Collections
AI and automation
In this collection, we explore the latest developments in artificial intelligence (AI) and automation, covering technologies and applications such as machine learning, robotics, laboratory automation and data analysis, and their impact on chemistry research, the profession, and chemistry-using industries.
The robots revolutionising chemistry
Researchers working with automated systems are pushing the boundaries of what chemists can achieve in the lab, reports James Mitchell Crow
What does AI mean for chemistry?
Phil Ball looks at whether letting machines do our thinking for us will change our understanding of chemistry itself
How to automate your lab
Whether it’s robots, automation or software hacks, Nessa Carson finds ways for everyone to improve how they work in the lab
The psychology of our future with AI
It’s time to accept that digitalisation is changing laboratory work, and embrace the opportunity
Encoding creativity in drug discovery
Machine learning can complement and reinforce human intuition and experience
How will AI and automation change chemistry?
It’s going to change our lives. But it’s not clear in what ways
You don’t need coding to be a chemist
Writing your own software can be useful, but what matters is knowing how to use it
Robots in the lab – learn how automation can streamline your workflow
The future of lab automation is promising. This webinar session reveals the answers to the most important questions in chemistry related automation today
SmartChemistry brings the power of AI and machine learning into your lab
Digital chemistry technologies provide the tools to accelerate your research
ResearchAI helps chemists consider more options when it comes to picking the best reactants for an experiment
Algorithm can standardise substrate selection to improve performance and structural diversity
OpinionScientists must be trained to work without AI, as well as working with it
As AI and autonomous labs become more capable, human reasoning must be preserved
ResearchTagging AI-generated proteins during design process will let scientists know who made them
Google DeepMind researchers who developed the method say that this will help uphold scientific integrity and prevent misuse of protein designs
WebinarEl Agente: ask me anything! A live demonstration
Join us as we tackle your chemistry challenges live with the El Agente team on 24 November
NewsGoogle DeepMind’s mutation Atlas shines a light on our dark DNA
AI’s predictions on the impact of changing each and every base of the human genome will help scientists understand genetic basis of disease
OpinionFeeding AI’s appetite for data
Tapping companies’ archives makes for better predictions of how proteins bind drugs, but any data inputs need to be transparent and attributed
ResearchBenchmark flaws may be distorting AI drug-discovery leaderboards
Audit identifies subtle but consequential issues, such as conflicting labels and train–test leakage, in numerous benchmark datasets
OpinionArtificial intelligence or clever artifice?
It’s important to be realistic about what AI can, and can’t, achieve, across the chemistry enterprise
BusinessCombining AI with experiments to solve real-world materials problems
CuspAI’s Materials Foundry partner network includes 45 technology, data and materials chemistry companies to make and test its predictions
NewsUS National Science Foundation putting $380 million into building ‘self-driving’ labs
North Carolina State is one of the institutes receiving a $20 million grant aims to advance an autonomous chemistry lab
FeatureHow AI is transforming the world of analytical chemistry
Analytical chemists have been using machine learning long before ChatGPT made headlines. Now, as generative AI enters the laboratory, the discipline faces both opportunities and risks
ResearchProtein wrappers designed by AI solve membrane proteins’ solubility problem
Protein sheaths encapsulate membrane proteins while preserving their structure and function making them easier to study
OpinionCould AI undermine our (belief in the truth of) scientific theories?
Artificial intelligence models that make predictions based solely on data present problems for philosophers
ResearchAI model fills in the gaps in crystal structures by placing missing hydrogen atoms
Model may help fix existing structures in the database or better simulate new materials
FeatureAI agents accelerate catalyst discovery from simulation to scale-up
Artificial intelligence tools are transforming catalyst research, with new AI agents capable of completing in minutes what once took computational chemists days. Andy Extance explores how all scientists can benefit, from small groups to those at tech giants like Meta, Google and Nvidia
ResearchCould AI research assistants speed up scientific discovery?
Google’s Co-Scientist and Futurehouse’s Robin can help scientists generate hypotheses, design experiments and analyse data
ResearchStripped down bacterium functions with one less amino acid than the rest of life on Earth
Deep learning models used to understand how isoleucine could be replaced in proteins without disrupting their structures
Research‘Human-in-the-loop’ approach could cut costs of robotic labs by 90%
Reducing costs may democratise field by making self-driving labs more accessible
OpinionWhy data visualisation is so important in the age of AI
Machines don’t need to draw charts and plots to work with data, but humans will still need datavis skills to work with machines.
ResearchMachine learning cuts complexity of computational calculations in catalysis
Software simulates 370,000 steps in under 100 hours, potentially cutting demand for time on supercomputers by orders of magnitude
ResearchMolecules with largest dipole moments aren’t due to electronegativity differences
Computational analysis challenges Pauling’s idea of polarity
PodcastAlphaGenome & the RNA world hypothesis
In this episode, we discuss Google DeepMind’s latest deep learning model AlphaGenome, dissect the origins of life from chemicals to complex lifeforms, and hear the latest headlines.
ResearchGoogle’s AlphaGenome wants to do for DNA what AlphaFold did for proteins
Model predicts effect of mutations on sequences up to 1 million base pairs in length and is adept at tackling complex non-coding regions
NewsAI research tools benefit individual scientists but may slow scientific progress
There may be a conflict between personal and collective gain in the sciences