# Evaluation and optimization of PCM-integrated walls: Energy, exergy, environmental, and economic perspectives

Qianwen Tan, Monica Siroux

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Qianwen Tan, Monica Siroux. Evaluation and optimization of PCM-integrated walls: Energy, exergy, environmental, and economic perspectives. Renewable and Sustainable Energy Reviews, 2025, 222, pp.115922. 10.1016/j.rser.2025.115922. hal-05132422

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# Evaluation and optimization of PCM-integrated walls: Energy, exergy, environmental, and economic perspectives

Qianwen Tan *, Monica Siroux

INSA Strasbourg, ICUBE Laboratory, University of Strasbourg, Strasbourg, 67000, France

## ARTICLE INFO

### Keywords:

Renewable energy

Exergy efficiency

Environmental

Economic

Multi-objective optimization

Phase change materials

## ABSTRACT

Phase Change Materials (PCM) is a promising solution for thermal energy storage, offering significant potential to enhance the efficiency of renewable energy systems, reduce energy consumption, and support sustainable energy practices in nearly zero-energy buildings (NZEB). While extensive research has examined the energy performance of PCM-integrated walls, a comprehensive evaluation that simultaneously considers energy efficiency, exergy performance, carbon footprint, and economic feasibility remains limited. This review addresses this gap by assessing the current status and applicability of the Energy, Exergy, Environmental, and Economic (4E) analysis for PCM-integrated walls and identifying key evaluation metrics and methodologies. Additionally, multi-objective optimization is explored to determine the optimal configuration of PCM-integrated walls, addressing trade-offs among the 4E objectives. Furthermore, the review emphasizes the growing role of artificial intelligence (AI) in enhancing multi-objective optimization within the 4E framework. Findings indicate that PCM-integrated walls can reduce annual energy use by 13–50 %, enhance exergy efficiency by up to 50 %, and lower total environmental impact by roughly 12–34 %. Payback periods are generally greater than 5 years. Notably, the combination of smart control systems with PCM-integrated walls can further enhance exergy performance by an additional 5–50 %. This review serves as a valuable reference for advancing the application of PCM in sustainable building wall design, thus contributing to the broader adoption of renewable energy strategies.

## Nomenclature

### Latin Letters

<table><tr><td>A</td><td>Area of glass cover</td><td>m<sup>2</sup></td></tr><tr><td>Cp</td><td>Specific heat capacity</td><td>J/K</td></tr></table>

<table><tr><td>c</td><td>Unit cost</td><td>kg-K</td></tr></table>

<table><tr><td>E</td><td>Energy</td><td>J</td></tr><tr><td>Ex</td><td>Exergy</td><td>J</td></tr></table>

<table><tr><td>m</td><td>Mass</td><td>kg</td></tr><tr><td>S</td><td>Entropy generation</td><td>J/K</td></tr></table>

<table><tr><td>t</td><td>Time</td><td>s</td></tr><tr><td>Ẇ</td><td>Work rate (power)</td><td>W</td></tr></table>

<table><tr><td>ĒĒ</td><td>Exergy rate of the system</td><td>W</td></tr><tr><td>Z</td><td>Non-energetic cost rate</td><td>$/h</td></tr></table>

<table><tr><td>C</td><td>Cost rate</td><td>$/h</td></tr></table>

<table><tr><td>η<sub>ex</sub></td><td>Exergy efficiency</td><td>—</td></tr><tr><td>λ</td><td>Thermal conductivity</td><td>W/m-K</td></tr></table>

(continued on next column)

(continued)

### Subscripts and Superscripts

amb Ambient condition —

a Air flow in channel —

destroyed Exergy destruction —

emitted Emitted to the environment —

F Fuel —

gen Generation —

input/in Input of the system —

o Properties at the restricted dead state —

output/out Output of the system —

pcm Phase change material —

pi Products in the system —

q,k Heating energy —

sun Solar —

p,tot Product totally —

w,k Power energy —

### Abbreviations

AI Artificial intelligence —

BIPV Typical solar ventilation wall —

(continued on next page)

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: qianwen.tan@etu.unistra.fr (Q. Tan).</footnote>
(continued)

<table><tr><td>BIPV-dPCM</td><td>Building-integrated photovoltaic system integrated a double-layer PCM</td><td>-</td></tr><tr><td>DPP</td><td>Dynamic investment payback period</td><td>-</td></tr><tr><td>DSPVW-PV/ PCM</td><td>Novel dual-channel solar photocatalytic ventilation wall integrated with PV and PCM</td><td>-</td></tr><tr><td>4E</td><td>Energy, Exergy, Environmental, Economic</td><td>-</td></tr><tr><td>EPBT</td><td>Energy payback time</td><td>-</td></tr><tr><td>EC</td><td>Electricity consumption</td><td>-</td></tr><tr><td>Exp</td><td>Experimental</td><td>-</td></tr><tr><td>FVBE-PV/ PCM</td><td>Ventilation wall incorporating PV and PCM</td><td>-</td></tr><tr><td>FVBE-PV</td><td>PV ventilation wall without PCM</td><td>-</td></tr><tr><td>GA</td><td>Genetic Algorithms</td><td>-</td></tr><tr><td>GCE</td><td>Global carbon emissions</td><td>-</td></tr><tr><td>HDPE</td><td>High-density polyethylene</td><td>-</td></tr><tr><td>LCA</td><td>Life Cycle Assessment</td><td>-</td></tr><tr><td>LCCA</td><td>Life Cycle Cost Analysis</td><td>-</td></tr><tr><td>LCC</td><td>Life-cycle cost</td><td>-</td></tr><tr><td>LWA</td><td>Lightweight aggregates</td><td>-</td></tr><tr><td>MOO</td><td>Multi-objective optimization</td><td>-</td></tr><tr><td>ML</td><td>Machine Learning</td><td>-</td></tr><tr><td>MOWOA</td><td>Multi-Objective Whale Optimization Algorithm</td><td>-</td></tr><tr><td>MSSA</td><td>Multi-Objective Slap Swarm Algorithm</td><td>-</td></tr><tr><td>Num</td><td>Numerical</td><td>-</td></tr><tr><td>NZEB</td><td>Nearly Zero-Energy Buildings</td><td>-</td></tr><tr><td>NSGA-II</td><td>Non-dominated Sorting Genetic Algorithm II</td><td>-</td></tr><tr><td>NLCS</td><td>Net life-cycle cost saving</td><td>-</td></tr><tr><td>ANN</td><td>Artificial Neural Networks</td><td>-</td></tr><tr><td>PCM</td><td>Phase Change Materials</td><td>-</td></tr><tr><td>PCM-FC</td><td>PCM-foam concrete</td><td>-</td></tr><tr><td>PU</td><td>Polyurethane</td><td>-</td></tr><tr><td>PV</td><td>Photovoltaic</td><td>-</td></tr><tr><td>PSO</td><td>Particle Swarm Optimization</td><td>-</td></tr><tr><td>PESA-II</td><td>Pareto Envelope-based Selection Algorithm II</td><td>-</td></tr><tr><td>RSM</td><td>Response Surface Method</td><td>-</td></tr><tr><td>SPP</td><td>Static payback period</td><td>-</td></tr><tr><td>SPVW-PV/ PCM</td><td>Solar composite ventilation wall combined with PV and PCM</td><td>-</td></tr><tr><td>SSPCM</td><td>Shape-stabilized PCM</td><td>-</td></tr><tr><td>SPEA-II</td><td>Strength Pareto Evolutionary Algorithm II</td><td>-</td></tr><tr><td>TSCs</td><td>Transpired solar collectors</td><td>-</td></tr><tr><td>TMS</td><td>Thermal management systems</td><td>-</td></tr><tr><td>VIPs</td><td>Vacuum insulation panels</td><td>-</td></tr><tr><td>VDSF</td><td>Ventilated double skin facades</td><td>-</td></tr></table>

# 1. Introduction

The rapidly increasing demand in the building sector has led to massive energy consumption. According to the International Energy Agency (IEA) [1], buildings accounted for 27.91 % of global final energy consumption in 2023, as shown in Fig. 1. Thus, the building sector has emerged as a major contributor to energy consumption. Energy in buildings is mainly used for a variety of purposes including heating, cooling, lighting, and ventilation [2,3]. In response, the European Union (EU) proposed the directive for Nearly Zero-Energy Buildings (NZEB) in 2010, requiring all new buildings to achieve nearly zero-energy status by the end of 2020. To accelerate this transition, the Energy Performance of Buildings Directive was revised again, proposing to shift from nearly zero-energy buildings to zero-emission buildings by 2030 [4]. Minimizing building energy demand is crucial for achieving NZEB. This objective can be attained through energy-efficient building envelopes, high-efficiency systems, integration of energy storage and advanced energy management and control systems [5].

Among various energy-efficient technologies, the integrated Phase Change Materials (PCM) in buildings to improve energy efficiency and reduce overall energy consumption has gained significant attention [6]. PCM can absorb and release thermal energy during phase transitions [7]. These materials absorb substantial thermal energy from the surrounding environment as they transition from solid to liquid during melting. Conversely, when freezing, this absorbed thermal energy is

<figure><img src="image_4.png" /><figcaption>Fig. 1. Final energy consumption by sector all over the world.</figcaption></figure>

<caption>Table 1</caption>

Summary of selected studies on PCM-integrated walls based on 4E evaluations.

<table><thead><tr><th>Ref</th><th>Type</th><th>Energy</th><th>Exergy</th><th>Environmental</th><th>Economic</th><th>4E</th></tr></thead><tbody><tr><td>2025 [35]</td><td>Review</td><td>✓</td><td>×</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2025 [36]</td><td>Review</td><td>✓</td><td>×</td><td>✓</td><td>✓</td><td>×</td></tr><tr><td>2025 [37]</td><td>Research</td><td>✓</td><td>×</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2025 [38]</td><td>Research</td><td>✓</td><td>✓</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2025 [39]</td><td>Research</td><td>✓</td><td>×</td><td>×</td><td>✓</td><td>×</td></tr><tr><td>2025 [40]</td><td>Research</td><td>✓</td><td>×</td><td>✓</td><td>✓</td><td>×</td></tr><tr><td>2024 [41]</td><td>Review</td><td>✓</td><td>×</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2024 [42]</td><td>Research</td><td>✓</td><td>×</td><td>✓</td><td>✓</td><td>×</td></tr><tr><td>2024 [43]</td><td>Research</td><td>✓</td><td>✓</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2024 [44]</td><td>Research</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>2024 [45]</td><td>Research</td><td>✓</td><td>✓</td><td>×</td><td>✓</td><td>×</td></tr><tr><td>2023 [46]</td><td>Research</td><td>✓</td><td>×</td><td>✓</td><td>✓</td><td>×</td></tr><tr><td>2023 [18]</td><td>Review</td><td>✓</td><td>×</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2023 [47]</td><td>Research</td><td>✓</td><td>×</td><td>×</td><td>✓</td><td>×</td></tr><tr><td>2023 [48]</td><td>Research</td><td>✓</td><td>×</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2022 [49]</td><td>Review</td><td>✓</td><td>×</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2022 [50]</td><td>Research</td><td>✓</td><td>×</td><td>✓</td><td>✓</td><td>×</td></tr><tr><td>2022 [51]</td><td>Research</td><td>✓</td><td>✓</td><td>×</td><td>×</td><td>×</td></tr><tr><td>2022 [52]</td><td>Research</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr></tbody></table>

released as latent heat or crystallization energy [8]. Due to these unique properties, PCM have applications in buildings [9,10], electronics [11, 12], textiles and clothing [13]. Buildings represent one of the primary application areas actively developed for PCM. PCM can be applied passively (incorporated into building elements) or actively (combined with other systems) to manage the building temperature, significantly contributing to occupant comfort [14,15].

Numerous studies have demonstrated the significant thermal energy storage capacity of PCM in building envelopes [16–20], highlighting their potential to enhance energy management and contribute to the realization of NZEB. Under the initial NZEB concept, research has extended to economic and environmental analyses, typically using simple payback periods and embodied energy metrics. However, these assessments no longer align fully with the latest definitions of NZEB, as conventional energy evaluations neglect the irreversibility of energy storage and recovery processes [21]. This limitation can be addressed by applying the second law of thermodynamics through exergy analysis, providing a comprehensive understanding of system performance by assessing both energy quality and quantity, thus facilitating scientifically informed system design and optimization [22].

