After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, MIT researchers organized them into a “periodic table of machine learning” that can help scientists combine elements of different methods to improve algorithms or create new ones.

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.