetic properties. The proposed method aims to (1) accurately estimate formation energies with limited first-principles calculation data, (2) visually monitor the progress of the structure search process, (3) extract correlations between structures and formation energies, and (4) recommend the most beneficial candidates of SmFe$$_{12}$$ 12 -substituted structures for the subsequent first-principles calculations. The structures of SmFe$$_{12-\upalpha -\upbeta }\mathsf {X}_{\upalpha }\mathsf {Y}_{\upbeta }$$ 12 - α - β X α Y β before optimization are prepared by substituting $$\mathsf {X}, \mathsf {Y}$$ X , Y elements—Mo, Zn, Co, Cu, Ti, Al, Ga—in the region of $$\upalpha +\upbeta α + β < 4 into iron sites of the original SmFe$$_{12}$$ 12 structures. Using the optimized structures and formation energies obtained from the first-principles calculations after each active learning cycle, we construct an embedded two-dimensional space to rationally visualize the set of all the calculated and not-yet-calculated structures for monitoring the progress of the search. Our machine learning model with an embedding representation attained a prediction error for the formation energy of $$1.25\times 10^{-2}$$ 1.25 × 10 - 2 (eV/atom) and required only one-sixth of the training data compared to other learning methods. Moreover, the time required to recall most potentially stable structures was nearly four times faster than the random search. The formation energy landscape visualized using the embedding representation revealed that the substitutions of Al and Ga have the highest potential to stabilize the SmFe$$_{12}$$ 12 structure. In particular, SmFe$$_{9}$$ 9 [Al/Ga]$$_{2}$$ 2 Ti showed the highest stability among the investigated structures. Finally, by quantitatively measuring the change in the structures before and after optimization using OFM descriptors, the correlations between the coordination number of substitution sites and the resulting formation energy are revealed. The negative-formation-energy-family SmFe$$_{12-\upalpha -\upbeta }$$ 12 - α - β [Al/Ga]$$_{\upalpha }\mathsf {Y}_{\upbeta }$$ α Y β structures show a common trend of increasing coordination number at substituted sites, whereas structures with positive formation energy show a corresponding decreasing trend. Impact statement Seeking the next generation of high-performance magnets is a crucial demand for replacing the widely accepted Nd-Fe-B magnets developed in the middle 80s. The iron-rich compounds with the original tetragonal ThMn12 structure appear as the most potential candidates except for the hard synthesizing it in nature due to its high energy of formation. Stabilization for this material system is expected by substituting new elements, but the vast number of possible structures makes the exploration difficult even for theoretical calculations. This article proposes an integration of first-principles calculations and explainable active learning to efficiently explore the crystal structure space of this material system. In particular, the explored crystal structure space can be rationally visualized, on which the relationship between substitution elements, substitution sites, and crystal structure stabilization can be intuitively interpreted.

As interdisciplinary science is flourishing because of materials informatics and additional factors; a systematic way is required for expressing knowledge and facilitating communication between scientists in various fields. A function decomposition tree is such a representation, but domain scientists face difficulty in constructing it. Thus, this study cites the general problems encountered by beginners in generating function decomposition trees and proposes a new function decomposition representation method based on a causality-first perspective for resolution of these problems. The causality-first decomposition tree was obtained from a workflow expressed according to the processing sequence. Moreover, we developed a program that performed automatic conversion using the features of the causality-first decomposition trees. The proposed method was applied to materials informatics to demonstrate the systematic representation of expert knowledge and its usefullness.

To study the temperature dependence of magnetic properties of permanent magnets, methods of treating the thermal fluctuation causing the thermal activation phenomena must be established. To study finite-temperature properties quantitatively, we need atomistic energy information to calculate the canonical distribution. In the present review, we report our recent studies on the thermal properties of the Nd2Fe14B magnet and the methods of studying them. We first propose an atomistic Hamiltonian and show various thermodynamic properties, for example, the temperature dependences of the magnetization showing a spin reorientation transition, the magnetic anisotropy energy, the domain wall profiles, the anisotropy of the exchange stiffness constant, and the spectrum of ferromagnetic resonance. The effects of the dipole–dipole interaction (DDI) in large grains are also presented. In addition to these equilibrium properties, the temperature dependence of the coercivity of a single grain was studied using the stochastic Landau-Lifshitz-Gilbert equation and also by the analysis of the free energy landscape, which was obtained by Monte Carlo simulation. The upper limit of coercivity at room temperature was found to be about 3 T at room temperature. The coercivity of a polycrystalline magnet, that is, an ensemble of interactinve grains, is expected to be reduced further by the effects of the grain boundary phase, which is also studied. Surface nucleation is a key ingredient in the domain wall depinning process. Finally, we study the effect of DDI among grains and also discuss the distribution of properties of grains from the viewpoint of first-order reversal curve.