Exergy analysis has been widely applied in various energy systems, including power generation [23], thermal processes [24], and fuel
<figure><img src="image_5.png" /><figcaption>Fig. 2. Schematic overview of this review.</figcaption></figure>

processing [25,26], as well as renewable energy systems [27]. More recently, integrated exergy-based methods such as exergoenvironmental and exergoeconomic analyses have emerged. These methods combine exergy with environmental [26] and economic criteria as new evaluation metrics, respectively, and have garnered significant attention, particularly in complex energy systems such as natural gas processing [28–31], where thermodynamic efficiency and sustainability must be balanced. Building upon these developments, researchers have applied integrated exergy frameworks to the built environment, proposing new NZEB concepts [32–34]. These include Net-Zero Exergoeconomic Buildings (NZXEB), Net-Zero Exergoenvironmental Buildings (NZXNB), and Net-Zero Extended Exergy Buildings (NZZEB). The NZZEB approach, in particular, encompasses social, labor, economic, energetic, and environmental aspects through its exergetic footprint [32], offering a more holistic approach to sustainable building design.

To systematically illustrate this research gap, Table 1 summarizes selected studies from 2023 to 2025 on PCM-integrated walls, categorized by their inclusion of energy, exergy, environmental, and economic evaluations. Most studies focus primarily on energy performance, with only about 30 % including exergy analyses. Only two studies achieved comprehensive 4E (Energy, Exergy, Environmental, and Economic) evaluations, emphasizing a significant research gap. Furthermore, although multi-objective optimization methods are increasingly applied in building energy research, their application in PCM-integrated walls remains underexplored. Existing studies typically optimize single metrics, such as energy savings or economic feasibility, without addressing the interactions among energy efficiency, exergy efficiency, economic feasibility, and environmental trade-offs. An optimal PCM configuration for NZEB requires a multi-objective approach balancing these competing factors. The absence of systematic reviews on multi-objective optimization strategies for PCM-integrated walls represents a critical gap in the

literature.

This review addresses these gaps by integrating a holistic 4E framework, providing a systematic and comprehensive evaluation of PCM applied in building walls for NZEB. Recent studies are systematically reviewed to identify key optimization strategies and their potential for enhancing NZEB implementation. Accordingly, research trends in PCM applications are discussed in Section 2. PCM classification and integration methods are summarized in Section 3. Recent advancements in PCM application in building walls based on an energy analysis are classified and discussed in Section 4. Exergy-based evaluations are presented in Section 5. Environmental implications, specially LCA analysis, are discussed in Section 6, and economic feasibility is analyzed in Section 7. Multi-objective optimization methods are explored in Section 8. Finally, recommendations for future development of PCM-integrated walls are proposed in Section 9. The schematic structure of core analytical sections is illustrated in Fig. 2, highlighting Sections 2-8, including research trends, PCM classification, performance analysis, and optimization. Introduction, recommendations, and conclusions are excluded from this diagram for clarity. The findings of this review will serve as a reference for researchers and practitioners aiming to optimize PCM use in building walls.

## 2. Emerging trends and novel contributions

### 2.1. *Emerging trends*

Analyzing PCM application in buildings from a historical development viewpoint is essential for systematically identifying research trends. A comprehensive analysis of the quantity of research articles within this field also facilitates a precise assessment of its development trajectory. Therefore, the number of articles published in the Web of
<figure><img src="image_6.png" /><figcaption>Fig. 3. Flow diagram of data collection.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 4. Number of papers in PCM published annually.</figcaption></figure>

Science database was analyzed in this section. The search terms ‘phase change material’ and ‘building’ were selected, refined by the meso-level citation topics ‘thermodynamics and ‘sustainability’, and the micro-level topics ‘phase change material’ and ‘thermal comfort’. A total 5607 articles satisfied these criteria as of February 28, 2025 (Fig. 3). The annual publication count is showed in Fig. 4.

As shown in Fig. 4, the earliest study on PCM applications in buildings dates back to 1991, marking approximately 30 years of development in this research area. A significant increase in publications is evident post-2010, indicating intensified research activity in recent years. The number of publications peaked in 2024, with a total of 693 articles, including over 600 research articles and 59 review articles published. This growth highlights a rising interest in PCM applications in buildings.

Over recent decades, PCM extensively studied for use in different building components, including walls, floors, windows, ceilings and roofs [9]. Research emphases vary across different components. The distribution of PCM research across these building components is shown in Fig. 5, including only research and review articles. Around 1400

<figure><img src="image_8.png" /><figcaption>Fig. 5. Distribution of different building components with PCM.</figcaption></figure>

articles had been published on PCM in walls up to 2025, with publications focused on walls exceeding those of other building elements by a factor of five to six. This impressive number indicates great research interest and commercial potential in PCM applications for walls. Additionally, the noticeable gap between review and research articles suggests a critical need for a comprehensive literature review.

Among the existing literature on PCM-integrated walls, paraffin-based and salt-hydrate PCM dominate experimental and modelling studies. Paraffins [53] have historically attracted greater attention due to suitable phase-change temperatures and chemical stability. However, recent lifecycle and economic assessments indicate that salt-hydrate PCM [54–56] are generally more cost-effective and environmentally beneficial, rendering them particularly suitable for large-scale applications. These differing advantages emphasize the necessity of evaluating PCM performance using multiple criteria rather than relying solely on thermal performance metrics. Hence, a holistic review considering energy, exergy, environmental, and economic factors is crucial to align material selection and system design with project-specific goals and climatic conditions.
<table><caption>**Table 2**
Summary of review articles related to PCM applied in buildings.</caption><thead><tr><td>Research Focus</td><td>Year</td><td>Scope</td></tr></thead><tbody><tr><td>Passive building thermal management with PCM</td><td>2025 [57]</td><td>Wall, performance factors, wall type, encapsulation methodologies.</td></tr><tr><td>PCM integration in brick walls</td><td>2025 [41]</td><td>Incorporation methods, parameter optimization, application.</td></tr><tr><td>Macro-encapsulation of PCM for buildings</td><td>2024 [58]</td><td>Space and water heating/cooling, renewable energy integration, and advanced control systems.</td></tr><tr><td>Salt hydrate PCM in building energy storage systems</td><td>2024 [59]</td><td>Optimization methodologies and bolstering mechanisms.</td></tr><tr><td>Bio-based PCM for passive thermal storage</td><td>2023 [60]</td><td>Thermophysical properties, integration techniques, lifetime impacts.</td></tr><tr><td>Salt hydrate PCM</td><td>2023 [61]</td><td>Physical property regulation, applications.</td></tr><tr><td>PCM for construction materials</td><td>2022 [62]</td><td>Characteristics, incorporation methods, thermal performance, applications.</td></tr><tr><td>MXene-based PCM in thermal energy storage</td><td>2022 [63]</td><td>Synthesized techniques, applications.</td></tr><tr><td>PCM embedded radiant chilled ceiling</td><td>2021 [64]</td><td>Peak load shifting, energy savings, and indoor thermal comfort.</td></tr><tr><td>PCM in building walls</td><td>2021 [65]</td><td>Integration techniques, research method.</td></tr><tr><td>PCM for cooling applications</td><td>2020 [66]</td><td>Active and passive systems.</td></tr><tr><td>PCM foam composites</td><td>2020 [67]</td><td>Production methods, insulations and application.</td></tr><tr><td>Passive and active PCM integrated building energy systems</td><td>2020 [68]</td><td>Heating, cooling and electrical system with advanced machine-learning.</td></tr></tbody></table>

## 2.2. Novel contributions

To ensure that this review meaningfully contributes to ongoing research published in *Renewable and Sustainable Energy Reviews*, an initial analysis of relevant review articles from this journal was conducted to identify existing research gaps and emerging trends. Additional review articles from other leading journals were also analyzed to provide a broader perspective. Table 2 summarizes selected reviews from the past five years related to PCM applications in buildings.

These reviews cover a broad range of PCM applications, including cooling systems, wall integration and advanced AI-driven optimization techniques. Each review highlights different aspects of PCM, with some focusing on specific applications (e.g., wall, radiant ceilings, foam composites), while others explore broader systems like cooling or heating management. Furthermore, research on PCM-integrated buildings primarily emphasizes energy performance. Few of the existing

reviews simultaneously focus on the energy, exergy, environmental, and economic performance of PCM applications. This observation underscores the novelty and comprehensiveness of the present review, which not only fills a critical gap within *Renewable and Sustainable Energy Reviews* journal but also broadly to the research on PCM-integrated buildings.

# 3. Description of PCM

## 3.1. Classification

PCM can absorb and release thermal energy during the process of transforming physical properties. They can be classified into four groups based on the phase change state: solid-gas, solid-liquid, liquid-gas and solid-solid PCM [69,70]. Among these, solid-liquid PCM are predominantly used in buildings due to their high latent heat storage capacity,

<figure><img src="image_9.png" /><figcaption>**Fig. 6.** The classification of PCM.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Fig. 7. Classification of integration method.</figcaption></figure>

availability, and ease of implementation. Based on their nature and source, solid-liquid PCM can be classified into three main categories: organic, inorganic, and eutectic PCM, as shown in Fig. 6, and reviewed in detail below.

### 3.1.1. Organic PCM

Organic PCM are the most commonly used materials in buildings for thermal storage [18] due to their extensive temperature range. Even though organic PCM have a lot of disadvantages, they suffer from the common problem of low thermal conductivity [71], large volume change and flammability. Organic PCM can be classified into two main group: paraffins and non-paraffins, with non-paraffins typically including fatty acids, stearyl and alcohol.

Currently, the most common solid-liquid PCM in building application is paraffin PCM. On the one hand, the paraffin PCM have wide phase change temperature, high thermal energy storage density and small volume change during phase transitions. On the other hand, the low cost and low vapor pressure make it commercialized on a large scale. Paraffin are hydrocarbons with the general formula $C_nH_{2n+2}$, obtained through petroleum refining [72]. However, petroleum is non-renewable, and extensive paraffin PCM use may raise energy consumption and environmental concerns. So, bio-based PCM, derived from renewable plant and animal fats [19], have emerged as a suitable alternative to

paraffin-based PCM, aligning better with the objectives of NZEB.

### 3.1.2. Inorganic PCM

Compared to organic PCM (thermal conductivity ~0.2 W/(m·K) [73]), inorganic PCM generally offer higher thermal conductivity (~0.5 W/(m·K)), lower volume changes, and lower costs. However, inorganic PCM include salt, hydrated salts, metal compound, and metal alloy. Especially, hydrated salts are the most attracted for building applications.

Hydrated salts consist of salts combined with water in fixed ratios, offering economic and environmental advantages and high thermal storage capacities. Nevertheless, when hydrated salts undergo phase transition, it is easy for salt and water to separate out, reducing thermal energy storage. To address this issue, Zeng et al. [74] designed a composite PCM using $CaCl_2·6H_2O/EG$ with KCl as a modifier and Sr($OH)_2·8H_2O as a nucleating agent, effectively mitigating phase segregation and super cooling while enhancing thermal conductivity.

### 3.1.3. Eutectic PCM

Eutectic PCM typically include organic-organic, inorganic-inorganic, and organic-inorganic. They consist of mixtures comprising two or more components [65] that melt and solidify at a single lower temperature
<table><caption>**Table 3**
Comparison of different integration method of PCM [18,65,77,78].</caption><thead><tr><th>Method</th><th>Advantage</th><th>Disadvantage</th></tr></thead><tbody><tr><td>Direct incorporation</td><td><ul><li>Easiest</li><li>Most economical</li></ul></td><td><ul><li>PCM leakage</li><li>Incompatibility with aggregate</li><li>Mechanical properties affected</li><li>Hydration process affected</li></ul></td></tr><tr><td>Impregnation</td><td><ul><li>Simple and feasible</li><li>Uniform distribution</li></ul></td><td><ul><li>More expensive</li><li>Same as direct incorporation</li></ul></td></tr><tr><td>Encapsulation</td><td><ul><li>Preserves base material strength</li><li>Improved heat transfer rate</li><li>Higher PCM content</li><li>Reduced PCM volume change</li><li>Avoids leakage</li><li>Heat exchange at constant temperature</li><li>High heat transfer per volume</li><li>Higher heat transfer</li><li>Reduced reactivity</li><li>Same support used for store/transport</li><li>Better cooling</li><li>Good compatibility</li><li>Chemical stability</li><li>Improved thermal reliability</li><li>Prevented PCM leakage</li></ul></td><td><ul><li>Corrosion</li><li>Requires protection</li><li>Low thermal conductivity</li><li>Complex installation</li><li>Mechanical properties affected</li><li>Higher cost</li><li>Limited convection</li><li>Lower total heat storage capacity</li></ul></td></tr><tr><td>Stabilized PCM</td><td><ul><li>Nano-<ul><li>Same as micro-encapsulation</li><li>Enhanced material properties</li><li>No need for external container</li><li>Good thermal conductivity</li><li>Thermal stability</li><li>Reduce leakage rate</li></ul></li></ul></td><td><ul><li>Highest cost</li><li>More complex fabrication</li><li>Difficult control</li><li>Reduced heat storage density</li><li>Complex fabrication process</li><li>High cost</li></ul></td></tr></tbody></table>

compared to their individual melting points [62,75]. Researcher can control phase-change temperature by adjusting eutectic PCM compositions (component ratios and types). Besides, eutectic PCM generally exhibit slightly higher volumetric thermal storage density compared to organic PCM. Despite their potential benefits, eutectic PCM remain relatively less explored in building applications, resulting in limited data availability.

