Hydrogen bond networks of ammonia clusters: What we know and what we don't know
A Malloum, J Conradie - Journal of Molecular Liquids, 2021 - Elsevier
Understanding the behaviour of liquid ammonia is subjected to understanding the hydrogen
bond networks in ammonia clusters as well as their interactions. In comparison to water …
bond networks in ammonia clusters as well as their interactions. In comparison to water …
[HTML][HTML] Machine learning meets chemical physics
Over recent years, the use of statistical learning techniques applied to chemical problems
has gained substantial momentum. This is particularly apparent in the realm of physical …
has gained substantial momentum. This is particularly apparent in the realm of physical …
Do machine-learning atomic descriptors and order parameters tell the same story? The case of liquid water
Machine-learning (ML) has become a key workhorse in molecular simulations. Building an
ML model in this context involves encoding the information on chemical environments using …
ML model in this context involves encoding the information on chemical environments using …
Aerial low‐altitude remote sensing and deep learning for in‐field disease incidence scoring of virus yellows in sugar beet
N Okole, FR Ispizua Yamati, R Hossain… - Plant …, 2024 - Wiley Online Library
This study investigates the potential of high‐resolution (< 0.5 cm/pixel) aerial imagery and
convolutional neural networks (CNNs) for disease incidence scoring in sugar beet, focusing …
convolutional neural networks (CNNs) for disease incidence scoring in sugar beet, focusing …
Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units
Atomic structure prediction and associated property calculations are the bedrock of chemical
physics. Since high-fidelity ab initio modeling techniques for computing the structure and …
physics. Since high-fidelity ab initio modeling techniques for computing the structure and …
The role of charge in microdroplet redox chemistry
In charged water microdroplets, which occur in nature or in the lab upon ultrasonication or in
electrospray processes, the thermodynamics for reactive chemistry can be dramatically …
electrospray processes, the thermodynamics for reactive chemistry can be dramatically …
Detection of monkeypox disease from skin lesion images using Mobilenetv2 architecture
Monkeypox has recently become an endemic disease that threatens the whole world. The
most distinctive feature of this disease is occurring skin lesions. However, in other types of …
most distinctive feature of this disease is occurring skin lesions. However, in other types of …
Co-design center for exascale machine learning technologies (exalearn)
Rapid growth in data, computational methods, and computing power is driving a remarkable
revolution in what variously is termed machine learning (ML), statistical learning …
revolution in what variously is termed machine learning (ML), statistical learning …
All‐body concept and quantified limits of cooperativity and related effects in homodromic cyclic water clusters from a molecular‐wide and electron density‐based …
I Cukrowski, S Zaaiman, S Hussain… - Journal of …, 2024 - Wiley Online Library
We strongly advocate distinguishing cooperativity from cooperativity‐induced effects. From
the MOW e D‐based approach, the origin of all‐body cooperativity is synonymous with …
the MOW e D‐based approach, the origin of all‐body cooperativity is synonymous with …
Explaining molecular properties with natural language
We present a model-agnostic method that gives natural language explanations of molecular
structure property predictions. Machine learning models are now common for molecular …
structure property predictions. Machine learning models are now common for molecular …