Automated Optimization of Phase Change Material (PCM) Microencapsulation for Enhanced Thermal Energy Storage in Building Insulation

**Abstract:** This paper proposes an automated system leveraging multi-modal data analysis and a novel HyperScore framework to optimize the microencapsulation process of phase change materials (PCMs), specifically octadecane, for superior thermal energy storage within building insulation. The system integrates patent analysis, scientific literature review, material property datasets, and experimental simulation data to identify optimal encapsulation parameters, significantly enhancing thermal performance and long-term stability. The proposed approach underscores a 30% improvement in thermal energy storage capacity and a 20% reduction in leakage rates compared to conventional microencapsulation methods, offering a practical and scalable solution for next-generation building insulation materials.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-11
DOI
https://doi.org/10.5281/zenodo.17317269
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automated Optimization of Phase Change Material (PCM) Microencapsulation for Enhanced Thermal Energy Storage in Building Insulation

Zenodo (CERN European Organization for Nuclear Research)
Plant Water Relations and Carbon Dynamics
article

Automated Optimization of Phase Change Material (PCM) Microencapsulation for Enhanced Thermal Energy Storage in Building Insulation

article en

Abstract

**Abstract:** This paper proposes an automated system leveraging multi-modal data analysis and a novel HyperScore framework to optimize the microencapsulation process of phase change materials (PCMs), specifically octadecane, for superior thermal energy storage within building insulation. The system integrates patent analysis, scientific literature review, material property datasets, and experimental simulation data to identify optimal encapsulation parameters, significantly enhancing thermal performance and long-term stability. The proposed approach underscores a 30% improvement in thermal energy storage capacity and a 20% reduction in leakage rates compared to conventional microencapsulation methods, offering a practical and scalable solution for next-generation building insulation materials.

Zenodo (CERN European Organization for Nuclear Research)
Freed–Hardeman University (US)
Affordable and clean energy
Openalex Percentile: Top 46%
Plant Water Relations and Carbon Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Automated Optimization of Phase Change Material (PCM) Microencapsulation for Enhanced Thermal Energy Storage in Building Insulation · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS