Maciej Harańczyk
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Transferable 3D convolutional neural networks for elastic constants prediction in nanoporous metals Open
The topology of nanoporous metals is crucial for determining their mechanical response. In this work, we generated 6,000 gold and 422 silver nanoporous structures and calculated three components of elastic modulus with Molecular Dynamics s…
View article: Genipin-crosslinked pectin hydrogels: A dual strategy for enhanced 3D printability and stability
Genipin-crosslinked pectin hydrogels: A dual strategy for enhanced 3D printability and stability Open
The development of polysaccharide-based biomaterial inks with tailored physicochemical properties and dynamic responsiveness currently attracts a lot of scientific interest. Pectin, a natural and biocompatible polysaccharide, shows great p…
Descriptor and Graph-based Molecular Representations in Prediction of Copolymer Properties Using Machine Learning Open
Copolymers are highly versatile materials with a vast range of possible chemical compositions. By using computational methods for property prediction, the design of copolymers can be accelerated, allowing for the prioritization of candidat…
A molecular dynamics study of chemistry-inspired nanoporous aluminum structures Open
Nanoporous metal structures are of high interest in both academic research and industry due to their tunable mechanical properties and light weight. However, understanding the mechanical properties of these materials is still a challenge. …
View article: Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites
Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites Open
The development of multifunctional nanocomposites for numerous applications typically requires extensive exploration of the design space, which must be reduced to accelerate discovery, lower costs, and minimize environmental impact. This s…
View article: Data-Driven Design and Green Preparation of Bio-Based Flame Retardant Polyamide Composites
Data-Driven Design and Green Preparation of Bio-Based Flame Retardant Polyamide Composites Open
This work introduces, for the first time, an innovative bio-based flame retardant (FR) system forbiocomposites, integrating experimental insights and machine learning (ML) to optimize both compositionand performance. By employing a computa…
CoRE MOF DB: a curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening Open
We present an updated version of the CoRE MOF database, which includes a curated set of computation-ready MOF crystal structures designed for high-throughput computational materials discovery. Data collection and curation procedures were i…
Streamlining Material Testing: Collaborative Robotics for Specimen Monitoring Open
The development of polymer materials for real-world applications requires careful assessment of material degradation over time and under environmental exposure. Such tests often necessitate frequent monitoring of test specimens, which can …
Streamlining material degradation testing: collaborative robotics for specimen monitoring Open
We present an experimental setup involving a collaborative robot to perform polymer material degradation experiments.
CoRE MOF DB: a curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening Open
We present an updated version of the CoRE MOF database, which includes a curated set of computation-ready MOF crystal structures designed for high-throughput computational materials discovery. Data collection and curation procedures were i…
View article: Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2019 Dataset
Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2019 Dataset Open
High-throughput computational screening of metal-organic frameworks rely on the availability of atomic coordinate files which can be used as input to simulation software packages. CoRE MOF Datasets are derived from Cambridge Structural Dat…
Streamlining Material Testing: Collaborative Robotics for Specimen Monitoring Open
The development of polymer materials for real-world applications requires careful assessment of material degradation over time and under environmental exposure. Such tests often necessitate frequent monitoring of test specimens, which can …
Model‐based reinforcement learning control of reaction‐diffusion problems Open
Mathematical and computational tools have proven to be reliable in decision‐making processes. In recent times, in particular, machine learning‐based methods are becoming increasingly popular as advanced support tools. When dealing with con…
View article: Advancing the Prediction of 3D Printability for Polymer Nanocomposites
Advancing the Prediction of 3D Printability for Polymer Nanocomposites Open
The development of new thermoplastic-based nanocomposites for, as well as using, 3D printing requires extensive experimental testing. One typically goes through many failed, or otherwise sub-optimal, iterations before finding acceptable so…
A Novel Constrained Sampling Method for Efficient Exploration in Materials and Chemical Mixture Design Open
Efficient exploration of multicomponent material composition spaces is often limited by time and financial constraints, particularly when mixture and synthesis constraints exist. Traditional methods like Latin hypercube sampling (LHS) stru…
Pellet dispensomixer and pellet distributor: Open hardware for nanocomposite space exploration via automated material compounding Open
The development of novel polymer-based nanocomposites necessitates the experimental preparation and characterization of numerous compositions to identify optimal formulations. For thermoplastic-based materials, the compounding process typi…
View article: A Novel Benchmarking Approach to Assess Fire Safety of Liquid Electrolytes in Lithium‐Ion Batteries
A Novel Benchmarking Approach to Assess Fire Safety of Liquid Electrolytes in Lithium‐Ion Batteries Open
Establishing authoritative electrolyte safety assessment methods at laboratory levels is crucial for addressing conflicts from thermal runaway of lithium‐ion batteries. However, self‐extinguishing time (SET), as the most widely used evalua…
Thermogravimetric Analysis of Moisture in Natural and Thermally Treated Clay Materials Open
Clays are a class of porous materials; their surfaces are naturally covered by moisture. Weak thermal treatment may be considered practical to remove the water molecules, changing the surface properties and making the micro- and/or mesopor…
Model-Based Reinforcement Learning Control of Reaction-Diffusion Problems Open
Mathematical and computational tools have proven to be reliable in decision-making processes. In recent times, in particular, machine learning-based methods are becoming increasingly popular as advanced support tools. When dealing with con…
Toward Diverse Polymer Property Prediction Using Transfer Learning Open
The prediction of mechanical and thermal properties of polymers is a critical aspect for polymer development. Herein, we discuss the use of transfer learning approach to predict multiple properties of linear polymers. The neural network mo…
Pellet dispensomixer and pellet distributor: open hardware for nanocomposite space exploration <i>via</i> automated material compounding Open
We present do-it-yourself instruments that can be both adopted and adapted to fit your self-driving lab.
tda-segmentor: A tool to extract and analyze local structure and porosity features in porous materials Open
Local geometrical features of a porous material such as the shape and size of a pore or the curvature of a solid ligament often affect the macroscopic properties of the material, and their characterization is necessary to fully understand …
Flame retardant properties of metal hydroxide-based polymer composites: A machine learning approach Open
With increasing the practical applications of polymeric materials, surging demands for the high-performance flame-retardant polymer composites are obvious. Accurately predicting the performance of flame-retardant materials is critical for …
View article: Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2019 Dataset
Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2019 Dataset Open
High-throughput computational screening of metal-organic frameworks rely on the availability of atomic coordinate files which can be used as input to simulation software packages. CoRE MOF Datasets are derived from Cambridge Structural Dat…
Robotically automated 3D printing and testing of thermoplastic material specimens Open
An automated platform to explore parameters for pellet-based 3D printing and characterize the samples for weight, impact strength and surface quality.