Author

Alexandra Farcas

3 papers indexed here

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Open access Oct 2026

AdaptDelivery: a polymer informatics platform for predicting structural properties of polymers via machine learning

Polymers are highly versatile and cost-effective materials with a wide range of tunable physicochemical properties, making them indispensable across numerous technological and biomedical applications. However, their intrinsic chemical heterogeneity and complex structural organization pose significant challenges for t...

Lorand Gabriel Parajdi, I. Tóth, Alex-Adrian Farcas et al. · Scientific Reports · 0 citations

#machine learning Preprint Sep 2026

A strategic roadmap for an atomistic machine-learning ecosystem

Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of matter is particularly widespread and impactful. This success is due largely to the existence of a well-developed and established physics-based modeling framework, ranging...

Jörg Behler, Michele Ceriotti, Cecilia Clementi et al. · 0 citations

Open access Jul 2026

A molecular descriptor dataset of 33,715 small molecules based on operator-based descriptor framework.

This Data Descriptor presents a large-scale molecular descriptor dataset comprising 33,715 small molecules, specifically curated for high-throughput screening and drug delivery strategy optimization. Addressing the limitations of traditional descriptors in characterizing complex molecular geometry, we provide advanced...

Alexandra Farcaș, L. Jäntschi · Scientific Data · 1 citation