9 papers · ranked by Valyu relevance
Authors not listed
High-quality data preprocessing is essential for untargeted metabolomics experiments, where increasing dataset scale and complexity demand adaptable, robust, and reproducible software solutions. Modern preprocessing tools must evolve to integrate seamlessly with downstream analysis platforms, ensuring efficient and…
Authors not listed
In the data-driven discovery of high-performance thermoelectric (TE) materials, the lack of high-quality data remains a key bottleneck. Addressing this issue, we introduce the Systematically Verified Thermoelectric (sysTEm) dataset. Leveraging the physical relationships between transport properties, we curated and…
Adarsh Arun, Jana Weber, Zhen Guo, Alexei Lapkin
As the chemical sector looks to decarbonize, one promising solution is the utilization of bio-feedstocks and biowaste to produce functional molecules. There is, therefore, great interest in understanding how and where to integrate these resources within chemical supply chains. To assist such efforts, screening…
Kevin Robben, Christopher Cheatum
We report a comprehensive study of the efficacy of least-squares fitting of multidimensional spectra to generalized Kubo lineshape models and introduce a novel least-squares fitting metric, termed the Scale Invariant Gradient Norm (SIGN), that enables a highly reliable and versatile algorithm. The precision of…
Eftychia Eva Kontou, Axel Walter, Timo Sachsenberg, Tilmann Weber + 5 more
Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for…
Authors not listed
We present TAPAS (Transient Absorption Processing and Analysis Software), an open-source, Python-based graphical platform that covers the entire transient absorption (TA) workflow, from raw data import and preprocessing to visualization, global and target fitting, and statistical evaluation. Users operate TAPAS through…
Keisuke Ozawa
Statistically weighted principal component analysis (wPCA) is widely used to reduce the noise of scanning transmission electron microscopy-energy-dispersive X-ray (STEM-EDX) spectroscopy data. It is beneficial to retain the spatial resolution of observation in each step of the analysis, but the direct application of…
Mahnoor Zulfiqar, Michael R. Crusoe, Birgitta König-Ries, Christoph Steinbeck + 2 more
Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for…
Somesh Mohapatra, Daniel Griffin
Identification and control of impurities play a critical role in chemical process development for drug substance synthesis. Most chemical reactions result in a number of by-products and side-products, along with the intended major product. While chemists can predict many of the main process impurities, it remains…