First-principles calculation based on density functional theory is a powerful tool for understanding and designing magnetic materials. It enables us to quantitatively describe magnetic properties and structural stability, although further methodological developments for the treatment of strongly correlated 4f electrons and finite-temperature magnetism are needed. Here, we review recent developments of computational schemes for rare-earth magnet compounds, and summarize our theoretical studies on Nd2Fe14B and RFe12-type compounds. Effects of chemical substitution and interstitial dopants are clarified. We also discuss how data-driven approaches are used for studying multinary systems. Chemical composition can be optimized with fewer trials by the Bayesian optimization. We also present a data-assimilation method for predicting finite-temperature magnetization in wide composition space by integrating computational and experimental data., Graphical abstract

We propose a scheme for investigating the correlation and trade-off among target variables using a multi-objective Bayesian optimization (MBO). We discuss the features of the Pareto front (PF) of ThMn12-type compounds, (R, Z)(Fe,Co,Ti)12 (R = Y, Nd, Sm; Z = Zr, Dy) in terms of magne- tization, Curie temperature, and a price index by using data from first-principles calculations, and we extract the trade-off relations from the analysis. We show that the trade-off relationships can be used to determine changes in the controllable variables by using partial least squares regression. For example, the tendency toward low cost and high Curie temperature is related to the reduction in Dy and increase in Co. We also discuss the efficiency of MBO as a practical scheme to obtain the features of the PF. We show that MBO can offer an approximated set for the PF even when obtaining the true PF is difficult., 6 pages, 8 figures

We have developed an open-source software called CrySPY, which is a crystal structure prediction tool written in Python 3, and runs on Unix/Linux platforms. CrySPY enables anyone to easily perform ...

Measuring the similarity between materials is essential for estimating their properties and revealing the associated physical mechanisms. However, current methods for measuring the similarity between materials rely on theoretically derived descriptors and parameters fitted from experimental or computational data, which are often insufficient and biased. Furthermore, outliers and data generated by multiple mechanisms are usually included in the dataset, making the data-driven approach challenging and mathematically complicated. To overcome such issues, we apply the Dempster–Shafer theory to develop an evidential regression-based similarity measurement (eRSM) method, which can rationally transform data into evidence. It then combines such evidence to conclude the similarities between materials, considering their physical properties. To evaluate the eRSM, we used two material datasets, including 3[Formula: see text] transition metal–4[Formula: see text] rare-earth binary and quaternary high-entropy alloys with target properties, Curie temperature, and magnetization. Based on the information obtained on the similarities between the materials, a clustering technique is applied to learn the cluster structures of the materials that facilitate the interpretation of the mechanism. The unsupervised learning experiments demonstrate that the obtained similarities are applicable to detect anomalies and appropriately identify groups of materials whose properties correlate differently with their compositions. Furthermore, significant improvements in the accuracies of the predictions for the Curie temperature and magnetization of the quaternary alloys are obtained by introducing the similarities, with the reduction in mean absolute errors of 36% and 18%, respectively. The results show that the eRSM can adequately measure the similarities and dissimilarities between materials in these datasets with respect to mechanisms of the target properties.

There is no proven medical therapy to inhibit the progression of abdominal aortic aneurysm (AAA) in the clinical setting. To develop a novel therapeutic approach for the treatment of AAA, we focused on vaccination targeting Ang II (angiotensin II) and assessed the effect of an Ang II peptide vaccine on the progression of AAA using a rat model. Ang II peptide was conjugated with KLH (keyhole limpet hemocyanin) carrier protein to induce a sufficient immune response. Male rats were subcutaneously immunized with Ang II–KLH with an adjuvant on days 0, 14, and 28. Aortic dilatation was induced by intraluminal incubation with elastase on day 35. Treatment with Ang II vaccine successfully induced the production of a high titer of anti-Ang II antibodies. Immunization with Ang II vaccine resulted in a significant reduction in expansion of the aortic diameter compared with control rats, without a blood pressure–lowering effect. Four weeks after operation, the increase in Ang II in the aneurysm wall was significantly inhibited by treatment with Ang II vaccine. Inhibition of Ang II action led to suppression of the inflammatory response in the AAA wall through attenuation of the NFκB (nuclear factor kappa B) and c-jun N-terminal kinase signaling cascades. Treatment with Ang II vaccine inhibited accumulation of macrophages in the AAA wall. In addition, expression of TNF-α (tumor necrosis factor alpha) and activation of MMP (matrix metalloproteinase)-2 and MMP-9 were also inhibited by treatment with Ang II vaccine, resulting in protection against the destruction of elastic fibers. This vaccine therapy could become a potent therapeutic option to treat patients with AAA.

