Given the multitude of conditions that must be optimized in synthesis routes, chemical synthesis remains a complex and multidimensional challenge. The rapid development of computational guidelines and machine learning (ML) techniques has brought exciting hope to this dilemma. A new study published in the journal National Science Review highlights the advancement of computationally guided and ML-assisted approaches in inorganic material synthesis.

On the eve of Holocaust Remembrance Day, the Center for the Study of Contemporary European Jewry and the Irwin Cotler Institute for Democracy, Human Rights and Justice, both at Tel Aviv University, publish the Annual Antisemitism Worldwide Report, which focuses on 2024. The 160-pages Report was prepared by 11 researchers. The annual study has been published for a quarter of a century and is considered the most cited and authoritative document of its kind.

In a paper published in National Science Review, researchers report on the discovery of a novel octupole topological insulating phase, protected by a 3D momentum-space nonsymmorphic group, within the framework of the Brillouin 3D real projective space. The 3D higher-order topological insulator exhibits the coexistence of symmetry-protected and surface-obstructed topological phases. The existence of the octupole insulating phase is confirmed through the corner-state impedance peak in the topological circuit.

A new study offers a framework to estimate the sample size required for microbiome association studies based on expected effect sizes and analysis methods. By utilizing two large datasets involving around 10,000 individuals, the researchers found that 500 individuals may be sufficient to detect associations targeting larger effect sizes or metabolic diseases closely related to lifestyle, while thousands of samples may be needed for smaller effect sizes or multifactorial complex diseases such as psychiatric and autoimmune conditions. This framework guides future studies in human microbiome research.