## 3.2. Integration method of PCM

Choosing an appropriate PCM integration method significantly impacts thermal performance, durability, and system effectiveness. A systematic classification of integration techniques assists optimal application of different PCM types, addressing challenges like leakage, thermal conductivity limitations, and long-term stability. PCM integration methods in buildings are discussed below, with classifications [65, 76] illustrated in Fig. 7. PCM incorporation methods are categorized into four categories: direct incorporation, impregnation (including immersion and vacuum methods), encapsulation (macro-, micro-, and nano-encapsulation), and stabilized PCM systems (shape-stabilized and

form-stable composites). Each method exhibits specific advantages and disadvantages, which are summarized in Table 3. To facilitate quantitative comparison, the key thermophysical properties reported for representative studies are compiled side-by-side in Table 4. The most suitable integration method can then be selected according to the performance targets and boundary conditions of a given application.

### 3.2.1. Direct incorporation

Direct incorporation is the easiest and most economical PCM integration method [65], involving mixing PCM directly with building material during manufacturing. An example includes cellulose insulation mixed with paraffin-based PCM as insulation layers [79], which reduced daily average peak heat flux by approximately 25.4 %.

### 3.2.2. Impregnation

#### 3.2.2.1. Immersion.
Porous materials (e.g., bricks, concrete, plaster, wood boards) absorb liquid PCM through capillary action or pressure differences during immersion. Boussaba et al. [81] incorporated coconut fat into matrix to fabricate a composite PCM by immersion. The results showed that the composite PCM was suitable for application in walls due to its good thermal stability and lack of chemical degradation risks. Subsequently, it was structured as a sandwich panel and applied to the external walls of building envelopes for passive thermal energy storage. Additionally, ceramsite [97] can act as a porous carrier that absorbs and retains paraffin PCM. The ceramsite was then used in mortar, resulting in a homogenous distribution of the PCM throughout the wall structure. The results showed that the average heat transfer resistance of the PCM-wall was 2.04 times greater than that of an ordinary mortar-coated wall.

#### 3.2.2.2. Vacuum impregnation.
Vacuum impregnation and immersion are often used interchangeably in the context of integrating PCM into building materials, but nuanced differences exist between the two. In vacuum impregnation, a vacuum is applied to the system to accelerate the absorption of liquid PCM [65]. This method ensures that the PCM can store sufficient heat once incorporated. The effectiveness of this process is attributed to capillary action and surface tension forces that occur during incorporation [98]. Microscopic images from the study of Nomura et al. [99] demonstrated that the PCM was well impregnated into the porous material under vacuum conditions.

### 3.2.3. Encapsulation

Encapsulation is the process of covering the PCM (which forms the core) with a suitable coating or shell material [100]. It is one of the most commonly used PCM integration methods. Encapsulated PCM can be classified into three types based on the size of shell: (1) Macro-encapsulation (diameter above 1 mm); (2) Micro-encapsulation (diameter from 1 to 1000 µm); (3) Nano-encapsulation (diameter from 1 to 1000 nm).

#### 3.2.3.1. Macro-encapsulation.
Currently, macro- and micro-encapsulation are the most commonly method in building applications. Many studies [10,101] have adopted macro-encapsulated PCM for buildings due to their greater flexibility in application compared to other encapsulation techniques. Based on their geometry shapes, macro-encapsulation forms can be classified into three categories: cylindrical [102,103], spherical [104], and rectangular [105], with the rectangular form being the most widely used in building walls. In terms of encapsulation materials, metal containers [106,107] and pouches made from plastic foil or white plastic sheeting [108] are commonly used. Metal containers are particularly suitable for macro-encapsulation due to their favorable thermal performance. Additionally, epoxy resin or styrene-acrylic emulsion used to seal PCM/lightweight aggregates (LWA) can also be considered a form of macro-encapsulation method
<table><caption>**Table 4**
Key thermophysical metrics of representative PCM-integrated wall composites for each integration method.</caption><thead><tr><th rowspan="2">Method</th><th rowspan="2">Ref</th><th rowspan="2">PCM</th><th colspan="2">Latent heat (J/g)</th><th rowspan="2">Thermal conductivity (W/mK)</th><th rowspan="2">Note</th></tr><tr><th>PCM</th><th>Composite</th></tr></thead><tbody><tr><td>Direct incorporation</td><td>[79]</td><td>Paraffin</td><td>147</td><td>60.45</td><td>0.2</td><td>Sprayed in cellulose</td></tr><tr><td>Direct incorporation</td><td>[80]</td><td>Fatty-acid ester</td><td>134.16</td><td></td><td>-</td><td>Added in mixture</td></tr><tr><td rowspan="2">Immersion</td><td>[81]</td><td>Coconut fat</td><td>106.17 (m)<br>107.34 (f)</td><td>59.10 (m)<br>60.72 (f)</td><td>1.06</td><td>Composite immersed in PCM</td></tr><tr><td>[82]</td><td>CaCl<sub>2</sub></td><td>150</td><td>-</td><td>-</td><td>Impregnated concrete</td></tr><tr><td>Immersion</td><td>[82]</td><td>PureTemp 25</td><td>187</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Vacuum</td><td>[82]</td><td>CaCl<sub>2</sub></td><td>150</td><td>22.5</td><td>-</td><td>Impregnated concrete</td></tr><tr><td>Vacuum</td><td>[82]</td><td>PureTemp 25</td><td>187</td><td>19.45</td><td>-</td><td>-</td></tr><tr><td>Vacuum</td><td>[83]</td><td>RT25HC</td><td>200</td><td>-</td><td>0.2</td><td>Aggregate impregnated</td></tr><tr><td>Vacuum</td><td>[84]</td><td>Capric (CA)-palmitic acid (PA) eutectic mixture</td><td>170.12</td><td>56.45</td><td>-</td><td>PCM mixed with pumice (PUM)</td></tr><tr><td>Vacuum</td><td>[84]</td><td>Heptadecane (HEPD)</td><td>228.89</td><td>72.38</td><td>-</td><td>PUM</td></tr><tr><td>Vacuum</td><td>[84]</td><td>Dodecanol (DD)</td><td>205.88</td><td>67.32</td><td>-</td><td>PUM</td></tr><tr><td rowspan="2">Macro-</td><td>[85]</td><td>CaCl<sub>2</sub>-6H<sub>2</sub>O/PVC container</td><td>122.3 (m)<br>116.9 (f)</td><td></td><td>-</td><td>Wallboard</td></tr><tr><td>[86]</td><td>BioPCM/pouch container</td><td>223</td><td></td><td>0.25</td><td>Wall panels</td></tr><tr><td>Macro-</td><td>[86]</td><td>Hydrate-salts/pouch container</td><td>188</td><td></td><td>0.50</td><td>Wall panels</td></tr><tr><td rowspan="2">Macro-</td><td>[87]</td><td>Lauryl alcohol- LWA/epoxy coat</td><td>206.5 (m) 204.8<br>(f)</td><td>100.6 (m)<br>100.9 (f)</td><td>0.615</td><td>Encapsulated concrete</td></tr><tr><td>[87]</td><td>Lauryl alcohol- LWA/cement coat</td><td>206.5 (m) 204.8<br>(f)</td><td>-</td><td>0.738</td><td>Encapsulated concrete</td></tr><tr><td>Micro-</td><td>[88]</td><td>Plant-based feedstocks/acrylic polymer shell</td><td>175</td><td>-</td><td>0.6</td><td>Mixed with cement</td></tr><tr><td>Micro-</td><td>[89]</td><td>Sodium phosphate dodecahydrate/SiO<sub>2</sub></td><td>177.0</td><td>-</td><td>0.50</td><td>-</td></tr><tr><td rowspan="2">Micro-</td><td>[90]</td><td>Branched-chain hydrocarbon mixtures/melamine-formaldehyde shell</td><td>190</td><td>51.1</td><td>0.1041</td><td>Mixed with wood fiber-starch</td></tr><tr><td>[91]</td><td>Polyethylene glycol/SiO<sub>2</sub> shell</td><td>108.4</td><td>66.24</td><td>-</td><td>-</td></tr><tr><td rowspan="2">Shape-stabilized</td><td>[92]</td><td>Paraffin (hexadecane and octadecane)/ polypropylene and elastomer</td><td>62.24</td><td></td><td>0.12</td><td>Wall panels</td></tr><tr><td>[93]</td><td>Paraffin/HDPE and expanded graphite powder</td><td>150.7</td><td></td><td>0.8</td><td>Wall panels</td></tr><tr><td>Form-stable composite</td><td>[94]</td><td>Binary eutectic hydrate salt (EHS)/expanded graphite oxide (EHS/EG)</td><td>-</td><td>195.0</td><td>0.90</td><td>Incorporated in cement</td></tr><tr><td>Form-stable composite</td><td>[94]</td><td>EHS/poly (acrylamide-co-acrylic acid) copolymer (EHS/P(AA-AA))</td><td>-</td><td>189.1</td><td>0.77</td><td>Incorporated in cement</td></tr><tr><td>Form-stable composite</td><td>[95]</td><td>Paraffin/diatomite</td><td>165.59 (m)<br>170.76 (f)</td><td>70.51(m)<br>71.96 (f)</td><td>1.34</td><td>Paraffin vs. Composite</td></tr><tr><td>Form-stable composite</td><td>[96]</td><td>Lauric acid/Expanded perlite</td><td>-</td><td>93.36 (m)<br>94.87 (f)</td><td>0.07</td><td>-</td></tr></tbody></table>

[109,110]. This approach effectively prevents PCM leakage, as demonstrated in thermal cycling tests, where epoxy-coated lauryl alcohol/LWA endured 150 cycles with only minimal changes in phase-change temperature and latent heat storage [87]. Furthermore, some studies [111, 112] have employed geopolymer coatings or cementitious paste as alternative sealing materials to improve compatibility with concrete.

### 3.2.3.2. Micro-encapsulation.
Due to their smaller size compared to macro-encapsulation, micro-encapsulation methods are generally more complex and difficult to manufacture. These methods can be mainly divided into three groups: physical, physical-chemical, and chemical techniques [53,113,114]. Among these, chemical methods are the most widely used [114], and include processes such as in situ polymerization, emulsion polymerization, interfacial polymerization, suspension polymerization and dispersion polymerization process [113]. Konuklu et al. [115] conducted that the most economical and straightforward micro-encapsulation methods are coacervation and emulsion polymerization methods. One example is the encapsulation of inorganic PCM within an elastomeric polyacrylate using emulsion polymerization method.

### 3.2.3.3. Nano-encapsulation.
To incorporate PCM into more delicate or slender building materials, some researchers have explored nano-encapsulation techniques. This method enables the encapsulation of PCM at a much smaller scale than micro-encapsulation. However, nano-encapsulation is more technologically demanding and expensive, and

therefore is not yet widely applied in building applications. Currently, research in this area is primarily focused on the field of chemistry. Wang et al. [116] developed a hybrid composite PCM for application in wallboards. The nano-encapsulated PCM was prepared using emulsion polymerization and subsequently coated onto the surface of porous materials that had been penetrated by octadecane.

