Retraction: Néel Spin-Orbit Torque Driven Antiferromagnetic Resonance in Mn_{2}Au Probed by Time-Domain THz Spectroscopy [Phys. Rev. Lett. 120, 237201 (2018)].

Retraction of DOI: 10.1103/PhysRevLett.120.237201.

Néel Spin-Orbit Torque Driven Antiferromagnetic Resonance in Mn_{2}Au Probed by Time-Domain THz Spectroscopy.

We observe the excitation of collective modes in the terahertz (THz) range driven by the recently discovered Néel spin-orbit torques (NSOTs) in the metallic antiferromagnet Mn_{2}Au. Temperature-dependent THz spectroscopy reveals a strong absorption mode centered near 1 THz, which upon heating from 4 to 450 K softens and loses intensity. A comparison with the estimated eigenmode frequencies implies that the observed mode is an in-plane antiferromagnetic resonance (AFMR). The AFMR absorption strength exceeds those found in antiferromagnetic insulators, driven by the magnetic field of the THz radiation, by 3 orders of magnitude. Based on this and the agreement with our theory modeling, we infer that the driving mechanism for the observed mode is the current-induced NSOT. Here the electric field component of the THz pulse drives an ac current in the metal, which subsequently drives the AFMR. This electric manipulation of the Néel order parameter at high frequencies makes Mn_{2}Au a prime candidate for antiferromagnetic ultrafast memory applications.

[QSAR investigation of acute toxicity of organic compounds during oral administration to mice]. / QSAR-analiz ostroi toksichnosti organicheskikh soedinenii pri peroral'nom vvedenii mysham.

The effect of the structure of organic compounds on the acute toxicity upon oral injection in mice was studied using 2D simplex representation of the molecular structure and Random forest (RF) methods. Satisfactory quantitative structure-activity relationship (QSAR) models were constructed (R2 test = 0,61-0,62). The interpretation of the obtained QSAR models was carried out. The contributions of known toxicophores with established mechanisms of action were calculated in order to confirm the ability of the interpretation approach to correctly rank them relative to other structural fragments. The influence of the molecular surroundings of some toxicophores was analyzed. We analyzed the contributions of other highly ranked fragments from the list of common functional groups and ring systems in order to find new potential toxicophores. The on-line version of the expert system "OCHEM" (https://ochem.eu) and Arithmetic Mean Toxicity (AMT) approach were used for a comparative QSAR study.

Contribution assessment of multiparameter optimization descriptors in CNS penetration.

Assessment of the influence of six physicochemical properties used in the multiparameter optimization (MPO) approach for chemical penetration of the blood-brain barrier was carried out by means of application of logistic regression and multiple linear regression, using a data set of 578 diverse chemicals. It was found that use of an aggregation MPO-score descriptor did not give satisfactory results with central nervous system (CNS)/non-CNS classification. Thus an application of the MPO approach for CNS penetration is ambiguous. An alternative to the MPO approach in this work contains detailed (quantitative) structure-activity relationship analysis using a number of methods (linear discriminant analysis, random forest, support vector machine, Gaussian process). Three properties (molecular weight, number of H-bond donors and octanol-water partition coefficient) yielded optimal categorical models with modest statistical parameters (accuracy 0.730-0.765 for CNS/non-CNS classification). The poor statistics of regression models for the common data set suggested the presence of subsets with different mechanisms of penetrations. Based on graphic comparison of experimental and calculated Cu,b values, subset clusters have satisfactory statistics. The regression models obtained allowed the estimation of descriptor contributions in log Cu,b. This means that medicinal chemists now have a simple additive scheme for at least preliminary quantitative assessment of this important pharmacokinetic parameter.

[Classification models of structure - P-glycoprotein activity of drugs].

Thirty three classification models of substrate specificity of 177 drugs to P-glycoprotein have been created using of the linear discriminant analysis, random forest and support vector machine methods. QSAR modeling was carried out using 2 strategies. The first strategy consisted in search of all possible combinations from 1÷5 descriptors on the basis of 7 most significant molecular descriptors with clear physico-chemical interpretation. In the second case forward selection procedure up to 5 descriptors, starting from the best single descriptor was used. This strategy was applied to a set of 387 DRAGON descriptors. It was found that only one of 33 models has necessary statistical parameters. This model was designed by means of the linear discriminant analysis on the basis of a single descriptor of H-bond (ΣC(ad)). The model has good statistical characteristics as evidenced by results to both internal cross-validation, and external validation with application of 44 new chemicals. This confirms an important role of hydrogen bond in the processes connected with penetration of chemical compounds through a blood-brain barrier.