12 papers · ranked by Valyu relevance
Adarsh Arun, Zhen Guo, Simon Sung, Alexei Lapkin
Automated prediction of reaction impurities can be useful in facilitating rapid early-stage reaction development, synthesis planning and optimization. Existing reaction predictors are catered towards main product prediction, and are often black-box, making it difficult to troubleshoot erroneous outcomes. This work…
Jonathan Fine, Anand Rasjashekar, Gaurav Chopra
We present a deep learning method for identifying all the functional groups of unknown compounds using a combination of FTIR and MS spectra without the use of any database, pre-established rules, procedures, or peak-matching methods. We derive patterns and correlations directly from spectral data representing multiple…
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Acutely toxic substances such as cyanide salts and mercury metal are commonly used in gold mining. Mercury amalgamation in artisanal gold mining is especially problematic and the largest source of mercury pollution on Earth. New strategies are needed that do not rely on cyanide and mercury for gold recovery. To address…
Chonghuan Zhang, Qianyue Zhang, Alexei Lapkin
Biochemical transformations may allow significant improvements in synthetic efficiency of complex functional molecules through reduction in the number of synthetic steps or avoidance of harsh conditions and/or toxic solvents/reactants. Yet, there is a limited access to biochemical reaction data, which reduces the…
Pulan Yu
Associative classification mining (ACM) integrating association rule mining and classification has become a significant tool for knowledge discovery, especially in the chemical domain. Its major advantage is providing high accuracy as well as chemically interpretable models. Additionally, it is able to find…
Dev Punjabi, Yu-Chieh Huang, Laura Holzhauer, Pierre Tremouilhac + 3 more
In this study, we propose a neural network based approach to analyze IR spectra and detect the presence of functional groups. Our neural network architecture is based on the concept of learning split representations. We demonstrate that our method achieves favorable validation performance using the NIST dataset.…
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Iron, the most abundant element on Earth by mass (34.6%), primarily exists as iron minerals due to its inherent reactivity. The study of iron mineral phase transformations under changing environmental conditions remains an important research focus due to its geological, environmental, and industrial significance. Yet…
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Curried functions provide a systematic way of transforming multi-argument functions into nested singleargument functions. This transformation allows partial application and supports many central principles of functional programming. Their extension, called curried 𝑘-ary functions, naturally generalizes the familiar…
Kevin Maik Jablonka, Andrew S. Rosen, Aditi S. Krishnapriyan, Berend Smit
The space of all plausible materials for a given application is so large that it cannot be explored using a brute-force approach. This is, in particular, the case for reticular chemistry which provides materials designers with a practically infinite playground on different length scales. One promising approach to guide…
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Artificial intelligence (AI) is reshaping scientific research by accelerating discovery and enabling the analysis of complex data that traditional methods struggle to handle. This review examines over 310,000 journal articles and patents from the CAS Content Collection (2015–2025), with a focus on, biomedical research…
Yi Luo, Saientan Bag, Orysia Zaremba, Jacopo Andreo + 3 more
Despite rapid progress in the field of metal-organic frameworks (MOFs), the potential of using machine learning (ML) methods to predict MOF synthesis parameters is still untapped. Here, we show how ML can be used for rationalization and acceleration of the MOF discovery process by directly predicting the synthesis…
Julian Ivanov, Alan Lipkus, Haitao Chen, Chris Aultman + 3 more
A novel bibliometric methodology based on natural language data processing for identifying emerging topics in science is presented. Along with the usual practice of data collection and preprocessing, our method includes a natural language processing (NLP) technique and an innovative mathematical function data…