### 3.2.4. Stabilized PCM

#### 3.2.4.1. Shape-stabilized PCM.
In shape-stabilized PCM (SSPCM), the PCM is dispersed within the matrix of a supporting material that maintains the physical shape of composite during phase transitions. This supporting material may be a polymer or another substance with a high melting point and good mechanical stability. Based on a summary of various studies on SSPCM integrated into building envelopes, Lamrani et al. [65] identified high-density polyethylene (HDPE) as a common supporting material. Zeng et al. [93] applied SSPCM plates in the renovation of walls in pre-existing granaries. The SSPCM was prepared using paraffin (as the PCM), expanded graphite (as a thermal conductivity enhancer), and HDPE (as a supporting material) via the melt blending method. Microstructural analysis confirmed that HDPE exhibited good compatibility with both paraffin and ethylene glycol. A ternary SSPCM designed through in-situ polymerization [117] was shown to be more cost-effective than traditional board, with its cost being only 34.34 % of that of expanded polystyrene while achieving a similar energy-saving effect.
<table><caption>**Table 5**
Summary of key studies in PCM integrated into bricks.</caption><thead><tr><th>Ref</th><th>PCM type</th><th>Location</th><th>Method</th><th>Remark</th></tr></thead><tbody><tr><td>[120]</td><td>Paraffin</td><td>Al Amarah, Iraq</td><td>Exp</td><td>• Square cross-section PCM capsules showed best thermal performance.<br>• Excessive heat transfer area may cause overheating.</td></tr><tr><td>[121]</td><td>n-Eicosane, capric acid, RT-42</td><td>Egypt</td><td>Num, Exp</td><td>• PCM blocks improve thermal storage and reduce peak load.<br>• n-Eicosane showed highest energy saving (up to 18 %).</td></tr><tr><td>[122]</td><td>n-Eicosane, capric acid, RT-42</td><td>Algeria</td><td>Num</td><td>• n-Eicosane/capric acid mixture had best thermal performance.<br>• 6.39 % peak temperature reduction, 36.49 % heat flux reduction, 5 h delay in peak temperature time.</td></tr><tr><td>[123]</td><td>OM35, Eicosane</td><td>Delhi</td><td>Exp</td><td>• OM35 brick reduced heat gain by 12 %.<br>• Eicosane brick reduced heat gain by 8 %<br>• OM35 brick was better than Eicosane brick in terms of cost.</td></tr><tr><td>[105]</td><td>Dual (Eicosane + OM35), Single OM35</td><td>Delhi</td><td>Exp</td><td>• Double PCM layer reduced temperature by 9.5 °C.<br>• Single PCM layer reduced temperature by 6 °C.</td></tr><tr><td>[124]</td><td>n-Octadecane, Capric Acid</td><td>Lucknow, India</td><td>Exp</td><td>• Tubular capsules showed best thermal performance.<br>• Average temperature reductions: 4.20 °C (tubular), 3.60 °C (square), 3.43 °C (rectangular).</td></tr><tr><td>[125]</td><td>Paraffin wax</td><td>Al Amarah, Iraq</td><td>Exp</td><td>• PCM layer integration showed better thermal performance than capsule.</td></tr><tr><td>[126]</td><td>PCM (18°C-23 °C)</td><td>Qingdao, China</td><td>Num, Exp</td><td>• PCM in hollow cavities enhances thermal inertia, lower thermal insulation.<br>• Better location to fill PCM in is the inner cavities of hollow bricks.</td></tr><tr><td>[127]</td><td>Paraffin5913, Capric acid, n-Eicosane</td><td>Marrakech</td><td>Num</td><td>• Best efficiency achieved with capric acid (32 °C melting) filled in middle cavities.<br>• Thermal inertia improved by combining with low-emissivity paint or cavity insulation.</td></tr></tbody></table>

### 3.2.4.2. Form-stable composite PCM.
Shape-stabilized PCM and form-stable composite PCM share similarities in that both are designed to prevent leakage during phase transitions and to maintain their shape. However, they are not identical. In the fabrication of form-stable composite PCM, the most common approach is to encapsulate the PCM within a supporting material. This typically involves forming microspheres through micro-encapsulation or impregnating the supporting material with the PCM [118,119].

## 4. Energy-based categorization of PCM in building walls

The integration of PCM into building walls has been extensively studied for its ability to enhance thermal regulation and reduce energy consumption. For clarity, PCM applications in building walls can be broadly classified into three categories based on thermodynamic behavior and practical implementation considerations. The major types are: (1) PCM integrated into building bricks, which enhances thermal mass at the material level and directly influences heat storage and release. This approach is particularly suitable for new construction; (2) PCM incorporated as a separate wall layer, allowing for greater control over placement and thickness to optimize transient thermal buffering. This method is especially advantageous in renovation projects; and (3) PCM mixed with raw materials, such as plaster, concrete, or paints, enabling a more homogeneous distribution. This improves the thermal conductivity of the base material and facilitates easier integration across a wide range of construction applications. These classifications reflect fundamental differences in heat transfer mechanisms, construction techniques, and practical applicability.

### 4.1. Energy analysis of PCM integrated into bricks

The integration of PCM into bricks has been widely studied for its potential to enhance thermal storage capacity, regulate indoor temperatures, and improve building energy efficiency. Table 5 summarizes selected studies, allowing for comparison of PCM types, locations, methods, and outcomes. Both experimental and numerical results consistently demonstrate that PCM bricks outperform conventional bricks by reducing peak thermal loads, delaying heat transfer, and improving thermal inertia.

Among the various integration techniques, macro-encapsulation is the most commonly used approach for PCM incorporation in brick. The laboratory-scale manufacturing process for PCM bricks is illustrated in Fig. 8. However, this method remains largely at the experimental stage,

with limited validation at the industrial scale. Key barriers to commercialization include challenges in ensuring uniform PCM distribution, preventing leakage during phase transitions, and minimizing integration cost [128]. To facilitate widespread adoption in the construction industry, simple, cheap, and reliable methods for PCM incorporation must be developed.

Thermal performance is influenced by several key factors, including PCM type, encapsulated PCM geometry, and strategic placement within brick structures. Current research generally supports the use of organic PCM, particularly paraffin-based materials, for integration in bricks used in hot climates due to their favorable thermal properties. Capsule geometry also plays a critical role in thermal regulation. Some studies suggest that tubular capsules [124] provide superior heat distribution, while others indicate that square-section capsules [120] optimize PCM utilization by balancing heat transfer and storage duration. The placement of PCM within the brick, especially filling middle [127] or inner cavities [126], has been shown to significantly enhance thermal regulation. Additionally, combining PCM with insulation techniques or low-emissivity coatings further improves energy performance [127].

Nonetheless, several challenges must be addressed before PCM bricks can be widely adopted. One key concern is the potential reduction in mechanical strength, which some studies [125] attribute to the ductility of encapsulation materials such as aluminum. This may compromise long-term structural integrity. Moreover, issues related to PCM leakage and durability still need to be resolved.

### 4.2. Energy analysis of PCM as a separate wall layer

PCM as a separate wall layer is a flexible approach that allows for modular installation, making it particularly suitable for retrofitting existing buildings. It can reduce the peak thermal loads through delaying heat transfer. Table 6 summarizes some studies on PCM used as a separate wall layer.

PCM wallboards or panels are a common form for integrating PCM in this configuration. Results demonstrate that PCM wallboards and panels not only contribute to energy savings but also enhance indoor thermal comfort and humidity regulation. The effectiveness of these systems depends on several interrelated factors, including PCM layer thickness [132], PCM layer arrangement [133], phase change temperature [134], and thermal conductivity [131]. Increasing the PCM layer thickness has been shown to effectively reduce cooling loads and energy consumption. However, findings indicate that thickness alone does not significantly enhance the time delay and attenuation effects, suggesting that other
<figure><img src="image_11.png" /><figcaption>Fig. 8. Laboratory-scale process of manufacturing the PCM brick. Reproduced with permission [105]. Copyright 2025, Elsevier.</figcaption></figure>

design parameters should also be considered. Optimizing the layering order of PCM wallboards also plays a crucial role in improving thermal regulation. Positioning the insulation layer on the exterior side and the PCM layer on the interior [133] has been identified as a highly effective strategy for reducing the temperature of indoor air, as shown in Fig. 9.

However, PCM performance is highly climate-dependent, posing challenges for achieving optimal results across various regions. To address this, double-layer PCM systems with different enthalpy values and melting temperatures have been introduced as a climate-responsive solution [135]. The rationale behind this design lies in the ability to target a wider range of thermal loads: the outer layer typically contains a PCM with a higher melting temperature to absorb excess heat during hot periods, while the inner layer uses a PCM with a lower melting temperature to regulate indoor temperatures during cooler periods. This configuration aims to improve thermal energy storage efficiency across varying daily and seasonal conditions, thereby extending the effective operating range of the system. These systems can be effective year-round, including both hot and cold conditions. Nevertheless, some studies have reported that this approach does not always yield superior performance. In certain regions with limited solar radiation during winter, single-layer PCM configurations have demonstrated better thermal performance [136]. Therefore, the suitability of double-layer PCM systems should be evaluated based on specific environmental conditions.

More recently, a wall with a dynamic PCM layer was proposed by an experimental study [137]. The position of PCM layer can be moved within an air gap according to environmental conditions. Compared to the static PCM configuration, the dynamic PCM wall reduced the average indoor temperature by 9.1 % and peak heat flux by 116.0 %, indicating significantly enhanced thermal regulation through greater latent heat exploitation.

### 4.3. Energy analysis of PCM mixed with raw materials

PCM mixed with raw materials such as cement, plaster, or other base materials provide a uniformly distributed thermal storage medium, enhancing the overall performance of building envelope. Relevant studies are presented in Table 7.

One of the most widely adopted methods is the direct incorporation of micro-encapsulated PCM. This allows for uniform distribution while ensuring ease of on-site construction, making it a practical solution for real-world applications. As shown in Table 5, incorporating micro-encapsulated PCM can significantly enhance energy performance. However, mechanical strength generally decreases, and porosity increases, because the hydration reactions of the base materials are slowed when PCM is added. Findings [146] show that incorporating 3 wt%, 6 wt%, 9 wt%, and 12 wt% of micro-encapsulated PCM into the base material results in compressive strengths of 16.71 MPa, 12.40 MPa, 10.84 MPa, and 7.78 MPa, respectively, compared to the normal strength of 22.53 MPa. To address this issue, researchers have explored the optimal PCM-to-raw material ratio to balance thermal efficiency with

mechanical integrity. Studies [139,138] indicate a micro-encapsulated PCM content between 5 % and 20 % by weight offers a favorable balance. In particular, 5 % micro-encapsulated eutectic incorporation has maintained a compressive strength of 23.23 MPa, which is comparable to conventional materials [140].

In foam concrete [143], higher PCM contents are often acceptable. PCM-foam concrete (PCM-FC) containing 39 % micro-encapsulated PCM has shown superior thermal storage properties, reducing temperature fluctuations by up to 51 %. In such applications, especially when micro-encapsulated PCM is used in plaster or coatings, mechanical performance is often not a primary concern. Laboratory results [142] confirm that gypsum plaster tiles containing 10 % micro-encapsulated eutectic PCM can reduce energy consumption by approximately 12 %, highlighting their effectiveness as passive energy-saving solutions.

Another practical method for incorporating PCM into construction materials, particularly concrete, is encapsulated PCM in aggregate. This technique significantly mitigates the mechanical and durability issues associated with direct micro-encapsulation while maintaining or even enhancing thermal performance. Porous aggregates such as expanded clay [147] and expanded perlite [145] are typically used as PCM carrier. Among PCM types, paraffin is the most widely used due to its chemical stability, compatibility with porous LWA, and reliable thermal cycling behavior. Studies [145] have shown that incorporating paraffin-LWA with different melting temperatures can increase the volumetric specific heat of mortar by approximately 40 %-60 %, significantly enhancing the thermal energy storage capacity of building components. However, this improvement comes with a trade-off: the thermal conductivity of such mortars may decrease by approximately 48 %-63 %, which can limit their use in systems that require rapid heat transfer or enhanced fire resistance.

In comparison, salt hydrates offer higher thermal conductivity and latent heat values, making them attractive for large-scale applications with greater thermal load demands. For example, sodium acetate trihydrate [55] has been used to develop thermal energy storage aggregates with a latent heat of approximately 150 J/g, while also addressing the supercooling problem that often affects salt hydrates.

### 5. Exergy analysis

Exergy represents the maximum useful work obtainable from a system as it moves toward thermodynamic equilibrium with its surroundings [148]. It accounts for both the quantity and quality of energy, offering insight into the irreversibility inherent in the thermodynamic processes [149]. Unlike conventional energy analysis, exergy analysis provides a more comprehensive understanding of system inefficiencies, making it particularly valuable for the design and optimization of engineering systems. The distinction between energy, exergy, and entropy is presented in Fig. 10, based on references [149–151].

