The 2024 contest is live this week through 10/16! See this year's entries and vote for your favorite: bit.ly/MFnanovote24
????Last year, our Molecular Foundry hosted their annual NanoArt Image Contest in celebration of #NationalNanoDay. The result? Incredible science images captured at the nanoscale! Check out the 2023 winners below ?? https://lnkd.in/ghXsh2Pp
AI can be seen both an opportunity for research productivity and a threat to research integrity. Our latest open research report "Feasibility of technical solutions for the detection of falsified images in research" discusses the risks posed by altered, duplicated and faked images and explores potential technical solutions. Focusing initially immunochemistry blots and microscopy images, our Phill Jones describes how digital signatures, metadata registries, and decentralised infrastructure could be used to certify images and other types of data. The question then becomes: how create the standards, organisational structures and community buy-in necessary to make it a success? Why not join the conversation during STM week in London in December. Follow the links in STMs post below to find out more. Read the report here: https://lnkd.in/ew6fiUJ3 or find it on our website.
?? New report is now live: Feasibility of technical solutions for the detection of falsified images in research With the rise of AI-generated content, image integrity in research is a critical challenge. STM funded a new report by MoreBrains Cooperative, investigating technical solutions to detect falsified images, focusing on areas like immunohistochemistry blots and microscopy. Key findings? While technology offers some answers, the real challenge lies in creating accepted standards and building community-wide trust. Download the report to dive into potential solutions — from digital signatures to trusted certificates >> https://lnkd.in/eWwdFxtT ?? Join the conversation: December 4 at STM Integrity Day in London —?part of STM's Innovation & Integrity Days (seats are going fast) >> https://lnkd.in/eq-uMRmG
Sign up for our first industry talk of 2025 in collaboration with STFC Scientific Computing, CCPBioSim Biomolecular Simulation and EPSRC! Lance Westerhoff at QuantumBio Inc. will be speaking about 'Advancing #CADD and #AI /ML campaigns through X-ray/ #Cryo-EM Density-Driven Refinement, #Tautomer Analysis and #Ligand Sampling' on Thursday 23rd January 2025 at 4pm UK time. Register for #FREE at https://lnkd.in/eeDi_muh Summary of abstract: Accurate protein:ligand structure determination is essential for structure-based #drugdiscovery (#SBDD), computer-aided drug design (CADD), and free energy methods. Precise modeling of protein:ligand complexes underpins key workflows. Traditional X-ray and Cryo-EM refinement methods rely on geometric restraints that often overlook critical interactions. QuantumBio has integrated the DivCon semiempirical quantum mechanics (SE-QM) engine into crystallographic refinement workflows to enable automated, density-driven structure preparation, completion, density search, ligand placement, and refinement. This approach significantly improves agreement with experimental data while delivering chemically accurate models.
A new article in collaboration with J. Russo, D. Pinto and F. Sciortino is out in ACS Nano journal. We use our #SATAssembly method to design particles that can self-assemble into a 3D quasicrystal cluster (a 3D ordered space-filling structure without translational symmetry), paving a way towards possible experimental realization at nanoscale with DNA nanostructures: https://lnkd.in/exZ7k-fB
Distinguished Professor of Theoretical Chemistry @ Sorbonne Université | Electronic Structure, Molecular simulation | CSO and Co-Founder @ Qubit Pharmaceuticals
Happy to see this one out. We present a new hybrid #quantumcomputing scheme for getting accurate energies and first-order properties of small molecules in quantum chemistry.#compchem The use of #GPU-accelerated emulation allows us to obtain quantitative results with ADAPT-VQE that would otherwise require brute-force quantum simulations using far more than 100 logical qubits (actually we reached an equivalent of nearly 300 qubits!). It is grounded on on-the-fly pivoted Cholesky-like adaptive basis sets (System-Adapted-Basis-Sets or SABS) and on a specific density basis set embedding of the quantum ansatz denoted density-based basis-set correction that allows recovering missing dynamical correlation effects due to basis set incompletess. Remaining missing basis effects can be included via a cheap Hartree Fock correction. - We converge the ground-state energies of four systems (He, Be, H2, LiH) within chemical accuracy of the CBS full-configuration-interaction reference, while offering a systematic increase of accuracy beyond a double-zeta quality for various molecules up to the H8 hydrogen chain. - We also obtain dissociation curves for H2 and LiH that reach the CBS limit whereas for the challenging simulation of the N2 triple-bond breaking, we achieve a near-triple-zeta quality at the cost of a minimal basis-set. A nice feature of the approach is that it can be also used as "a posteriori" correction to any real QPU computation. Hardware implementations to come! This work was funded in part by European Research Council (ERC) (project EMC2), by the ANR, the French National Research Agency (PEPR Epiq). Thanks to GENCI for a generous supercomputer time allocation. Kudos to all co-authors: Diata Traore Olivier ADJOUA César Feniou Ioanna-Maria Lygatsika?Yvon Maday ?Evgeny Posenitskiy Kerstin Hammernik Alberto Peruzzo Julien Toulouse?Emmanuel Giner Sorbonne Université Centre national de la recherche scientifique Qubit Pharmaceuticals #HPC #supercomputing
?? We’re excited to share our latest research, "Shortcut to Chemically Accurate Quantum Computing via Density-based Basis-set Correction," on arXiv! Shortcut to the full paper here: https://lnkd.in/erAhU5CP Our new hybrid scheme uses GPU-accelerated emulation and ADAPT-VQE to achieve accurate energies and properties predictions for small molecules while reducing the qubit requirements for quantum simulations. This approach leverages techniques such as System-Adapted-Basis-Sets (SABS) and density-based basis-set corrections to improve molecular energy calculations and properties, making advanced quantum computing more accessible for chemical research. Why is this important for drug discovery? By enabling highly accurate simulations of molecular interactions, we will be able to ultimately better understand how drugs bind to their targets, accelerating the identification and optimization of new drug candidates and reducing the time and cost involved in bringing new therapies to market. Reaching quasi-exact energies for small molecules is a first important milestone in that direction! Research like this is what makes us pioneers in quantum-assisted drug design and will allow us to design better treatments for any target and every patient. ?? Huge congratulations to the team Diata Traore, Olivier ADJOUA, César Feniou, I.-M. Lygatsika, led by Jean-Philip Piquemal, - as well as Alberto Peruzzo and Evgeny Posenitskiy. Special thanks as well to co-author Kerstin Hammernik! Massive thanks as well to our partners for their support: GENCI, NVIDIA and Scaleway ! Read the paper here: https://lnkd.in/erAhU5CP #QuantumComputing #DrugDiscovery #Chemistry #DeepTech #Innovation #GPUComputing
Materials Scientist | Computational Chemistry | Molecular Dynamics | DFT | Machine Learning | Multi-scale Modeling | Quantum Chemistry | Process Modeling | Project Planning | Strategic Communication | Skier ??
Thank you for sharing this excellent post on the transformative power of simulations in chemistry, Quantistry team! The strides being made in computational chemistry are indeed impressive and critical for advancing our field. Having been deeply involved in similar research, I can attest to the immense potential of these tools. During my projects at CMMR Lab at Michigan Technological University, I utilized reactive molecular simulations to simulate curing (crosslinking) reactions in high-performance polymers and predict thermo-mechanical properties as a function of processing parameters. This approach not only enhanced our understanding of the evolution of material properties with curing but also paved the way for multiscale process modeling using ICME (Integrated Computational Materials Engineering). One of the highlights of my recent work was winning the AIAA ICME prize 2022, where we leveraged advanced simulation techniques to optimize the design of composite Y-joint used in Aurora Flight Science's D8 aircraft. Seeing the capabilities of these simulations in action reaffirms my belief in their importance for future discoveries and innovations. It's inspiring to see the progress and dedication of the Quantistry team. #Simulation #Chemistry #Research #Innovation #ComputationalChemistry #MolecularSimulation #reactivity #polymers
