Accelerated Materials Laboratory for Sustainability's repositories
BayesProcess
Physics informed Bayesian network + autoencoder for matching process / variable / performance in solar cells.
Benchmarking
Benchmarking
SL-PerovskiteOpt
This is a code and data repository to conduct Bayesian Optimization with knowledge constraints for manufacturing process of perovskite solar cells
PvkAdditives
Hypothesis generation using combination of RFE, random forest regression/ classification, and SHAP for additives in perovskite single-crystal synthesis.
hte_degradation_chamber
High throughput degradation chamber for aging perovskite samples under extreme humidity, heat, and illumination.
PV-ML-Starter-Kit
Starter kit for photovoltaics optimization using machine learning.
Autocharacterization-Bandgap
Automatic band gap calculation of arbitrarily many semiconductor deposits from reflectance hypercube using computer vision segmentation.
Automatic-Band-Gap-Extractor
Automated direct band gap extractor from many measured reflectance samples at a time using recursive segmentation and regression fitting of Tauc plots.
cluster-perovskite-data
Clustering perovskite degradation data (sample colors vs. time) and plotting XRD for cluster centroids
dissimatrix
Dissimilarity matrix analysis for perovskite cappping-absorber pairs degradation data
hte_degradation_chamber_gen2
High throughput degradation chamber for aging perovskite samples under extreme humidity and illumination.
Archerfish
Archerfish: A Retrofitted 3D Printer for General High-throughput Combinatorial Experimentation
Autocharacterization-Stability
Automatic stability calculation of arbitrarily many semiconductor deposits from degradation experimental data using computer vision segmentation.
Robotic_Liquid_Handling
Code developed for use on Opentrons robots for automated liquid handling
BayesMC
Bayesian parameter estimation with MCMC
RGBanalysis
RGB analysis codes for film degradation chamber.
Robotic-Conductivity-Probe-Optimization
This toolkit provides robust methods for image segmentation and path planning, employing Meta AI's Segment Anything model and optimization techniques for efficient pathfinding.
tonio-presentations
Slides from Tonio Buonassisi's presentations