In PCM-integrated wall systems, energy analysis typically evaluates the total heat stored or released during phase transitions. However, it does not consider the temperature level at which this energy is
<table><caption>**Table 6**
Summary of key studies in PCM as a separate wall layer.</caption><thead><tr><th>Ref</th><th>PCM type</th><th>Location</th><th>Method</th><th>Remark</th></tr></thead><tbody><tr><td>[129]</td><td>MPCM28 (Octadecane), CPCM23 (porous silica/paraffin)</td><td>Tianjin, China</td><td>Exp</td><td><ul><li>Sandwich and mix wallboard forms both improved thermal comfort.</li><li>Summer: sandwich wallboard; Winter: mix wallboard.</li></ul></td></tr><tr><td>[130]</td><td>Shape-stabilized PCM (Paraffin)</td><td>Wuhan, China</td><td>Num</td><td><ul><li>Double-layer wallboards improved indoor humidity and temperature control.</li><li>Optimal melting points: 25 °C (summer), 17 °C (winter).</li></ul></td></tr><tr><td>[131]</td><td>Expanded graphite/paraffin composite</td><td>Xi'an, China</td><td>Num</td><td><ul><li>Interior surface temperature affected by various parameters: thickness > phase change temperature > thermal conductivity.</li></ul></td></tr><tr><td>[132]</td><td>10 % paraffin-based n-octadecane in pouches</td><td>Darwin</td><td>Num</td><td><ul><li>Increasing PCM thickness reduced cooling load and energy use.</li></ul></td></tr><tr><td>[133]</td><td>Na<sub>2</sub>SO<sub>4</sub>·10H<sub>2</sub>O in bag</td><td>Western China</td><td>Exp</td><td><ul><li>Increasing PCM thickness alone had limited effect.</li><li>Optimizing layer order improves thermal performance.</li><li>Best design: insulation outside, PCM layer inside.</li></ul></td></tr><tr><td>[134]</td><td>Prefabricated PCM plate</td><td>Guangzhou, Zhengzhou, Harbin, China</td><td>Num</td><td><ul><li>Energy savings depend on phase change temperature and latent heat.</li><li>Optimal PCM temps: 31 °C (Guangzhou), 28 °C (Zhengzhou and Harbin).</li><li>Energy savings: 12.5 % (Guangzhou), 14.8 % (Zhengzhou), 17.5 % (Harbin).</li></ul></td></tr><tr><td>[135]</td><td>RT-line paraffin wax</td><td>Tehran, Isfahan, Shiraz, Tabriz, Bandar Abbas, Iran</td><td>Num</td><td><ul><li>Double-layer PCM reduced heating/cooling energy vs. single-layer.</li><li>Dual PCM with different enthalpy/melting temps improved climate adaptability.</li><li>Effective for both hot and cold conditions</li><li>Dual-PCM (RT28HC/RT24HC) configuration is optimal for Beijing.</li><li>Single PCM recommended for Zhengzhou and Wenzhou.</li></ul></td></tr><tr><td>[136]</td><td>RT-line paraffin wax</td><td>Beijing, Zhengzhou, Wenzhou, China</td><td>Num</td><td></td></tr></tbody></table>

<table><caption>**Table 6 (continued)**</caption><thead><tr><th>Ref</th><th>PCM type</th><th>Location</th><th>Method</th><th>Remark</th></tr></thead><tbody><tr><td>[137]</td><td>Paraffin</td><td>–</td><td>Exp</td><td><ul><li>Dynamic PCM utilized more latent heat.</li><li>Dynamic PCM wall offers exclusive cooling performance.</li></ul></td></tr></tbody></table>

exchanged, which is critical factor for matching with indoor comfort requirements. As a result, energy analysis may report 100 % efficiency in a full charge/discharge PCM cycle, since the latent heat stored equals the heat released [152]. However, this overlooks energy degradation caused by irreversibility, such as thermal mismatches between the PCM and indoor air, incomplete melting/solidification, and heat losses.

In contrast, exergy analysis quantifies the useful portion of stored energy by accounting for its temperature-dependent potential to perform work relative to the surrounding environment. Ajah et al. [153] reported that a PCM Trombe wall stored a total of 479.5 MJ of energy but only 26.8 MJ of exergy, with respective energy and exergy efficiencies of 43.02 % and only 2.56 %. This pronounced discrepancy underscores the limitations of conventional energy analysis and demonstrates the necessity of exergy-based assessment for accurately evaluating and optimizing PCM-integrated building systems.

Considering a control volume at steady state, the corresponding energy and exergy balances of the system can be expressed as [43,151]:

$$E_{in} = E_{out} + E_{emitted} \quad (1)$$

$$Ex_{in} = Ex_{out} + Ex_{emitted} + Ex_{destroyed} \quad (2)$$

Where: $E_{in}$ and $Ex_{in}$ represent the energy and exergy input to the system, respectively (e.g., solar radiation); $E_{out}$ and $Ex_{out}$ are the useful energy and exergy output (e.g., entered to the interior space or stored in the PCM); $E_{emitted}$ and $Ex_{emitted}$ refer to the energy and exergy emitted to the environment (e.g., exhaust air or surface losses); $Ex_{destroyed}$ is the exergy destruction of system due to irreversible processes.

Based on exergy analysis, several exergy metrics have been developed to evaluate the exergetic performance of system. However, due to the limited research on exergy analysis of PCM systems in building wall applications, only two key metrics are commonly used: exergy efficiency and exergy destruction. These metrics are introduced below.

(1) **Exergy efficiency.** Exergy efficiency ($\eta_{ex}$) is a commonly used parameter for evaluating the exergetic performance of an energy system. It is defined as:

$$\eta_{ex} = Ex_{out} / Ex_{in} \quad (3)$$

Specially, in a ventilation building envelope integrated PV and PCM [43], the stored exergy efficiency in PCM ($\eta_{ex_{pcm}}$) is the ratio of the stored exergy of PCM ($Ex_{pcm}$) to the exergy input by sun ($Ex_{sun}$), as Eq (4):

$$\eta_{ex_{pcm}} = Ex_{pcm} / Ex_{sun} \quad (4)$$

The solar exergy input is commonly determined using the Petela model:

$$Ex_{sun} = G(t) \cdot A \cdot (1 - (T_{amb} + 273.15) / T_{sun}) \quad (5)$$

The exergy stored in PCM varies with its phase and temperature (solid, melting, liquid), and can be calculated by:
<figure><img src="image_12.png" /><figcaption>Fig. 9. Test results of different PCM wall configurations. Reproduced with permission [133]. Copyright 2025, Elsevier.</figcaption></figure>

$$ 
\begin{aligned}
Ex_{pcm} = m_{pcm} \cdot C_{p\_pcm.solid} \cdot \frac{dT_{pcm.solid}}{dt} (1 - T_a/T_{pcm.solid}) \\
+ m_{pcm} \cdot C_{p\_pcm.solid-liquid} \cdot \frac{dT_{pcm.solid-liquid}}{dt} (1 - T_a/T_{pcm.solid-liquid}) \\
+ m_{pcm} \cdot C_{p\_pcm.liquid} \cdot \frac{dT_{pcm.liquid}}{dt} (1 - T_a/T_{pcm.liquid})
\end{aligned}
\qquad (6) $$

Where: A is the area of glass cover; $T_{amb}$ is the ambient temperature; $T_{sun}$ is the solar temperature; $m_{pcm}$ is the mass of PCM; $C_{p\_pcm}$ terms are specific heat capacities of the PCM in different states (solid, melting, liquid); $T_{pcm}$ refer to PCM temperature in different states (solid, melting, liquid); $T_a$ is the temperature of air flow the ventilation channel.

(2) Exergy Destruction (ED). Exergy destruction quantifies the irreversibility in the system [51] and is defined by when $Ex_{emitted}$ is negligible:

$$ Ex_{destroyed} = Ex_{in} - Ex_{out} \qquad (7) $$

Alternatively, it can be derived from entropy generation [154]:

$$ Ex_{destroyed} = T_0 S_{gen} \qquad (8) $$

Where: $T_0$ is the temperature of properties at the restricted dead state (typically the ambient indoor air); $S_{gen}$ is the entropy generation.

However, there is limited research on the exergy analysis of PCM applications in building systems. Table 8 summarizes various studies that evaluate PCM integration in building walls from an exergy perspective. These studies highlight the crucial role of exergy analysis in the design and optimization of PCM-integrated building systems, particularly in material selection, system configuration, and ensuring efficient energy use under diverse climatic conditions.

Different PCM exhibit varying levels of latent heat, thermal conductivity, and phase change characteristics, which influence their ability to store and release thermal energy efficiently. As indicated by Oruc et al. [159], SP26E demonstrated the highest exergy efficiency among four types of PCM (C13-C24, C18, SP21EK and SP26E), attributed to its lowest latent heat capacity and higher heat of fusion.

Several studies have also focused on optimizing exergy performance by adjusting key parameters of PCM systems. One critical factor is the melting temperature of the PCM, which plays a pivotal role in determining exergy efficiency. In a solar composite ventilation wall integrated with PV and PCM (SPVW-PV/PCM), He et al. [156] showed that lower melting temperatures (e.g., 298 K) enhanced natural ventilation and pollutant dilution, while higher melting temperatures optimized exergy recovery through improved thermal regulation. Additionally,

Askari et al. [163] demonstrated that using two different melting temperature (29 °C and 18 °C) in double-layer PCM Trombe walls significantly improved exergy efficiency, especially during the cooling season.

Moreover, integrating PCM into novel system configurations can further enhance exergy efficiency. For example, Shu et al. [43] proposed a ventilation wall incorporating PV and PCM (FVBE-PV/PCM) and compared it to a conventional solar ventilation wall (BIPV) and a PV ventilation wall without PCM (FVBE-PV). Their findings confirmed that PCM played a key role in improving exergy efficiency, with stored exergy accounting for 38.249 % of the total input exergy. The energy and exergy flow distributions of the FVBE-PV/PCM system are detailed in Fig. 11.

Similarly, Li et al. [45] simulated the energy and exergy performance of transpired solar collectors (TSCs) integrated with PCM under varying temperature conditions. Their results indicated substantial improvements in exergy efficiency, particularly during periods of high solar gain. However, under insufficient sunlight, exergy efficiency declined, resulting in negative net heating power from the absorber, highlighting the critical importance of system design and solar availability. Furthermore, Cai et al. [155] showed that incorporating a double-layer PCM into an innovative building-integrated photovoltaic system (BIPV-dPCM) improved electrical exergy efficiency by 11.66 % and thermal exergy efficiency by 1.54 %.

## 6. Environmental analysis

Environmental analysis is used to systematically identify and categorize the potential positive or negative impacts that an energy system may have on the environment [164]. Among various methodologies, Life Cycle Assessment (LCA) stands out as the most direct and effective approach, offering significantly more detailed information than conventional assessment tools [165]. A standard LCA is carried out by four steps: definition of goal and scope, inventory analysis, impact assessment, and interpretation of results [166].

