Continuous flow synthesis of pyridinium salts accelerated by multi-objective Bayesian optimization with active learning
We report a human-in-the-loop implementation of the multi-objective experimental design
via a Bayesian optimization platform (EDBO+) towards the optimization of butylpyridinium …
via a Bayesian optimization platform (EDBO+) towards the optimization of butylpyridinium …
Deep Learning for Size‐Agnostic Inverse Design of Random‐Network 3D Printed Mechanical Metamaterials
H Pahlavani, K Tsifoutis‐Kazolis… - Advanced …, 2024 - Wiley Online Library
Practical applications of mechanical metamaterials often involve solving inverse problems
aimed at finding microarchitectures that give rise to certain properties. The limited resolution …
aimed at finding microarchitectures that give rise to certain properties. The limited resolution …
A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys
D Khatamsaz, R Neuberger, AM Roy… - npj Computational …, 2023 - nature.com
The design of materials and identification of optimal processing parameters constitute a
complex and challenging task, necessitating efficient utilization of available data. Bayesian …
complex and challenging task, necessitating efficient utilization of available data. Bayesian …
Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery
Significant acceleration of the future discovery of novel functional materials requires a
fundamental shift from the current materials discovery practice, which is heavily dependent …
fundamental shift from the current materials discovery practice, which is heavily dependent …
Multi-objective, multi-constraint high-throughput design, synthesis, and characterization of tungsten-containing refractory multi-principal element alloys
Refractory multi-principal element alloys (RMPEAs) have gained interest recently due to
their superior properties at elevated temperatures, including outstanding yield and ultimate …
their superior properties at elevated temperatures, including outstanding yield and ultimate …
Bayesian blacksmithing: discovering thermomechanical properties and deformation mechanisms in high-entropy refractory alloys
Finding alloys with specific design properties is challenging due to the large number of
possible compositions and the complex interactions between elements. This study …
possible compositions and the complex interactions between elements. This study …
Multi-fidelity Bayesian optimization of covalent organic frameworks for xenon/krypton separations
Our objective is to search a large candidate set of covalent organic frameworks (COFs) for
the one with the largest equilibrium adsorptive selectivity for xenon (Xe) over krypton (Kr) at …
the one with the largest equilibrium adsorptive selectivity for xenon (Xe) over krypton (Kr) at …
Accelerated design of solid bio-based foams for plastics substitutes
Biobased substitutes for plastics are a future necessity. However, the design of substitute
materials with similar or improved properties is a known challenge. Here we show an …
materials with similar or improved properties is a known challenge. Here we show an …
Compactness matters: Improving Bayesian optimization efficiency of materials formulations through invariant search spaces
Would you rather search for a line inside a cube or a point inside a square? Physics-based
simulations and wet-lab experiments often have symmetries (degeneracies) that allow …
simulations and wet-lab experiments often have symmetries (degeneracies) that allow …
Exploring chemistry and additive manufacturing design spaces: a perspective on computationally-guided design of printable alloys
Additive manufacturing (AM), especially Laser Powder-Bed Fusion (L-PBF), provides alloys
with unique properties, but faces printability challenges like porosity and cracks. To address …
with unique properties, but faces printability challenges like porosity and cracks. To address …