?? Moving Beyond Serendipity in Science with Simulations Can multiscale simulations and machine learning end trial and error, ushering in a data-driven science era? Serendipity, like Fleming's penicillin discovery, has long driven breakthroughs in science, such as X-rays, chemotherapy, and graphene. Traditionally, science relied on trial and error — constant, meticulous, repetitive experiments informing the next round of research. Technology like computational simulations and machine learning is revolutionizing research, making traditional methods obsolete. Read more in our blog: https://lnkd.in/geRHuhVj ?? If you want to know how Quantistry can help you upgrade your R&D get in touch: https://lnkd.in/gE8uy8rA #simulation #chemistry #research #machinelearning #materials #science
I am excited to share our latest findings of the molecular modeling of catenanes for moletronics applications! Our research demonstrates the study of using these unique molecules to create molecular switches and compare different molecular structures. Investigating different molecules' behavior in different environments using advanced molecular modeling tools and simulation techniques, opens up a new era of innovation. #MolecularModeling #Catenane #Moletronics #Nanotechnology #Science #IEEE #UniversityOfBridgeport https://lnkd.in/e6-gsaaY
Ultrafast creation of a light-induced semimetallic state in strongly excited 1T-TiSe2 Science Advances https://lnkd.in/g-hqne3M
The Round Robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential Dimitra-Danai Varsou, Arkaprava Banerjee, Joyita Roy, Kunal Roy, Giannis Savvas, Haralambos Sarimveis, Ewelina Wyrzykowska, Mateusz Balicki, Tomasz Puzyn, Georgia Melagraki, Iseult Lynch and Antreas Afantitis Beilstein Arch. 2024, 202433. https://lnkd.in/gmH-WX8n Using a publicly available dataset four research groups (NovaMechanics Ltd (NovaM) - Cyprus, National Technical University of Athens (NTUA) - Greece, QSAR Lab Ltd - Poland, and DTC Laboratory - India) built five distinct machine learning (ML) models for the in silico prediction of the zeta-potential of metal and metal oxide-nanomaterials (NMs) in aqueous medium. The individual models were integrated into a consensus modelling scheme, enhancing their predictive accuracy, and reducing their biases. The consensus models outperform the individual models, resulting in more reliable predictions. We propose this approach as a valuable method for increasing the validity of nanoinformatics models and driving regulatory acceptance of?in silico?new approach methodologies for use within an Integrated Approach to Testing and Assessment (IATA) for risk assessment of NMs. #nanoqsar #nanoinformatics #cheminformatics #zetapotential #readacross #rasar
?? Exciting News! ?? I am thrilled to announce that my latest research paper, titled "SMARTINI3: Systematic Parametrization of Realistic Multi-Scale Membrane Models via Unsupervised Learning and Multi-Objective Evolutionary Algorithms," has been published! In this study, we delve into the innovative integration of unsupervised learning techniques and multi-objective evolutionary algorithms to enhance the parametrization of multi-scale membrane models. Our findings pave the way for more accurate and efficient simulations in membrane science, which can have significant implications for various applications in biotechnology, materials science, and beyond. If you're interested in learning more about our work, feel free to reach out or check out the publication here: [https://lnkd.in/eng8zVZE] Looking forward to more exciting research and discoveries ahead! #SMARTINI3 #Multiscale #MembraneModels #UnsupervisedLearning #MultiObjective #EvolutionaryAlgorithms
?? Join the talk and get updated on recent innovations in the field of particle technology.
New virtual talk, new opportunity to gain expert knowledge – #PARTEC Edition!? ? Join the talk about particle technology, where four professors from the Executive Committee will provide insights about current topics and trends. The topic: Particles empowering tomorrow: Innovations for our global world.? ? ???Date:?Tuesday, June 18, 2024 ??Time: 13:00 – 14:45 CEST ???Location: Online? ? Two of our experts are..? ? ?? … Lutz M?dler, Director of the Leibniz Institute for Materials Engineering IWT, Bremen, Chair PARTEC 2025 with the talk “Heteroaggregates - Particle building blocks for many applications”, and? ? ?? ... Stefan Heinrich, Director Institut für Feststoffverfahrenstechnik und Partikeltechnologie, Technische Universit?t Hamburg, who will share insights about challenges in modelling and understanding of particle formulation by fluidized bed spray granulation.? ? Be part of the conversation about innovations that are empowering the processing industry tomorrow!? ? ???Register now for the #POWTECHTECHNOPHARM Virtual Talk:?https://lnkd.in/dYcJWcMG? ? #processing #particle #particletechnology #granulation #processindustry #ai #particles?
