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−100−50050100−100−50050100
ENMGNP001GNP002GNP003GNP004GNP005GNP006GNP007GNP008GNP009GNP010GNP011GNP012GNP059GNP060GNP061GNP062GNP063GNP064GNP065GNP067GNP068GNP069GNP070GNP071GNP072GNP073GNP075GNP076GNP077GNP078GNP079GNP080GNP081GNP083GNP084GNP085GNP086GNP087GNP088GNP089GNP091GNP092GNP093GNP094GNP095GNP096GNP097GNP099GNP100GNP101GNP102GNP103GNP104GNP105GNP106GNP107GNP108GNP109GNP110GNP111GNP112GNP113GNP114GNP115GNP116GNP117GNP118GNP119GNP120GNP121GNP122GNP123GNP124GNP125GNP126GNP127GNP128GNP129GNP130GNP131GNP132GNP133GNP134GNP135GNP136GNP137GNP138GNP139GNP140GNP141GNP142GNP143GNP144GNP145GNP146GNP281GNP282GNP283GNP284GNP285GNP286GNP287GNP288GNP322GNP323GNP324GNP325GNP372GNP373GNP374GNP386GNP387GNP388GNP389GNP393GNP394GNP395GNP396GNP397GNP398GNP401GNP404GNP405GNP406GNP407GNP408GNP409GNP411GNP412GNP413GNP414AgNP001AgNP002AgNP003AgNP004AgNP005AgNP006PtNP001PtNP002PtNP003PtNP004PtNP005PtNP006PtNP007PtNP008PtNP009PtNP010PtNP011PdNP001PdNP002PdNP003PdNP004PdNP005PdNP006PdNP007PdNP008PdNP009PdNP010PdNP011MONP013MONP014MONP015MONP016MONP017MONP018MONP019QDNP001QDNP002QDNP003QDNP004QDNP005QDNP006QDNP007QDNP008QDNP009QDNP010QDNP011QDNP012QDNP016QDNP017QDNP025QDNP026QDNP027QDNP028QDNP029QDNP030QDNP031Dendrimer001Dendrimer002Dendrimer003Model for Nanomaterials with NanoAID-16ExperimentPrediction

1. Model Data

2. Model Deployment for Prediction

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3. Model Description

This is a partial least squares regression (PLSR) model for NanoAID-16 (Zeta Potential in Water).
The model was developed using a training set of 190 nanomaterials (NMs) and employed a leave-one-out cross-validation procedure. Additionally, it was validated with a validation set of 23 NMs. The model's coefficient of determination (R2) for the training set is 0.798, and it has a root mean squared error (RMSE) of 13.627. For the validation set, the R2 value is 0.625, with an RMSE of 14.530. The zeta potential of NMs were measured in a Malvern Nano Z Zetasizer by suspending NMs in Millipore water PH=7.