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AI as a tool in flavor research

Researchers developed an AI-based method to predict bitterness of peptides, enabling de novo design of bitter peptides for improved flavor control. The method used a combination of a protein language model and an artificial neural network to analyze structural data, resulting in the identification of new bitter-tasting peptides.

SourceLeibniz-Institut für Lebensmittel-Systembiologie an der TU München·Journalnpj Science of Food·TypeComputational simulation/modeling·DateSep 22, 2026

HKU chemists harness light to build 3D molecular structures for drug discovery

Researchers at HKU have developed a new light-driven method for constructing three-dimensional molecular building blocks. This approach broadens the range of starting materials and suppresses unwanted polymerisation, overcoming key limitations of existing synthetic methods. The findings have the potential to improve characteristics of ...

SourceThe University of Hong Kong·JournalNature Chemistry·TypeObservational study·DateSep 8, 2026

Machine-learning how to overcome antibiotic-resistant gonorrhea

A new study uses AI to identify promising chemical compounds that could develop into effective antibiotics against multi-drug resistant Neisseria gonorrhoeae. The approach has the potential to address the growing crisis of antimicrobial resistance in this fast-evolving pathogen.

SourceWyss Institute for Biologically Inspired Engineering at Harvard·JournalScience Translational Medicine·TypeComputational simulation/modeling·DateJun 17, 2026

How life could arise from molecules

Complex systems exhibit emergent properties due to water's unique polarity, enabling DNA to store information and proteins to adopt specific structures. This order forms the basis for complex molecules to develop unpredictable properties, driving the evolution of life.

SourceGoethe University Frankfurt·JournalAngewandte Chemie International Edition·TypeData/statistical analysis·DateMay 5, 2026

Kent computational approach takes the guesswork out of drug development for Chagas disease

A computational protocol has been established by University of Kent researchers to accurately identify reactions that can result in successful drug candidates for Chagas disease. This approach reduces the need for trial-and-error, prioritizing promising compounds earlier and making the drug discovery process faster and more affordable.

SourceUniversity of Kent·JournalChemistryOpen·TypeComputational simulation/modeling·DateApr 24, 2026

Scientists develop ultra‑robust machine‑learning models capable of stable molecular simulations at extreme temperatures

Researchers have created a new AI model that can simulate molecules under extreme conditions, allowing for reliable discoveries in fields like drug development and sustainable chemistry. The model's stability opens up new opportunities for simulations in areas where long-term accuracy is essential.

SourceUniversity of Manchester·JournalCommunications Chemistry·TypeComputational simulation/modeling·DateMar 31, 2026

Exposing a hidden anchor for HIV replication

Scientists at the University of Delaware discovered a previously unknown structural role for the HIV integrase protein, which forms gluey filaments that anchor the RNA genome to the capsid. This discovery provides a promising new target for drug development and could lead to the development of next-generation inhibitors.

SourceUniversity of Delaware·JournalNature·DateFeb 18, 2026

Nobel Prize-awarded material that puncture and kill bacteria

Researchers at Chalmers University of Technology have developed a new material that uses metal-organic frameworks to physically injure and kill bacteria, preventing biofilm formation without antibiotics or toxic metals. This innovation eliminates the risk of antibiotic resistance and has potential applications in various industries.

SourceChalmers University of Technology·JournalAdvanced Science·TypeExperimental study·DateNov 27, 2025

AI engineers nanoparticles for improved drug delivery

Biomedical engineers at Duke University developed a platform combining automated wet lab techniques and AI to design nanoparticles for drug delivery. The TuNa-AI platform resulted in a 42.9% increase in successful nanoparticle formation compared to standard approaches.

SourceDuke University·JournalACS Nano·TypeComputational simulation/modeling·DateSep 24, 2025

When waves meet the shore

Researchers found that strong wave breaking along shorelines produces significant amounts of sea spray aerosols, increasing cloud condensation nuclei and aerosol mass concentration. This can lead to gross overestimations of sea spray aerosols in open oceans using coastal measurements.