The application of LCA in building sector began in the 1990s with the introduction of first ISO standards [167,168]. Following the ‘cradle-to-gate’ principle, the life cycle of an energy system includes materials manufacturing (raw material extraction and processing, manufacture, distribution), use and maintenance, and end of life (disposal or recycling) [169,170]. Among these, the operating phase has been identified as contributing the most to environmental impact [169], primarily due to the high energy consumed for heating and cooling buildings. The integration of PCM into building design can mitigate environmental impacts during this phases, helping to avoid the transfer of
<table><caption>**Table 7**
Summary of key studies in PCM mixed with raw materials.</caption><thead><tr><th>Ref</th><th>PCM type</th><th>Location</th><th>Method</th><th>Remark</th></tr></thead><tbody><tr><td>[138]</td><td>Micro-encapsulated paraffin (Micronal5040X, Micronal5038X)</td><td>Sicily, Italy</td><td>Num, Exp</td><td><ul><li>15 wt% PCM in mortar improved comfort by ~15 % annually.</li><li>Micronal5038 performed slightly better due to cooling-dominated climate.</li></ul></td></tr><tr><td>[139]</td><td>Micro-encapsulated paraffin (Nextek37D)</td><td>-</td><td>Exp</td><td><ul><li>5-20 % PCM improved thermal and without affecting mechanical properties.</li><li>5 % developed eutectic PCM did not affect cement strength.</li><li>Heat transfer reduction up to 16.69 % vs normal plastered wall.</li></ul></td></tr><tr><td>[140]</td><td>Micro-encapsulated Eutectic</td><td>India</td><td>Exp</td><td><ul><li>PCM plaster had higher insulation and thermal storage than normal one.</li><li>Mechanical strength and thermal conductivity remained acceptable.</li><li>10 wt% PCM in gypsum reduced energy use by ~12 %.</li></ul></td></tr><tr><td>[141]</td><td>Micro-encapsulated paraffin</td><td>Hokkaido, Japan</td><td>Exp</td><td><ul><li>Sample (39 % PCM by volume) showed higher thermal storage density.</li><li>No major impact on mechanical properties vs. normal PCM concrete.</li></ul></td></tr><tr><td>[142]</td><td>Micro-encapsulated eutectic (stearic acid + coconut oil)</td><td>-</td><td>Num, Exp</td><td><ul><li>Temp fluctuations reduced by up to 51 % vs. conventional cement render under real-weather conditions.</li><li>Volumetric heat capacity (MJ/m³.K): 1.65 (0 % PCM), 2.6 (50 % RT18HC), 2.4 (50 % RT22HC), 2.3 (50 % RT25HC).</li><li>Flexural strength reduced by 29.7 %–37.5 %, compressive strength reduced by 39.7–48.5 %, at 50 % PCM.</li></ul></td></tr><tr><td>[143]</td><td>Micro-encapsulated bio-based PCM (EnFinit 35)</td><td>-</td><td>Exp</td><td><ul><li>High latent heat, thermal stability, low supercooling.</li><li>Reducing the particle size leads to higher energy storage and better compressive strength.</li></ul></td></tr><tr><td>[144]</td><td>Micro-encapsulated bio-based PCM (EnFinit 35)</td><td>Malaysia</td><td>Exp</td><td></td></tr><tr><td>[145]</td><td>Paraffin impregnated</td><td>-</td><td>Exp</td><td></td></tr><tr><td>[55]</td><td>Sodium acetate trihydrate impregnated</td><td>-</td><td>Num, Exp</td><td></td></tr></tbody></table>

<figure><img src="image_13.png" /><figcaption>**Fig. 10.** Overview of energy, exergy, and entropy transfer in a system.</figcaption></figure>

environmental burdens from one stage to another [171–173]. Table 9 provides a comprehensive overview of the LCA methodologies employed in the environmental analysis of PCM-integrated wall systems.

Studies summarized in Table 9 consistently demonstrate that PCM generally have a positive environmental impact over its lifecycle compared to conventional construction materials. For instance, Żelazna et al. [175] found that integrating paraffin PCM into Trombe walls reduced carbon emissions by up to 8.96 MgCO₂eq and decreased the environmental load by 1.947 Pt, compared to buildings using traditional insulation. Similarly, Papadaki et al. [178] confirmed that incorporating PCM-23 and vacuum insulation panels (VIPs) into wall systems reduced environmental impact by 57 % compared to a reference house. However, during the construction phase, walls with PCM and VIPs exhibited a higher environmental footprint than the reference walls, although these additional impacts were fully offset after just one year of operation. These findings underscore that the long-term environmental benefits of PCM systems despite potential initial production burdens.

Further supporting these benefits, de Gracia et al. [179] examined the use of PCM in ventilated double skin facades (VDSF). The study showed that the overall environmental impact of a VDSF system with PCM in the air chamber was 1559, compared to 1685 for a reference system over a 50-year operational period. Notably, the highest environmental performance was observed during the winter season, with a 20.7 % reduction in impact during operation, further emphasizing the benefit of PCM in reducing energy use during building operation.

The environmental impact of PCM-integrated buildings varies significantly depending on the type of PCM used. In particular, salt hydrate-based PCM generally demonstrate better sustainability than paraffin-based ones. Horn et al. [186] evaluated paraffin (RT21) and salt hydrate-based materials (SP21EK and SP58) at the material level. Salt hydrates required only 20 to 150 cycles to offset their non-renewable primary energy demand, while paraffins require up to 280 cycles, making them less sustainable. Among the materials assessed, SP21EK exhibited the best environmental performance, with amortization occurring after only 20 cycles.

In a related study [173], glycerine and fatty acids derived from waste cooking oil were evaluated and found to offer significant environmental advantages over paraffin-based materials. When integrated into sandwich panels, these waste-derived exhibited lower impact values across most ILCD impact categories compared to both paraffins and polyurethane (PU)-based panels. This shift to secondary materials highlights the potential for PCM technologies to support circular economy
<table><caption>**Table 8**
Summary of exergy-based studies on the PCM applied in building walls.</caption><thead><tr><th>Ref</th><th>PCM</th><th>Element</th><th>Method</th><th>Results</th></tr></thead><tbody><tr><td>[51]</td><td>PCM35 (inner), PCM50 (outer)</td><td>Brick</td><td>Num</td><td><ul><li>Energy efficiency: 0.113 %, exergy efficiency: 0.122 %.</li><li>Exergy efficiency decreased with increased PCM thickness (hot side).</li></ul></td></tr><tr><td>[153]</td><td>Emerest2325</td><td>Trombe walls</td><td>Num</td><td><ul><li>Energy efficiency: 61 % (concrete) vs. 62.5 % (clay).</li><li>Exergy efficiency: 3 % (concrete) vs. 3.1 % (clay).</li></ul></td></tr><tr><td>[155]</td><td>RT-28 (inner), RT-40 (outer)</td><td>Multi-layer PV-PCM wall</td><td>Num</td><td><ul><li>Enhanced electrical exergy efficiency by 11.66 %.</li><li>Enhanced thermal exergy efficiency by 1.54 %.</li></ul></td></tr><tr><td>[45]</td><td>RT18HC, ATP23, RT28HC, SP31</td><td>TSC-PCM envelope</td><td>Num</td><td><ul><li>Thermal efficiency: 60.9 % (TSC-PCM) vs. 47.3 % (TSC).</li><li>Exergy efficiency: 20.6 % (TSC-PCM) vs. 16.3 % (TSC).</li></ul></td></tr><tr><td>[43]</td><td>RT-42</td><td>FVBE-PV/ PCM</td><td>Num</td><td><ul><li>Exergy efficiency for power: 4.188 % (FVBE-PV) vs. 4.208 % (FVBE-PV/ PCM).</li></ul></td></tr><tr><td>[156]</td><td>-</td><td>SPVW-PV/ PCM envelope</td><td>Num</td><td><ul><li>Melting temperature had less impact on exergy efficiency than PV coverage ratio.</li><li>303K melting, 100 % PV: average exergy efficiency: 42.14 % (winter) and 31.21 % (summer).</li><li>In winter, 6:00 a.m., exergy efficiency: 0.273 (DSPVW-PV), 0.228 (DSPVW-PV/PCM), 0.450 (SPVW-PV).</li><li>In winter, 6:00 p.m., exergy efficiency: 0.569 (DSPVW-PV), 0.868 (DSPVW-PV/PCM), 0.494 (SPVW-PV).</li></ul></td></tr><tr><td>[157]</td><td>OM32</td><td>DSPVW-PV/PCM</td><td>Num</td><td><ul><li>PCM scenario had lowest exergy limitations across different temperature variations.</li><li>Exergy efficiency increased by 13.0 % (with PCM).</li><li>Energy efficiency: 62 % (Without PCM) vs. 87 % (SP26E).</li><li>Exergy efficiency: 14 % (Without PCM) vs. 56 % (SP26E).</li><li>Panel had better exergy performance than ball for cooling.</li><li>Exergy efficiency at 8 °C: 4.898 % (charging) to 2.378 % (discharging).</li><li>Stored energy vs. exergy: 479.5 MJ vs. 26.8 MJ.</li><li>Energy efficiency vs. exergy efficiency: 43.02 % vs. 2.56 %.</li><li>Best exergy efficiency in cold months with infiniteRPCM29/18 ranged from 3 % to 3.5 %.</li><li>Max exergy efficiency in August.</li><li>PCM pallets in façade increased exergy efficiency by 13.0 %.</li></ul></td></tr><tr><td>[44]</td><td>RT18HC</td><td>Multi-layer wall</td><td>Num</td><td></td></tr><tr><td>[158]</td><td>C-acid</td><td>Wall</td><td>Num</td><td></td></tr><tr><td>[159]</td><td>C13-C24, C18, SP21EK, SP26E</td><td>Radiant wall</td><td>Num</td><td></td></tr><tr><td>[160]</td><td>CaCl<sub>2</sub>-6H<sub>2</sub>O</td><td>PCM-TMS wall</td><td>Exp</td><td></td></tr><tr><td>[161]</td><td>RT-27</td><td>Façade</td><td>Num</td><td></td></tr><tr><td>[162]</td><td>Emerest2325</td><td>Trombe wall</td><td>Num</td><td></td></tr><tr><td>[163]</td><td>InfiniteRPC (18,25,29), WINCO21</td><td>Double PCM Trombe wall</td><td>Num</td><td></td></tr><tr><td>[52]</td><td>Emerciel22, C-acid</td><td>Wall</td><td>Num</td><td></td></tr></tbody></table>

principles.

Menoufi et al. [183] compared the environmental impacts of RT-27 paraffin, SP-25 A8 salt hydrate, and ester-based PCM during the manufacturing and disposal phases. The findings revealed that PU + RT-27 paraffin exhibited the highest environmental burden, followed by PU + SP-25 A8 salt hydrate, and PU + PCM ester. Additionally, PCM incorporated into cubicles exhibited higher environmental impact during the manufacturing phase than reference cubicles without PCM or PU cubicles, highlighting the embodied energy associated with PCM production and disposal.

Climate conditions also significantly influence the environmental impact of PCM systems. Castell et al. [180] analyzed the sustainability of PCM in alveolar brick systems and concluded that year-round summer climates significantly enhanced the environmental benefits of PCM systems. In such regions, where daily temperatures near the phase change point of the PCM, prolonged activation periods result in reducing environmental impact during operation. Even within the same climate classification, local variations can lead to differing environmental outcomes. For example, Vega et al. [169] found that using paraffin wax in lightweight buildings was more suitable for Calama, an area with relatively extreme climatic conditions, compared to Antofagasta, which, although also classified as BWk (cold desert climate), has a more moderate climate. This indicates that local climate characteristics must be taken into account when assessing the overall environmental performance of PCM systems.

Baylis and Cruickshank [174] further explored climate influence by comparing coconut oil and paraffin-based PCM across three North American cities. Despite paraffin PCM had higher embodied carbon, it resulted in greater lifetime carbon emissions reductions in both hot (Houston) and cold (Yellowknife) climates due to their higher latent heat capacity. In moderate climates like Ottawa, however, the difference in emissions reductions between the two types of PCM were negligible, highlighting the significant role of climate in PCM performance.

## 7. Economic analysis

Economic analysis is a key method for evaluating PCM-integrated walls and is often conducted in parallel with energy analysis. Typically, economic evaluations assess the economic feasibility of PCM applications by quantifying the relationship between energy efficiency improvements and the associated costs. Among these methods, the simple static payback period (SPP) is the most commonly used. This approach calculates the payback period by comparing the initial investment cost with annual energy cost savings [187], providing a clear and intuitive metric for economic assessment. However, the SPP does not account for the time value of money, limiting its applicability for long-term building evaluations. To address this limitation, the dynamic payback period (DPP) method incorporates discount rate, providing more realistic results [47,188]. For example, the SPP for office building integrated PCM27 in Shenyang was 5.91 years, while the DPP varied from 7.18 to 9.39 years depending on the applied discount rate [188].

Regardless of the metric used, payback periods for PCM systems vary widely across studies due to factors such as building type, climatic conditions, PCM properties, and the local economic context. For example, the SPP for PCM20 panels applied in Guangzhou [189] was reported at 9.72 years, which aligns with the material's useful lifespan and supports its economic viability. In contrast, OM35 bricks in another study [190] were found to have a payback period of up to 181 years, far exceeding their useable lifespan and highlighting severe economic limitations for that application.

These variations are consistent with trends shown in Fig. 12, which illustrates how DPP increases with greater PCM thickness under natural ventilation conditions across all regions [191]. The lowest DPP (13–16 years) are observed with a PCM thickness of 6 mm, while the highest DPP (22–32 years) correspond to 30 mm thickness. Mechanical ventilation also influences DPP, although its effect varies across climatic
<figure><img src="image_14.png" /><figcaption>Fig. 11. Energy and exergy flow structure of system. Reproduced with permission [43]. Copyright 2025, Elsevier.</figcaption></figure>

zones. The shortest DPP occurs at 0.5 ACH in Zones 1 and 2 (warm semi-arid and warm Mediterranean climates), at 3 ACH in Zones 3 and 4 (warm and temperate Mediterranean climates), and at 6 ACH in Zones 5 and 6, which are characterized by a warm summer climate.

