Organic reactivity from mechanism to machine learning

K Jorner, A Tomberg, C Bauer, C Sköld… - Nature Reviews …, 2021 - nature.com
As more data are introduced in the building of models of chemical reactivity, the mechanistic
component can be reduced until 'big data'applications are reached. These methods no …

Materials nanoarchitectonics from atom to living cell: A method for everything

K Ariga, R Fakhrullin - Bulletin of the Chemical Society of Japan, 2022 - academic.oup.com
Promoted understanding of nanostructures and their functions significantly rely on rapid
progress of nanotechnology within a few decades. It would be a fruitful way to consider …

Bio-interactive nanoarchitectonics with two-dimensional materials and environments

X Shen, J Song, C Sevencan, DT Leong… - … and Technology of …, 2022 - Taylor & Francis
Like the proposal of nanotechnology by Richard Feynman, the nanoarchitectonics concept
was initially proposed by Masakazu Aono. The nanoarchitectonics strategy conceptually …

Materials nanoarchitectonics in a two-dimensional world within a nanoscale distance from the liquid phase

K Ariga - Nanoscale, 2022 - pubs.rsc.org
Promoted understanding of nanotechnology has enabled the construction of functional
materials with nanoscale-regulated structures. Accordingly, materials science requires one …

Artificial intelligence and automation in computer aided synthesis planning

A Thakkar, S Johansson, K Jorner, D Buttar… - Reaction chemistry & …, 2021 - pubs.rsc.org
In this perspective we deal with questions pertaining to the development of synthesis
planning technologies over the course of recent years. We first answer the question: what is …

Mechanistic Inference from Statistical Models at Different Data-Size Regimes

DM Lustosa, A Milo - ACS Catalysis, 2022 - ACS Publications
The chemical sciences are witnessing an influx of statistics into the catalysis literature.
These developments are propelled by modern technological advancements that are leading …

Transformer performance for chemical reactions: Analysis of different predictive and evaluation scenarios

F Jaume-Santero, A Bornet, A Valery… - Journal of chemical …, 2023 - ACS Publications
The prediction of chemical reaction pathways has been accelerated by the development of
novel machine learning architectures based on the deep learning paradigm. In this context …

Liquid interfacial nanoarchitectonics: Molecular machines, organic semiconductors, nanocarbons, stem cells, and others

K Ariga - Current Opinion in Colloid & Interface Science, 2023 - Elsevier
The concept of nanoarchitectonics has been proposed as an extensional development of
nanotechnology through fusions with material science and the other fields. In …

Machine learning applications for chemical reactions

S Park, H Han, H Kim, S Choi - Chemistry–An Asian Journal, 2022 - Wiley Online Library
Abstract Machine learning (ML) approaches have enabled rapid and efficient molecular
property predictions as well as the design of new novel materials. In addition to great …

Nanoarchitectonics on living cells

K Ariga, R Fakhrullin - RSC advances, 2021 - pubs.rsc.org
In this review article, the recent examples of nanoarchitectonics on living cells are briefly
explained. Not limited to conventional polymers, functional polymers, biomaterials …