USC technology may reduce shipping emissions by half

A USC-developed shipboard system using limestone and seawater can remove up to half of carbon dioxide emitted from shipping vessels, cutting maritime CO2 emissions by 50%. The process mimics a natural chemical reaction in the ocean, where CO2 is absorbed into water pumped onboard and then neutralized through a bed of limestone.

SourceUniversity of Southern California·JournalScience Advances·TypeComputational simulation/modeling·DateJun 26, 2025

Model tackles key obstacle to efficient plastic recycling

Researchers developed a new framework that connects molecular scale processes with reactor-scale models for catalytic depolymerization of plastics. The findings offer a powerful tool for designing catalyst architectures and identifying reaction conditions to boost selectivity of value-added products.

SourceUniversity of Illinois at Urbana-Champaign, News Bureau·JournalAccounts of Chemical Research·TypeComputational simulation/modeling·DateJun 24, 2025

Modeling electric response of materials, a million atoms at a time

Researchers developed a machine learning framework that can predict how materials respond to electric fields up to a million atoms, accelerating simulations beyond quantum mechanical methods. This allows for accurate, large-scale simulations of material responses to various external stimuli.

SourceHarvard John A. Paulson School of Engineering and Applied Sciences·JournalNature Communications·TypeComputational simulation/modeling·DateJun 9, 2025

Quantum simulation of chemical dynamics achieved for the first time using Sydney quantum computer

Scientists successfully simulated real chemical interactions with light, marking a major breakthrough in applying quantum computing to chemistry and medicine. This achievement holds promise for understanding complex light-driven phenomena, such as photosynthesis and cancer research.

SourceUniversity of Sydney·JournalJournal of the American Chemical Society·TypeExperimental study·DateMay 14, 2025

Simulating the fluid dynamics of moving cells to map its location

Kyushu University researchers have successfully recreated the fluid dynamics of flowing biological cells using numerical simulations. The study reveals that capsule position depends on deformation and pulsation frequency, enabling precise cell manipulation in research and potential applications in artificial heart development.

SourceKyushu University·JournalJournal of Fluid Mechanics·TypeComputational simulation/modeling·DateApr 9, 2025

Chatbot opens computational chemistry to nonexperts

A new web platform, AutoSolvateWeb, developed at Emory University enables chemists of all levels to configure and execute complex quantum mechanical simulations through chatting. The free platform uses cloud infrastructure and automates software processes on the backend.

SourceEmory University·JournalChemical Science·TypeComputational simulation/modeling·DateApr 7, 2025

Scientists uncover a multibillion-year epic written into the chemistry of life

Researchers discovered that just eight new biochemical reactions can bridge the gap between simple geochemistry and biochemistry, indicating a limited loss of biochemistry to time. This finding suggests that even extinct reactions can be rediscovered from clues left behind in modern biochemistry.

SourceTokyo Institute of Technology·JournalNature Ecology & Evolution·TypeComputational simulation/modeling·DateMay 28, 2024

How scientists are accelerating chemistry discoveries with automation

A new statistical-modeling workflow can quickly identify molecular structures of products formed by chemical reactions, accelerating drug discovery and synthetic chemistry. The workflow also enables the analysis of unpurified reaction mixtures, reducing time spent on purification and characterization.

SourceDOE/Lawrence Berkeley National Laboratory·JournalJournal of Chemical Information and Modeling·TypeData/statistical analysis·DateApr 8, 2024

Carnegie Mellon researchers develop new machine learning method for modeling of chemical reactions

Researchers at Carnegie Mellon University have created a new machine learning model that can simulate reactive processes in diverse organic materials and conditions. The model, called ANI-1xnr, performs simulations with significantly less computing power and time than traditional quantum mechanics models.