Although the simple payback period offers a quick and straightforward economic evaluation, it lacks the comprehensiveness needed for long-term assessments. To overcome these limitations, Life Cycle Cost Analysis (LCCA) has been introduced by some researchers. LCCA is an economic analysis method for asset management that accounts for all lifecycle costs, including installation, maintenance, financing, restoration, and disposal [192]. An LCCA study [193] on PCM walls without insulation in the Xi'an region showed that increasing PCM thickness extended the payback period (from 10.13 to 13.41 years) but also increased net life-cycle cost saving (from 21.22 to 53.52 CNY/m²), highlighting PCM's long-term economic benefits. However, incorporating PCM into walls equipped with insulation was found to be not a cost-effective solution.

Building on insights provided by LCCA, exergoeconomic analysis represents the most advanced and current methodology for evaluating PCM-integrated building systems. This method combines the exergy analysis with economic evaluation, enabling the identification of the true cost of energy flows and system inefficiencies. The economic balance equation is used to conduct exergoeconomic analysis, as Eq (9) [194].

$$ \sum \dot{C}_{input} + \dot{Z} = \sum \dot{C}_{output} + \dot{C}_{destroyed} \quad (9) $$

Where: $\dot{C}_{input}$ is the cost rate of input exergy; $\dot{Z}$ is the non-energetic cost, normally, it is the sum of initial investment, operation, and maintenance cost; $\dot{C}_{output}$ is the cost rate of useful exergy output; $\dot{C}_{destroyed}$ is the cost rate of exergy destruction due to irreversibility.

Although its application to PCM wall systems remains limited, exergoeconomic analysis has demonstrated significant potential for optimizing thermoeconomic performance. A notable example is the study by Gholamian et al. [158], who applied exergoeconomic analysis to a proposed building-plant system with a PCM-integrated façade. Using exergy balance equation as the foundation (Eq (10)), extending it with exergy efficiency and unit cost of product exergy (Eq (11)), the study revealed that integrating PCM into the façade enhanced system performance significantly. Specifically, the exergy efficiency increased by 13.0 %, while the unit product cost was reduced by 28.54 %. Additionally, the component cost rate of the system with PCM was calculated at 76.78 $/h, compared to 125.91 $/h for the reference system, highlighting the economic and thermodynamic advantages of PCM

integration. The cost rate attributed to PCM itself was 0.1157 $/h, underscoring its cost-effectiveness in the proposed design. These equations are detailed as follows.

$$ \sum \dot{C}_{out,k} + \dot{C}_{w,k} = \sum \dot{C}_{in,k} + \dot{C}_{q,k} + \dot{Z}_k \quad (10) $$

Where: $\dot{C}_{out,k}$ is the cost rate of the system's output; $\dot{C}_{in,k}$ is the cost rate of the system's input; $\dot{C}_{w,k}$ is cost rate of the power energy; $\dot{C}_{q,k}$ is cost rate of the heating energy; $\dot{Z}_k$ is the non-energetic cost.

$$ c_{p,tot} = \left( \sum_{i=1}^{n_k} \dot{Z}_k + \dot{C}_F \right) / \sum_{i=1}^{n_k} \dot{E}_{pi} \quad (11) $$

Where: $\dot{C}_F$ is the cost rate of the fuel; $\dot{E}_{pi}$ is the sum of the exergy rate of the products in the system, $c_{p,tot}$ is the unit product cost.

## 8. Multi-objective optimization

In the context of optimizing PCM-integrated buildings, multi-objective optimization (MOO) is crucial for simultaneously addressing various conflicting objectives such as minimizing energy consumption, reducing carbon emissions, optimizing exergy efficiency, and minimizing life cycle costs. Achieving an optimal configuration that satisfies these objectives require advanced algorithms capable of handling complex, non-linear, and multi-objective optimization problems.

Recently, several advanced optimization techniques have been employed to PCM-integrated walls. These include Non-dominated Sorting Genetic Algorithm II (NSGA-II), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Response Surface Method (RSM). Their characteristics are compared in Table 10, outlining their definitions, diversity mechanisms, types, methods, and strengths.

While each method offers distinct advantages, they also involve trade-offs, especially in multi-objective contexts. Algorithms are typically evaluated using metrics such as computation time, Pareto front quality (including dimensionality and diversity), convergence rate, hypervolume, and the ability to identify global optima [215]. GA is among the most widely used heuristic methods due to their ease of implementation and robust performance [216]; however, it is often computationally intensive and prone to premature convergence, which can lead to entrapment in local optima and reduced effectiveness in complex MOO problems [217]. NSGA-II, an improved GA variant, is well-regarded for producing well-distributed Pareto-optimal solutions by maintaining population diversity through crowding distance mechanisms [216]. However, its performance degrades when the number of
<table><caption>**Table 9**
LCA used in environmental analysis of PCM applied in building walls.</caption><thead><tr><th>Year</th><th>PCM</th><th>Database/Tool</th><th>Location</th><th>Impact Method</th><th>Finding</th></tr></thead><tbody><tr><td>2023<br>[174]</td><td>Paraffin, Coconut oil</td><td>Ecoinvent/-</td><td>Houston, Ottawa, Yellowknife</td><td>Total lifecycle emissions, Carbon payback period</td><td><ul><li>Coconut oil had lower embodied carbon.</li><li>Paraffin PCM (greater latent heat capacity) led to lower lifetime carbon emissions in colder locations.</li></ul></td></tr><tr><td>2023<br>[175]</td><td>RT25HC</td><td>Ecoinvent v3 /SimaPro</td><td>Rzeszów</td><td>GWP100, IMPACT2002+</td><td><ul><li>Paraffin PCM reduced heating energy by 11.3 %.</li><li>Environmental payback &lt;5 years, GWP &lt;1.</li></ul></td></tr><tr><td>2022<br>[169]</td><td>Paraffin wax</td><td>Ecoinvent v3.6 /-</td><td>Antofagasta, Calama</td><td>GWP20/100, ReCiPe-E</td><td><ul><li>For GWP 100, PCM cubicles reduced impact by 34.5 % in Antofagasta and 31.7 % in Calama. For GWP 20, the reductions were 33.5 % and 31.4 %, respectively.</li><li>Total environmental impact decreased by 33.8 % in Antofagasta and 31.6 % in Calama compared to reference.</li></ul></td></tr><tr><td>2019<br>[176]</td><td>Eutectic (capric acid/lauric acid)</td><td>Ecoinvent 3.3/ SimaPro</td><td>Québec</td><td>IMP2002+, ReCiPe-M(H), ReCiPe-E (H)</td><td><ul><li>Damage assessment results: 1.9 × 10<sup>-6</sup> for Human health, 4.0 for Ecosystem quality, 1.1 for Climate change, 10.4 for Resources.</li></ul></td></tr><tr><td>2019<br>[177]</td><td>Salt hydrate</td><td>OneClickLCA</td><td>Athens</td><td>GWP, ReCiPe-M (EP, ODP, POFP, PE)</td><td><ul><li>PCM reduced GWP by up to 16 % in undivided office units. Other impacts reduced by 8–17 %.</li><li>Similar trends seen in subdivided units.</li></ul></td></tr><tr><td>2019<br>[171]</td><td>PCM</td><td>EcoHestia</td><td>Europe</td><td>Energy payback time (EPBT)</td><td><ul><li>EPBT ranged from 1.36 to 2.01 days/m<sup>2</sup> in Central and Northern Europe, and up to 6.95 days/m<sup>2</sup> in Southern Europe.</li></ul></td></tr><tr><td>2019<br>[178]</td><td>PCM-23</td><td>-/SimaPro</td><td>Crete</td><td>ReCiPe-E (HH, EQ, RS)</td><td><ul><li>PCM-VIP house reduced impact by 57 % (4.54 vs. 10.65 kPt/m<sup>3</sup>), 79 % of impact came from operation, 21 % from construction.</li></ul></td></tr><tr><td>2017<br>[173]</td><td>Polyols, Fatty acids, Paraffins</td><td>Ecoinvent 3.2/ SimaPro</td><td>Buchares, Seville</td><td>ILCD 2011 (Ozone depletion, Ionizing radiation, Land use)</td><td><ul><li>Glycerine and fatty acids (from waste oil) offer lower environmental impact than paraffin.</li><li>Polyol-embedded panels show the lowest impact across most ILCD categories, except for ozone depletion, ionizing radiation, and land use.</li></ul></td></tr><tr><td>2014<br>[179]</td><td>SP-22</td><td>EcoInvent 2009/-</td><td>Catalonia</td><td>EI99 (HH, EQ, NR)</td><td><ul><li>VDSF with PCM showed a lower total impact (1559 vs. 1685) over 50 years, with an environmental payback time of 31 years.</li></ul></td></tr><tr><td>2013<br>[180]</td><td>SP-25 A8, RT-27</td><td>EcoInvent 2009/-</td><td>Catalonia</td><td>EI99 (HH, EQ, NR)</td><td><ul><li>PCM use reduced environmental impact by 12–14 % compared to reference.</li><li>Longer operational periods and climates near the PCM's phase change point enhanced these benefits by increasing PCM activation.</li></ul></td></tr><tr><td>2013<br>[181]</td><td>RT-27, SP-25 A8, ester</td><td>EcoInvent 2009/-</td><td>Catalonia</td><td>EI99 (HH, EQ, NR)</td><td><ul><li>Ester slightly outperformed salt hydrates in manufacturing impact.</li><li>Salt hydrates (152.14) or ester (149.79) as PCM in the cubicles reduce total impact 9 % and 10.5 %, respectively, compared to paraffin (167.35).</li></ul></td></tr><tr><td>2013<br>[182]</td><td>Micronal DS 5001</td><td>EcoInvent 2009/-</td><td>-</td><td>EI99 (HH, EQ, NR)</td><td><ul><li>Micro-encapsulated PCM in rammed earth increased manufacturing impact up to 4.5 ×.</li></ul></td></tr><tr><td>2012<br>[183]</td><td>SP-25 A8, Micronal® DS 5001</td><td>-</td><td>Catalonia</td><td>EI99 (HH, EQ, NR)</td><td><ul><li>Macro-encapsulation is recommended as a more sustainable alternative.</li><li>Adding PCM increases environmental impact during manufacturing and disposal.</li><li>Macro-encapsulated salt hydrate in ALV increased impact by ~8 %, while micro-encapsulated paraffin in concrete raises it by 53 % due to high embodied energy and encapsulation materials.</li></ul></td></tr><tr><td>2013<br>[184]</td><td>Micronal DS5008X, ClimSel C24, ClimSel C21</td><td>Ecoinvent v2.2/ SimaPro</td><td>Almeria, Valencia, Santander, Zaragoza, Burgos</td><td>ReCiPe-M (CC, HT, AP, ODP, PM, EP)</td><td><ul><li>Salt hydrate PCM (ClimSel C21) showed the best performance, reducing environmental impact by 24–34 % over 50 years.</li></ul></td></tr><tr><td>2010<br>[185]</td><td>RT-27, SP-25 A8</td><td>EcoInvent 2009/-</td><td>Catalonia</td><td>EI99 (HH, EQ, NR)</td><td><ul><li>Highest benefit (34 %) was achieved in Almeria.</li><li>While PCM reduced operational energy use, the overall lifetime impact remained high unless low-impact materials are used.</li><li>SP-25 A8 had ~75 % lower manufacturing impact than RT-27, improving total performance.</li><li>Benefits are greater in climates with stable year-round temperatures due to more frequent PCM cycling.</li></ul></td></tr></tbody></table>

#EI99 (HH, EQ, NR): Eco-Indicator 99 (Human Health, Ecosystem Quality, Natural Resources).

#ReCiPe-M (CC, HT, AP, ODP, PM, EP): ReCiPe 2016 Midpoint (Climate Change, Human Toxicity, Acidification Potential, Ozone Depletion Potential, Particulate Matter Formation, and Eutrophication Potential).

#ReCiPe-E (HH, EQ, RS): ReCiPe 2016 Endpoint (Human Health, Ecosystem Quality, Resource Scarcity).

