Radiogenic Heat Production in West Malaysian Granites and Implications for Geothermal Energy Open Access

Malaysia is among the largest oil consumers, heavily reliant on natural gas and coal. To improve sustainability, the nation aims to boost its renewable energy share from 2% to 20% by 2030 [1]. Among the promising renewable energy sources, geothermal energy remains underutilized in Malaysia [2]. The Malaysian rift system features over 100 hot spring locations, many of which are associated with granite intrusions or situated in sedimentary regions near these intrusions [2-5]. These geothermal sites are categorized by temperature, ranging from low to medium, though the specific heat sources still need to be fully confirmed. In Peninsular Malaysia, hot springs such as those in Sungai Klah and Ulu Slim are linked to regional granite intrusions that have been cooling since the Triassic period [6]. These springs are commonly found in areas with high-permeability host rocks, typically associated with fault zones like Slim and Bukit Tinggi. These fault zones facilitate significant meteoric water infiltration into regions with notable geothermal gradients. With the exception of the Sabah volcanic district, Malaysia’s hot springs are classified as nonvolcanic [2, 5, 7].

Research into geothermal systems has advanced through various methods, with numerous studies focusing on West Malaysia [2, 8-12]. However, many earlier studies have not explored the radiogenic heat contribution from granite belts, while recent studies have highlighted the significance of RHP in nonvolcanic geothermal systems, particularly in granite-rich regions [13-15]. The heat flow rates in West Malaysia can reach up to 150 mW/m², particularly in regions with hot spring manifestations, as reported by [11, 16]. These high rates are likely associated with radiogenic granite in the upper crust of Peninsular Malaysia, contributing to the increased thermal output in these areas. This geological feature significantly influences the thermal characteristics of the region. Heat sources in Bangka Island’s granite are associated with radiogenic decay and have significant nonvolcanic geothermal potential [17]. [18] recommended, in their comprehensive review of the history and development stages of geothermal exploration in West Malaysia, calculating the RHP for the region and linking it with both hot and nonthermal springs across the three belts of Malaysia, ensuring accurate concentration assessments in the western belt. Although there is a lack of studies examining the influence of radiogenic heat generation on the geothermal potential of West Malaysia [17], certain outcomes were evaluated to draw parallels with their research conducted on Bangka Island, Indonesia. Nevertheless, uncertainties remain because of the quantity of samples and their uneven distribution regarding the granite belts, as well as their association with hot springs. Their investigation established a relationship between RHP and the geothermal system of Bangka Island, with minimal comparisons drawn to the Malaysian geothermal framework. While the researchers utilized heat flow data from the offshore region of East Malaysia, they omitted specific measurements for terrestrial sites in West Malaysia, particularly in relation to the locations of thermal springs. This lack of comprehensive understanding highlights the critical necessity for additional scholarly investigation to elucidate the degree to which radiogenic heat impacts geothermal dynamics within Malaysia, thereby establishing a basis for the RHP database and evaluating the role of RHP within the geothermal framework of West Malaysia. RHP in rocks, mainly from the decay of terrestrial radioisotopes such as uranium (U²³⁸), thorium (Th²³²), and potassium (K⁴⁰), is crucial in the Earth’s crust’s thermal regime [19, 20]. Granites, prevalent in the continental crust, exhibit varying RHP values influenced by their emplacement ages and geological histories. On a global scale, the various nonvolcanic geothermal manifestations, which encompass a wide variety of phenomena such as low-to-medium temperature hot springs, are frequently associated with geological formations of granite and the presence of active fault systems that contribute to the geothermal activity in these regions [8, 21-23]. The global average RHP for granites is approximately 2.92 ± 1.86 μW/m³, with variations based on granite age and composition [24]. For example, granitoids in the Sierras de Cordoba, Argentina, show significant RHP variability, with A-type granitoids reaching up to 4.54 ± 1.38 μW/m³ [15].

In China, granitoids in regions like western Sichuan and southeastern China contribute substantially to geothermal resources, with RHP values averaging above the global mean [14, 25, 26]. Similarly, studies in Egypt’s Eastern Desert and Indonesia’s Bangka Island highlight the importance of granitoid intrusions for geothermal heat production [17, 27-29].