The microscopic mechanism of coercivity at finite temperature is a crucial issue for permanent magnets. Here we present the temperature dependence of the coercivity of an atomistic spin model for the highest-performance magnet Nd2Fe14B. For quantitative analysis of the magnetization reversal with thermal fluctuations, we focus on the free energy landscape as a function of the magnetization. The free energy is calculated by the replica-exchange Wang–Landau method. This approach allows us to address a slow nucleation problem, i.e., thermal activation effects, in the magnetization reversal. We concretely observed that the thermal fluctuations lead to a downward convexity in the coercivity concerning the temperature. Additionally, through analyzing the microscopic process of the thermal activation (nucleation), we discover the activation volume is insensitive to a magnetic field around the coercivity. The insensitivity explains the linear reduction of the free energy barrier by the magnetic field in the nucleation process.

The structural stability of CeFe$_{12}$ is investigated by using first-principles calculation. The formation energies of CeFe$_{12}$ relative to the Ce$_{2}$Fe$_{17}$ + bcc-Fe phase and to the CeFe$_{2}$ + bcc-Fe phase are calculated with the assumptions of trivalency and tetravalency for Ce. Those values are compared with corresponding results in $R$Fe$_{12}$ for $R=$ Nd, Sm, and Zr. Our results suggest that the tetravalent Ce is a promising stabilizer of the ThMn$_{12}$ structure. We also show that the stabilizing effect of an element depends as much on the valency as on the size of the $R$ element by investigating $R$Fe$_{12}$ where $R$ is assumed to have a hypothetical valency on the basis of first-principles calculation., Comment: 5pages, 4figures

Recent progress in understanding the electronic band topology and emergent topological properties encourage us to reconsider the band structure of well-known materials including elemental substances. Controlling such a band topology by external field is of particular interest from both fundamental and technological viewpoints. Here we report possible signatures of the pressure-induced topological phase transition from a semiconductor to a Weyl semimetal in elemental tellurium probed by transport measurements. Pressure variation of the periods of Shubnikov–de Haas oscillations, as well as oscillation phases, shows an anomaly around the pressure theoretically predicted for topological phase transition. This behavior is consistent with the pressure-induced band deformation and resultant band-crossing effect. Moreover, effective cyclotron mass is reduced toward the critical pressure, potentially reflecting the emergence of massless linear dispersion. The present result paves the way for studying the electronic band topology in well-known compounds and topological phase transition by the external field.

To clarify the detailed molecular mechanisms underlying the development of asthma, we assessed the potential immune effects of prenatal osteoprotegerin (OPG) inhibition in the pathogenesis of asthma. The effects of OPG deficiency on the development of asthma were evaluated using an ovalbumin-induced asthma model in OPG knockout mice. Histological analysis demonstrated that OPG was mainly detected in airway epithelial cells in wild type mice. After ovalbumin sensitization and challenge, accumulation of inflammatory cells, gene expression of T helper 2-related cytokines and mucus hypersecretion in lung tissues were inhibited by OPG deficiency. Importantly, the serum level of IgE was not increased in OPG KO mice after ovalbumin sensitization and challenge. Based on these findings, OPG knockout mice were protected against methacholine-induced airway hyperresponsiveness. OPG expression is thought to be essential for induction of the allergic immune response in asthma.

Background: To establish a method to prevent and manage fatigue caused by psychological and physical stress in young females, early detection factors, such as understanding of fatigue and causes of psychological and physical stress, as well as a review of early management of psychiatric disease, are important. With increasing knowledge regarding the diverse causes of stress, it is important to select biomarkers with consideration of the types of stress burden and mechanisms underlying the development of physical symptoms. The methods used to search for stress characteristics is an issue that needs to be addressed. However, consensus regarding objective assessment methods for impaired mental health is lacking. Methods: We examined the effects of an objective structured clinical examination (OSCE), considered to be a uniform source of psychological and physical stress, on biomarkers of oxidative stress and fatigue in 16 third-year female medical university students (21.3 ± 2.1 years old) in Japan with a normal menstrual cycle. A self-administered questionnaire consisting of Zung’s Self-rating Depression Scale (SDS) and State-Trait Anxiety Inventory (STAI) was used to assess subjective stress. Furthermore, stress-related biomarkers (urinary 8-hydroxy-2ʹ-deoxyguanosine [u-8-OHdG], urinary 5-hydroxytryptamine [u-5-HT], and salivary human herpesvirus-6 [s-HHV-6]) were examined at 1 month, 1 week, and 1 day before, and 1 week after the OSCE. Results: The results indicated that the OSCE did not have effects on u-8-OHdG, a biomarker of oxidative stress. However, u-5-HT and s-HHV-6 were found to be elevated in examinations performed prior to the OSCE. Conclusions: The present findings suggest that u-5-HT and s-HHV-6 levels can be used for objective assessment of mental and physical fatigue in young females, including that produced not only by knowledge regarding an upcoming OSCE, but also by skill and attitude aspects related to that examination.