SourceCarnegie Mellon University·JournalNature Chemistry·TypeComputational simulation/modeling·DateMar 7, 2024

Magnesium still has the potential to become an efficient hydrogen store

A Swiss-Polish team has found the answer to why previous attempts to use magnesium hydride for efficient hydrogen storage failed. The researchers developed a new model that predicts local, thermodynamically stable clusters are formed in magnesium during hydrogen injection, reducing hydrogen ion mobility.

The mind’s eye of a neural network system

Researchers at Purdue University developed a new tool to visualize neural network decisions, making it easier to identify errors in image recognition. The tool uses graph-topological data analysis to provide a bird's-eye view of all images in a database, revealing areas where the network struggles to distinguish between classifications.

SourcePurdue University·JournalNature Machine Intelligence·TypeData/statistical analysis·DateNov 16, 2023

Towards computational design of molecules with desired properties

A new computational approach enables the design of molecules with targeted quantum-mechanical properties, finding that most properties are only weakly correlated among small molecules. The 'freedom of design' concept reveals an intrinsic flexibility in chemical compound space, allowing for simultaneous optimization of multiple properties.

SourceUniversity of Luxembourg·JournalChemical Science·TypeData/statistical analysis·DateSep 25, 2023

Evaluating the shear viscosity of different water models

Associate Professor Tadashi Ando from Tokyo University of Science conducted a study to test the performance of OPC and OPC3 water models, evaluating their shear viscosities and comparing values to experimental calculations. The calculated viscosities for both models were very close, with notable accuracy at temperatures above 310 K.

SourceTokyo University of Science·JournalThe Journal of Chemical Physics·TypeComputational simulation/modeling·DateSep 21, 2023

Ions share their hydration secrets for industrial design and manufacturing

Researchers have proposed an explanation for the ion-specific properties of ion hydration in water-based solutions, revealing that ions with lower charge density interact with more water molecules. This result has broad applications across multiple disciplines, including chemistry, biology, and materials science.

Decrypting integrins by mixed-solvent molecular dynamics simulation

A team of researchers developed a novel computational approach to identify allosteric sites in integrins, revealing previously inaccessible druggable pockets. This breakthrough has the potential to overcome limitations in integrin-targeting medication and open new avenues for drug discovery.

SourceUniversiteit van Amsterdam·JournalJournal of Chemical Information and Modeling·TypeComputational simulation/modeling·DateJun 28, 2023

New recipes for better solar fuel production

A team of researchers from China and the UK has developed new ways to optimise the production of solar fuels by creating novel photocatalysts. These photocatalysts, such as titanium dioxide with boron nitride, can absorb more wavelengths of light and produce more hydrogen compared to traditional methods.

SourceXi'an Jiaotong-Liverpool University·JournalApplied Surface Science·TypeExperimental study·DateJun 11, 2023

A new model predicts the flexibility of DNA movement at the molecular scale

A new model of DNA flexibility has been developed, providing results of unprecedented quality and characterizing precision and efficiency at the computational level. The study presents a systematic and comprehensive analysis of DNA movement correlations and introduces a new method to capture them.

SourceInstitute for Research in Biomedicine (IRB Barcelona)·JournalNucleic Acids Research·TypeComputational simulation/modeling·DateMar 31, 2023

Probe where the protons go to develop better fuel cells

A team led by Professor Yoshihiro Yamazaki from Kyushu University discovered the chemical innerworkings of a perovskite-based electrolyte developed for solid oxide fuel cells. By combining synchrotron radiation analysis, large-scale simulations, machine learning, and thermogravimetric analysis, they found that protons are introduced at...

SourceKyushu University·JournalChemistry of Materials·TypeExperimental study·DateMar 28, 2023

Quantum chemistry: Molecules caught tunneling

Scientists at the University of Innsbruck have successfully measured tunneling reactions in molecular chemistry, confirming a precise theoretical model. The experiment used hydrogen and deuterium isotopes to demonstrate the quantum mechanical tunnel effect in a slow ion-molecule reaction.

SourceUniversity of Innsbruck·JournalNature·TypeExperimental study·DateMar 1, 2023