#GWP (GWP100/GWP20): Global Warming Potential, over 100 or 20 years.
<figure><img src="image_15.png" /><figcaption>**Fig. 12.** Variation of payback period with ventilation rate and PCM thickness in different Moroccan climate zones. Reproduced with permission [191]. Copyright 2025, Elsevier.</figcaption></figure>

objectives increases, as distinguishing among solutions becomes more challenging. PSO is valued for its fast convergence and flexibility in both continuous and discrete domains, though it may struggle to preserve diversity across the Pareto front in MOO settings, thereby limiting its coverage of optimal trade-offs [218]. RSM, a surrogate modeling

technique, is advantageous when data are limited or computational costs are high, though its accuracy diminishes in highly non-linear or high-dimensional problems. Thus, choosing an appropriate optimization method requires balancing computational efficiency, solution diversity, accuracy, and problem complexity.
<table><caption>**Table 10**
Methods used in MOO.</caption><thead><tr><th>Name</th><th>Definition</th><th>Type</th><th>Diversity mechanism</th><th>Method</th><th>Strength</th><th>Application</th></tr></thead><tbody><tr><td>NSGA-II [195]</td><td>Utilized elitism, non-dominated sorting, and crowding distance to efficiently find Pareto-optimal solutions in multi-objective problems.</td><td>Evolution</td><td>Crowding distance</td><td>Population-based evolution</td><td>Effective for discrete optimization</td><td>[196-201]; [202,203] for NSGA; [204,205] for NSGA-III</td></tr><tr><td>GA [206]</td><td>Based on the principles of natural genetics and selection, employed selection, crossover, and mutation to evolve better solutions over successive generations [207].</td><td>Evolution</td><td>Crossover and mutation</td><td>Population-based evolution (selection, crossover, mutation)</td><td>Maintains a diverse Pareto front</td><td>[208]</td></tr><tr><td>RSM [209, 210]</td><td>A mathematical and statistical approach is used for designing experiments and optimizing responses influenced by multiple independent variables, often using regression models to predict outcomes.</td><td>Statistical /Mathematical</td><td>Not explicitly controlled</td><td>Regression-based modeling</td><td>Widely used in engineering and energy applications</td><td>[211,212]</td></tr><tr><td>PSO [213]</td><td>Used particles to explore a hyperspace for an optimal solution by iteratively updating their velocity and position based on their personal best and the global best until a stopping criterion is met [214].</td><td>Swarm Intelligence</td><td>Swarm diversity</td><td>Each particle updates its velocity and position</td><td>Suitable for both discrete and continuous optimization, flexible, and robust against local optima</td><td>[214]</td></tr></tbody></table>

Among these, NSGA-II has been widely applied in the optimization PCM-integrated walls. In a recent study by Wang et al. [196], annual electricity consumption (EC), and global carbon emissions (GCE), and life-cycle cost (LCC) were considered as objectives during optimizing office buildings with phase-change walls located in cold regions. The optimal solution for exterior phase-change walls was a 20 mm PCM layer thickness with a melting temperature of 21.6 °C. It reduced energy consumption by 13.58 %, lowering carbon emissions by 0.61 %, and cutting life cycle costs by 4.97 % compared to the prototype building, as shown in Fig. 13 (a). Similarly, for the interior phase-change walls, the optimal PCM thickness was also 20 mm, and the melting temperature was adjusted to 19.5 °C. The corresponding EC, LCC, and GCE values were 19.14 kW h/(m²·y), 3226.46 CNY/m², and 1410.05 kg CO₂e/m², showing reductions of 13.67 %, -4.95 %, and 0.67 %, respectively, compared to the prototype building, as shown in Fig. 13 (b). In another example, a vernacular house [201] was optimized using NSGA-II, and the results showed energy savings of over 50 % and 29.40 % reduction in both operational and embodied carbon emissions compared to conventional buildings.

However, some studies [219,220] have demonstrated and validated that NSGA-III is more accurate than NSGA-II for solving MOO problems with more than two objectives. Yang et al. [204] implemented NSGA-III to optimize a PCM-integrated building envelope system. Based on the Pareto-optimal solutions indicated that the absolute optimal PCM system reduced energy use by 45.38 % [221] and increased life cycle carbon reduction by 10.75 kg·CO₂·e/m² compared to conventional buildings. Over a 50-year period, the system also provided an economic benefit of 452.21 CNY/m².

Artificial Intelligence (AI) is increasingly being applied in the field of sustainable building design, particularly in the early design stage, where AI-driven optimization can rapidly identify high-performance configurations [222]. Within AI, Machine Learning (ML) enables algorithms to autonomously learn from data and make predictions without explicit programming [223]. Common ML techniques used in MOO include deep-learning models and reinforcement-learning agents.

Among surrogate models, Artificial Neural Networks (ANN) are widely used to approximate the outcomes of physics-based simulations [52]. In PCM-integrated wall studies, hybrid frameworks that combine ANN with evolutionary optimization algorithms are increasingly common. Typically, an ANN is first trained on simulation datasets (e.g., generated by EnergyPlus or TRNSYS) to predict thermal performance indicators such as heating and cooling loads based on input parameters like PCM thickness and melting temperature. These trained models are then embedded in MOO algorithms to identify optimal design configurations without needing to rerun full simulations for each candidate.

In the study by Lin et al. [224], six optimization algorithms—NSGA-II, PSO, Strength Pareto Evolutionary Algorithm II (SPEA-II), Pareto Envelope-based Selection Algorithm II (PESA-II), Multi-Objective Whale Optimization Algorithm (MOWOA), and Multi-Objective Slap Swarm Algorithm (MSSA)—were coupled with ANN models to optimize building-integrated photovoltaics with a Trombe wall and PCM. Results showed that SPEA-II achieved the best performance with the lowest Pareto front, while NSGA-II demonstrated the ability to generate a continuous Pareto front of solutions.

The integration of NSGA-II with ANN has been successfully demonstrated in several studies [198,199]. Specially, Bagheri-Esfeh et al. [198] utilized a GMDH-type ANN trained on EnergyPlus simulation data to predict building cooling and heating loads based on PCM design parameters. The derived polynomial models were then used in an NSGA-II framework to optimize PCM thickness and melting temperature. For a residential building in Tehran, the optimal configuration involved a optimal PCM layer thickness of 0.032 m and a melting temperature of 24.58 °C, resulting in significantly improved thermal performance.

Although ANN-based optimization frameworks show considerable promise, the current body of research is still limited. A key challenge is the practical reliability of ANN models. Most existing studies train ANN on simulation-generated data sets that rarely capture the full complexity and variability of real-world building conditions. As a result, such models can be prone to overfitting and may perform poorly when applied to different climates, occupancy patterns, or construction types. Even when full-scale experimental data are available, assembling sufficiently large, high-quality data sets is logistically challenging and costly. Finally, the inherently 'black-box' nature of ANN architectures hampers transparency, making it difficult for practitioners to interpret or trust the decision-making processes of models [225].

To address these limitations, future research should explore real-time optimization strategies enabled by the Internet of Things, allowing dynamic control of thermal systems in response to live environmental and user data. These systems could leverage MOO frameworks to balance energy efficiency, thermal comfort, and cost under variable conditions. Additionally, integrating advanced intelligent techniques such as reinforcement learning and Bayesian optimization into PCM decision-making could enhance system adaptability, enabling autonomous learning from building performance and user interaction. These approaches hold strong potential for improving resilience and performance in the face of climate variability and occupant behavior uncertainty.

## 9. Recommendations of future research

From the perspective of achieving NZEB, the application of PCM in
<figure><img src="image_16.png" /><figcaption>(a) The exterior walls with PCM.</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>(b) The interior walls with PCM.</figcaption></figure>

<caption>Fig. 13. Pareto results using multi-objective optimization. Reproduced with permission [196]. Copyright 2025, Elsevier.</caption>

building walls has broad potential. However, several research gaps remain. The following areas are recommended for further investigation.

1) Integration of recycled waste with PCM in various ratios within building walls. Improper use of PCM in building walls can significantly increase energy consumption. Thus, incorporated recycling waste into walls not only enhances the sustainability of building materials, but also improves thermal comfort. Such integration

contributes to energy reduction and supports the NZEB objective. Moreover, Abdulmunem et al. [226] combined recycled waste paper and PCM as an inner cladding layer. The experimental result revealed that this innovative method provided good acoustic and thermal insulation, and contributed to a marked reduction in the cooling and heating loads.

2) Combination of PCM and hygroscopic materials in building walls. Both thermal and humidity comfort need to be taken into
consideration to enhance overall indoor comfort and air quality. Bio-
based material is an ideal hygroscopic material, such as wood, straw,
hemp, and cellulose insulation. Wu et al. [227]. Integrated hemp
lime concrete and PCM into building envelopes to study their
hygrothermal behavior. The experiment results showed that this
configuration has both high thermal inertia and hygric inertia.

3) The evaluation of PCM-integrated walls should use a more holistic and comprehensive approach. Current research often focuses on energy performance, with exergy, environmental, and economic analyses addressed unevenly or in oversimplified ways. The 4E framework remains limited, with only a few studies addressing all four aspects. Future studies should aim to incorporate a more balanced and detailed evaluation across all four aspects to enhance decision-making in PCM applications.

4) The field lacks standardized and harmonized evaluation criteria for assessing PCM-integrated walls. A comprehensive evaluation framework should evaluate thermal performance, exergy efficiency, environmental impact, and economic viability, and be adaptable to different climatic zones. A systematic review of existing benchmarks is necessary to establish clear guidelines, providing technical support for researchers and engineers working in this field.

5) Integrating advanced machine learning techniques in multi-objective optimization can significantly enhance both computational efficiency and predictive accuracy. Methods such as deep learning, reinforcement learning, and surrogate modeling should be further explored to improve solution quality, accelerate convergence, and facilitate data-driven decision-making.

6) Long-term durability of PCM under real-world operating conditions should be investigated. Repeated thermal cycling can lead to material degradation, such as phase separation, reduced latent heat capacity, or leakage. Therefore, PCM stability over time must be experimentally tested and evaluated. Additionally, improving material formulations to enhance thermal reliability, chemical stability, and encapsulation durability is essential to ensure consistent performance and facilitate large-scale application.

7) Although PCM have demonstrated significant potential in simulation and laboratory studies, their widespread adoption in the construction industry remains limited. Future research should address practical challenges such as high initial investment costs, complexities in installation and maintenance, and the lack of established building code guidelines. There is a pressing need to develop and commercialize PCM that are both cost-effective and thermally stable. In addition, national and international building codes should incorporate clear standards and acceptance criteria for the design, construction, and validation of PCM-integrated building systems.

10. Conclusions

This review has provided a comprehensive evaluation of PCM inte-
grated into building walls, analyzing their performance in terms of en-
ergy, exergy, environmental, and economic aspects within the context of
NZEB. Findings from various studies highlight the potential of PCM to
reduce energy consumption, enhance thermal comfort, and support
sustainability goals across diverse climatic conditions.

The key findings and their practical implications are summarized as
follows.

1) Solid-liquid PCM, predominantly integrated through encapsulation, effectively enhance solar energy utilization and reduce dependence on fossil fuels. This underscores the importance of selecting PCM types and encapsulation methods carefully to maximize durability and thermal performance in real-world building applications.

2) Various PCM integration methods (integrated into bricks, applied as a separate wall layer, and mixed with raw materials) offer unique advantages and challenges concerning heat storage capacity, energy efficiency, and ease of implementation. Practically, this indicates

that architects and engineers must consider specific climate condi-
tions and building requirements carefully when choosing an appro-
priate integration strategy.

3) Exergy analysis has identified critical inefficiencies within systems, highlighting the crucial role of PCM selection, system configuration, and climatic conditions in optimizing overall performance. PCM with lower latent heat capacity and higher heat of fusion tend to exhibit superior exergy efficiency. Additionally, integrating PCM into advanced configurations (e.g., PV-PCM ventilation walls and double-layer PCM Trombe walls) can further enhance exergy efficiency. In practical terms, incorporating exergy-based analysis during the early design phase can help practitioners in improving system efficiency and maximizing the practical benefits of PCM installations.

4) PCM contribute notably to reducing carbon emissions and fossil fuel dependency throughout the building lifecycle, particularly in buildings with extended lifetimes. However, the sustainability impact varies significantly depending on the type of PCM and local climate conditions. Practitioners should prioritize salt hydrate-based PCM, especially in extreme climates, to enhance sustainability outcomes.

5) Although PCM integration offers energy cost savings during operational phase, the high initial investment cost remains a barrier. Salt hydrate-based PCM typically have lower initial costs, suggesting that their use may accelerate the economic feasibility of PCM-integrated walls. For comprehensive financial decision-making, LCCA and exergoeconomic assessment are recommended over simple payback calculations.

6) The use of multi-objective optimization methods, especially NSGA-II, has been proven effective in balancing conflicting objectives. Moreover, hybrid approaches combining NSGA-II with ANN provide enhanced accuracy and reduced computational costs. This practical insight suggests that designers should increasingly adopt hybrid optimization methods to effectively address complex PCM design scenarios.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

It is gratefully acknowledged that the first author was supported by
the China Scholarship Council.

Data availability

No data was used for the research described in the article.

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