Posters

WEIGen - Generative AI for Self Driving Laboratory Protocols

From Eyes to Cameras: Computer Vision for High-Throughput Liquid-Liquid Separation

A Dataset of Drug-Loaded PLGA Based Nanoparticle Formulations

CACTUS: Chemistry Agent Connecting Tool-Usage to Science

Acceleration of Microfluidic Technologies as a Prominent Tool for Micro-/Nano-Scale Fabrication of Materials: Toward Integration with Automation and Scalable Fluidic Processes

In Pursuit of Low-Cost Lab Automation: Designing Frugal Twins by Extending the Capabilities of Liquid Handlers and 3D Printers

Directed coevolution of chemicals

Streamlining the Discovery of Porous Materials

Italian Materials and Devices Acceleration Platform - “IT-MADAM”

Benchmarking an Open-source Workflow for High-Throughput Molecular Docking

DiSCO: Autonomous [Di]scovery, [S]ynthesis, [C]haracterization, and [O]ptimization of High-performance Functional Materials using Robotics and Computer Vision

Blend 0s and 1s with Chemical Intuition for Retrosynthesis Planning

EVOLVE: A Chemist Controllable Machine Learning Enhance Genetic Algorithm for Drug Candidate Discovery

Autonomous Creation of Soft Materials Through Robotic Assembly of Microliter Liquid/Gel Chambers

An autonomous experimentation platform for the optimization of silica nanoparticle morphologies

Multiscale Methods for the Active Learning of Interatomic Potentials

Computer vision aid for flash point detection of gel polymer electrolytes

Autonomous Experimentation for Material Discovery - Constrained Motion Planner

Using Automation to Lower the Barrier to High Quality Analytical Data in Drug Checking and Point of Care Services

Multi-fidelity Bayesian Optimization of Covalent Organic Frameworks for Xenon/Krypton Separations

Large-Scale Raman Spectra Calculations in Graphene and Hexagonal Boron Nitride Using Deep Learning

Predicting Pure Fluid Properties Using Self-Supervised Machine Learning

Precision Fluid Handling for Low-Cost and High-Throughput Direct Material Printers in Autonomous Research

Autonomous Generation of a Molecular Dataset for the Discovery of Alkaline Stable Anion Exchange Membranes

Advancing Graphene Field-Effect Transistors Biosensors Technology with Automated and Parallelized Systems

Calibration-Free Quantification and Automated Data Analysis for High-Throughput Reaction Screening

Open-source software tools for automated kinetics

Ranking models are good surrogates for Bayesian optimization of chemical compounds

Continuous flow production of near-infrared plasmonic nanostars with machine learning

High-Throughput Experimentation for High-Pressure Reverse-Osmosis Membranes

Accelerated Optimization of Water-Splitting Materials via Automation

Multi-fidelity Bayesian Optimisation: Challenges and Pitfalls for Autonomous Experimentation

Applying quantum mechanics to deconvolute benchtop 1H NMR reaction data

A Novel Approach to Chemical Synthesis: Modular, Reconfigurable Automation Systems

A General-Purpose Robotics Platform for Automated Biological Experimentation

On-the-fly reaction monitoring using correlated spectroscopies

Accelerating the development of performance fluids and materials for the transition at TotalEnergies: how automation and AI are contributing to the energy transition

Development of a Self-Driving Lab Inventory Database Using SQLite

Development of a modular, customizable Bayesian optimization software module for multi-objective optimization

Development of powder dispensing and weighing module for autonomous materials discovery of energy materials

Applications of Transient Flow for Sustainable Process Development: Kinetics, Selectivity, Solvent Replacement, and More

Rapid Exploration of Rare Earth Metal–Organic Framework Crystallization Enabled by High-Throughput, Automated Synthesis and Characterization

An XGBoost Algorithm Based on Molecular Structure and Molecular Specificity Parameters for Predicting Gas Adsorption

RPLtags for Unified Identification, Navigation, Pose Estimation in Uncalibrated Spaces

Accelerating Lubricant Screening for Electric Vehicles: A Self-Driving Lab Study on Thermophysical Properties

LLM enabled knowledge graph extraction for graph-based data management

A kinetic-assisted growth curve prediction method for Chlamydomonas reinhardtii incorporating transfer learning

Predicting Phase Evolution in Solid-State Synthesis Using Cellular Automata

From Concepts to Implementation: Machine Learning Accelerated Nanoporous Materials Discovery

