Positron annihilation and AI-technology for creation of novel biosensors

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61389005%3A_____%2F25%3A00646754" target="_blank" >RIV/61389005:_____/25:00646754 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1088/1742-6596/3149/1/012028" target="_blank" >http://dx.doi.org/10.1088/1742-6596/3149/1/012028</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1742-6596/3149/1/012028" target="_blank" >10.1088/1742-6596/3149/1/012028</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Positron annihilation and AI-technology for creation of novel biosensors

Popis výsledku v původním jazyce

Positron annihilation lifetime spectroscopy (PALS) is a powerful tool for characterization of polymer matrixes and micro/nanocarriers for creation of novel biosensors with predicted parameters. It is found that when holding matrixes with different morphology (difference in dependences of o-Ps lifetime (free volumes) as a function of temperature) are used, then topological mechanism for effective enzyme immobilization is dominant, but when holding matrixes with the same morphology (similarity in dependences of o-Ps lifetime (free volumes) as a function of temperature) are used, then chemical mechanism for effective enzyme immobilization is preferred. Finally, a correlation of network properties of holding matrixes with parameters of amperometric biosensors is found to be universal. By applying AI-technology based on machine learning interatomic potentials (MLIPs), and specially multi-atomic cluster expansion (MACE) potential, we can efficiently screen candidate materials for specific analyte detection and optimize the functional characteristics of biosensor.

Název v anglickém jazyce

Positron annihilation and AI-technology for creation of novel biosensors

Popis výsledku anglicky

Positron annihilation lifetime spectroscopy (PALS) is a powerful tool for characterization of polymer matrixes and micro/nanocarriers for creation of novel biosensors with predicted parameters. It is found that when holding matrixes with different morphology (difference in dependences of o-Ps lifetime (free volumes) as a function of temperature) are used, then topological mechanism for effective enzyme immobilization is dominant, but when holding matrixes with the same morphology (similarity in dependences of o-Ps lifetime (free volumes) as a function of temperature) are used, then chemical mechanism for effective enzyme immobilization is preferred. Finally, a correlation of network properties of holding matrixes with parameters of amperometric biosensors is found to be universal. By applying AI-technology based on machine learning interatomic potentials (MLIPs), and specially multi-atomic cluster expansion (MACE) potential, we can efficiently screen candidate materials for specific analyte detection and optimize the functional characteristics of biosensor.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10301 - Atomic, molecular and chemical physics (physics of atoms and molecules including collision, interaction with radiation, magnetic resonances, Mössbauer effect)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Journal of Physics: Conference Series

ISBN

—

ISSN

1742-6588

e-ISSN

1742-6596

Počet stran výsledku

5

Strana od-do

012028

Název nakladatele

IOP

Místo vydání

Bristol

Místo konání akce

Takamatsu

Datum konání akce

1. 6. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001680183000014