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Corrigendum: Design and Application of a Gas Diffusion Electrode (GDE) Cell for Operando and In Situ Studies
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Legal and Operational Aspects of Compliance with Scientific Integrity
Get PDFEnsuring scientific integrity is of utmost importance in the research community, as it forms the foundation of reliable and credible scientific knowledge. Compliance with scientific integrity involves adhering to ethical principles, research standards, and legal regulations that promote transparency, honesty, and accountability. Fabrication, falsification, and plagiarism are common forms of research misconduct that undermine the credibility and trustworthiness of scientific findings. Institutions must establish clear policies and procedures to address and prevent such misconduct, including mechanisms for reporting, investigation, and appropriate disciplinary actions. This article examines the legal and operational aspects related to compliance with scientific integrity, highlighting key considerations and best practices in this critical domain
The Multiple Challenges of Handling Scientific Integrity in the Swiss Higher Education System
Get PDFScientific integrity is the most important aspect that higher education institutions have to take care of, as it conveys credibility and acceptance of science to the public. Although science has a very powerful built-in self-regulation process for detecting and correcting scientific misconduct, there is a need for clear guidelines that have to be adapted on regular intervals to the rapidly changing world caused by scientific developments themselves. Outlined here are recent advances in how Switzerland increases awareness and transparency of scientific misconduct and how it handles cases of misconduct to improve the quality of science
Solving Intractable Chemical Problems by Tensor Decomposition
Get PDFMany complex chemical problems encoded in terms of physics-based models become computationally intractable for traditional numerical approaches due to their unfavorable scaling with increasing molecular size. Tensor decomposition techniques can overcome such challenges by decomposing unattainably large numerical representations of chemical problems into smaller, tractable ones. In the first two decades of this century, algorithms based on such tensor factorizations have become state-of-the-art methods in various branches of computational chemistry, ranging from molecular quantum dynamics to electronic structure theory and machine learning. Here, we consider the role that tensor decomposition schemes have played in expanding the scope of computational chemistry. We relate some of the most prominent methods to their common underlying tensor network formalisms, providing a unified perspective on leading tensor-based approaches in chemistry and materials science