Abdominal aortic aneurysm (AAA) is considered to be a potent life-threatening disorder in elderly individuals. Although many patients with a small AAA are detected during routine abdominal screening, there is no effective therapeutic option to prevent the progression or regression of AAA in the clinical setting. Recent advances in molecular biology have led to the identification of several important molecules, including microRNA and transcription factor, in the process of AAA formation. Regulation of these factors using nucleic acid drugs is expected to be a novel therapeutic option for AAA. Nucleic acid drugs can bind to target factors, mRNA, microRNA, and transcription factors in a sequence-specific fashion, resulting in a loss of function of the target molecule at the transcriptional or posttranscriptional level. Of note, inhibition of a transcription factor using a decoy strategy effectively suppresses experimental AAA formation, by regulating the expression of several genes associated with the disease progression. This review focuses on recent advances in molecular therapy of using nucleic acid drugs to treat AAA.

Introduction: New treatments to inhibit neointimal formation after percutaneous transluminal angioplasty (PTA) are needed for patients undergoing chronic hemodialysis (HD). We compared the efficacy and safety of AMG0102, a balloon catheter containing nuclear factor κB (NF-κB) decoy oligodeoxynucleotide (ODN) with the PTA balloon catheter (control group) for arteriovenous fistula (AVF) stenosis. Methods: In total, 175 patients (age ≥20 years, undergoing HD, with venous stenosis at the anastomotic region) were registered in this prospective open-label, randomized study. Patients were followed postoperatively for 36 weeks. The duration of primary patency on the targeted venous stenosis site (primary endpoint) was estimated by the Kaplan–Meier method. Results: A lower restenosis risk was observed for the AMG0102 group, but it was not statistically significant (stratified log-rank test P = 0.250, hazard ratio [HR] 0.774; 95% confidence interval [CI]: 0.500–1.198). The median duration of primary patency was 245 days and 172 days in the AMG0102 and control groups, respectively. After stratification based on the status of diabetes complications, the HR was 0.666 (95% CI: 0.366–1.212; P = 0.183) and the median duration of primary patency was prolonged by 108 days in the AMG0102 group with diabetes complications (245 days) compared with the control group (137 days). Adverse event (AE) incidence up to 36 postoperative weeks did not differ between groups. Four device failures occurred in 3 patients (AMG0102 group), but none resulted in AEs. Conclusion: Further modifications to enhance NF-κB decoy ODN uptake and efficacy are necessary to show its clinical utility for AVF stenosis in chronic HD. Keywords: arteriovenous fistula stenosis, balloon catheter, diabetes, hemodialysis, nuclear factor κB, percutaneous transluminal angioplasty

We present spin-wave dispersion in Sm(Fe$_{1-x}$Co$_x$)$_{12}$ calculated based on first-principles. Anisotropy in the lowest branch of the spin-wave dispersion around the $\Gamma$ point is discussed. Spin-waves propagate more easily along $a^*$-axis than along $c^*$-axis, especially in SmFe$_{12}$. We also compare values of the spin-wave stiffness with those obtained from an experiment. The calculated values are in good agreement with the experimental values., Comment: 15 pages, 6 figures

We present a data-driven approach to explore high-entropy alloys (HEAs). To overcome the challenges with numerous element-combination candidates, selecting appropriate descriptors, and the limitations and biased of existing data, we apply the evidence theory to develop a descriptor-free evidence-based recommender system (ERS) for recommending HEAs. The proposed system measures the similarities between element combinations and utilizes it to recommend potential HEAs. To evaluate the ERS, we compare its HEA-recommendation capability with those of matrix-factorization- and supervised-learning-based recommender systems on four widely known data sets, including binary and ternary alloys. The results of experiments using k-fold cross-validation on the data sets show that the ERS outperforms all competitors. Furthermore, the ERS shows excellent extrapolation capabilities in experiments of recommending quaternary and quinary HEAs. We experimentally validate the most strongly recommended Fe-Co-based magnetic HEA, viz. FeCoMnNi, and confirm that it shows a body-centered cubic structure and is stable at high temperatures.