Accelerating Screening of Polysaccharide-based Hydrogels Using Automated Systems and Image Analysis

Quantum-Infused Molecular Forge: Revolutionizing Molecular Design through Quantum-Inspired Multi-Objective Optimization

Laboratory Characterization Automation of Organic Thin Film Transistors for High Throughput Research and Development

High-throughput Screening of Thermal Fluid

UTILE: Autonomous Image Analysis to Accelerate the Discovery and Integration of Energy Materials

Universal chemical programming language for robotic synthesis repeatability

Efficient Determination of Born-Effective Charges, LO-TO Splitting and Raman Tensors of Solids with a Real-Space Atom-Centered Deep Learning Approach

Self-Driving Virtual Laboratory for Accelerated Design of PHA Biopolymers

Modular Cartesian Platform for liquid automation

Error Detection and Correction in High-Throughput Experimentation through Innovative Data Recycling Workflow

Computing Crystals: a self-driving lab for the purification of multicomponent solids via cooling crystallization

Towards AI-driven inverse method for identifying mechanical properties from miniaturised tests

Development of viscosity measurement and water content sensing module for autonomous materials discovery of energy materials

Accelerated Discovery Platform Instrumentation: High-Throughput Calorimetry for Heat Transfer Fluids

Simulations In Nvidia Omniverse For Validating Language Model-Based Experiment Designs

Perovskite Quantum Dots Synthesis Directed by Exploratory Data Analysis

Spock: LLM-based Tool for Bibliometric Analysis of Scientific Literature

A Bayesian Framework to Assess Equivalent Circuit Models Plausibility across Different Scenarios for Electrochemical Impedance Spectroscopy

Integrating Automation and Advanced Analytics in Drug Checking: Enhancing Sensitivity with NMR and HPLC

Quantum-Computing Enhanced Generative Transformer for Drug Discovery

Using a self-supervised transformer model for property predictions and MOF application recommendations with only x-ray diffraction patterns

A Modular User Facility for Self-Driving Polymer Research

Data-driven predictions for self-emulsifying drug delivery systems using machine learning

Autonomous Organ-on-a-Chip: Standardised Integration of Automation and Machine Learning with High-Fidelity Human in vitro Models

Advanced Automated Workflows on the OT-2 with Custom Labware and Machine Learning Algorithms

Towards efficient tuning of porphyrin affinities to gases using machine learning

ByteScience: Extracting Complex Structured Materials Information at Scale via Large Language Model

Accelerating Chemistry Digitization with Multimodal Large Language Models

Incorporating IoT Devices and Services to a Liquid Handling Robot: Designing a Closed-Loop Platform for Planning Experiments and Automating Data Collection

A tutorial on low-cost self-driving laboratories

Toward autonomous electrolyzer research: the ALEC story

Construction and application of Functional Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model

Machine learning accelerated design and assembly of synthetic microbial communities for sustainable chemical manufacturing

Real-Time Analysis Facilitates the Mechanistic Understanding of Suzuki-Miyaura Cross-Couplings

Behind the Scenes: Process Intensification and Increased safety for the On-Demand Continuous Flow Synthesis of Dithiothreitol (DTT), a Crucial component in PCR Testing Kits

Modular Robotic System for High Throughput Thin Film Deposition Processes

Affordable Automation for Electrochemistry Synthesis and Characterization

Research study on ways of Integrating environmental, social and economic factors into Self-Driving Lab processes of material development.

High-Throughput Aging Studies of Vapor-Deposited Perovskite Thin-Films Using Precise Automated Characterization Methods and Machine Learning-Assisted Analysis

Active learning guided high-throughput synthesis and characterization of mixed metal oxides

General structure of experiments for comfortable laboratory automation

Self-driving labs for scale-up: Bridging discovery and deployment

Toward the Accelerated Discovery of Electroactive Materials for Li-ion and Na-ion Batteries

ASKCOS: an Open-source, Microservice-based Web App for Automatic and Interactive Synthesis Planning

Accelerating the discovery of high-index facet nanocatalysts

Novel, Automated Metrology Tools for Machine Learning and Materials Optimization

Developing an Automated Workflow for Monitoring Polymer Precipitation

Self-Driving Labs for Multiscale Polymer Research

Putting the Flexible in Flexible Automation, Adaptable Modules with Lower Parts Counts and Less Wires

Flexible AI & Automation in Self-Driving Chemistry Labs

The future lab for organic materials