ReviewACS central science2018
The Matter Simulation (R)evolution.
Review in ACS central science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Quantum Chemistry-Driven Molecular Inverse Design of Stable Isomers with Data-Free Reinforcement Learning.Journal of chemical theory and computation · 2026Article
- Boosting Computational Catalysis and Chemical Reactivity with Artificial Intelligence.Journal of the American Chemical Society · 2026Review
- Elements and roadmap for interactive molecular graphics and modeling "in the Holodeck".Protein science : a publication of the Protein Society · 2026Article
- ASAS-NANP SYMPOSIUM: MATHEMATICAL MODELING IN ANIMAL NUTRITION: quantum computing in agricultural sciences: from theory to reality.Journal of animal science · 2026Review
- Studying Noncovalent Interactions in Molecular Systems with Machine Learning.Chemical reviews · 2025Review
- The Quantum Paradox in Pharmaceutical Science: Understanding Without Comprehending-A Centennial Reflection.International journal of molecular sciences · 2025Review
- A human-machine interface for automatic exploration of chemical reaction networks.Nature communications · 2024Article
- Sample efficient reinforcement learning with active learning for molecular design.Chemical science · 2024Article
- ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis.Journal of the American Chemical Society · 2023Article
- Neural network potentials for chemistry: concepts, applications and prospects.Digital discovery · 2023Review
- Uncertainty Quantification of Reactivity Scales.Chemphyschem : a European journal of chemical physics and physical chemistry · 2022Article
- On scientific understanding with artificial intelligence.Nature reviews. Physics · 2022Review
- Machine Learning for Electronically Excited States of Molecules.Chemical reviews · 2021Article
- Ab Initio Machine Learning in Chemical Compound Space.Chemical reviews · 2021Review
- Data-Driven Strategies for Accelerated Materials Design.Accounts of chemical research · 2021Article
- Big-Data Science in Porous Materials: Materials Genomics and Machine Learning.Chemical reviews · 2020Review
- Geometric landscapes for material discovery within energy-structure-function maps.Chemical science · 2020Article
- Article
- Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers.PeerJ. Computer science · 2020Article
- Digital quantum simulation of molecular vibrations.Chemical science · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To date, the program for the development of methods and models for atomistic and continuum simulation directed toward chemicals and materials has reached an incredible degree of sophistication and maturity. Currently, one can witness an increasingly rapid emergence of advances in computing, artificial intelligence, and robotics. This drives us to consider the future of computer simulation of matter from the molecular to the human length and time scales in a radical way that deliberately dares to go beyond the foreseeable next steps in any given discipline. This perspective article presents a view on this future development that we believe is likely to become a reality during our lifetime.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.