Despite these advancements, radiogenic geothermal systems in Malaysia still need to be explored. This study aims to investigate geothermal anomalies and heat source controls across Peninsular Malaysia by analyzing 139 granite samples from three major granite belts as well as a few samples from other rock types. The study will include both hot spring-associating and nonassociating granite samples, along with five granite samples and a rhyolite sample from recent investigations in Perak. By comparing these samples with existing data on U, Th, and K contents, the study will compute RHP to assess their contributions. This pioneering study comprehensively examines RHP from granites across three distinct belts, providing invaluable insights into Malaysia’s radiogenic geothermal systems. These findings will significantly contribute to the advancement of sustainable geothermal energy solutions.

Peninsular Malaysia, spanning approximately 183,000 km² from the Isthmus of Kra to Singapore, is a crucial component of Sundaland, the continental core of Southeast Asia. The peninsula is traditionally divided into three distinct north-south longitudinal belts: Western, Central, and Eastern (Figure 1). Each belt reflects different phases of geological evolution characterized by discrete changes in stratigraphy, structure, magmatism, and volcanism [30, 31]. The Western Belt, part of the Sibumasu terrane, consists of a Paleozoic sedimentary sequence overlying a Precambrian basement and was derived from NW Australian Gondwana in the late Early Permian [32]. The Central Belt is characterized by the Bentong-Raub Suture Zone, a narrow N-S zone that represents the remnants of the Paleo-Tethys Ocean, containing oceanic sediments, mélange deposits, and ophiolitic rocks [33]. This suture zone has recorded significant strike-slip motion and is associated with several gold mines and prospects. The Eastern Belt, comprising the East Malaya block, features Carboniferous to Triassic sequences of sedimentary and volcanic rocks overlying an older basement [31]. The Central and Eastern Belts, now considered a single tectonic unit known as the East Malaya Block, were part of the Indochina-East Malaya Terrane that separated from Gondwana in the Devonian [32, 34].

The tectonic evolution of Peninsular Malaysia is marked by several key events, including the opening of the Paleo-Tethys Ocean during the Early Devonian, its subsequent closure during the Triassic resulting in the Indosinian Orogeny, and the collision of the East Malaya block with Sibumasu in the Late Triassic [33]. This complex history is reflected in the distribution of granitic intrusions across the peninsula, as illustrated in Figure 2. The Western Belt is dominated by the West Malaya Main Range S-type granites of Late Triassic to Early Jurassic age (227, 201 Ma), with some older I-type granites in the northwest dating back to the Permian (280, 260 Ma) [6, 35-39]. These granites are characterized by high initial Sr⁸⁷/Sr⁸⁶ ratios (>0.710) and negative εNd values (-6, -10) [37, 40]. The Eastern Belt is dominated by I-type granitoids ranging from Middle Permian to Late Triassic in age (270, 200 Ma), formed in a precollisional arc setting [6]. A significant Late Cretaceous thermo-tectonic event affected the Malaysian Peninsula, resulting in major faulting, granitoid intrusion, and reorientation of paleomagnetic signatures. The granitic intrusions play a significant role in the region’s metallogenesis, particularly for tin mineralization, with the main phase of tin-bearing granite emplacement constrained to 220-210 Ma [41], coinciding with the late stages of the Indosinian Orogeny.

This study examines five granite samples and one rhyolite sample from Ulu Slim, Perak State, a region with the highest geothermal manifestations in West Malaysia. It has been identified as having the second highest recorded surface and subsurface temperatures in the region [2]. In the graphs, these samples are distinguished by black points within the data markers and are labeled with sample IDs from D1 to D6. Geochemical data from the past few decades across Peninsular Malaysia were integrated to estimate the rate of RHP in granites associated with hot springs and those not associated. A total of 139 samples were analyzed, sourced from the granite belts in Malaysia, along with a few additional samples from various rock types for comparative analysis. For this research, granites are classified as hot spring-associated if they directly outcrop at hot spring locations such as Ulu Slim, belong to the same plutonic body that serves as a heat source even if located up to 5 km from surface manifestations, or constitute the nearest granitic body to hot springs emerging through sedimentary formations.

The collected samples were first crushed and pulverized into a fine powder. Each powdered sample was then weighed accurately before being dissolved in an acid mixture (aqua regia or a combination of HNO₃, HCl, and HF) to achieve complete digestion of the minerals. The resulting solution was diluted with deionized water to a final volume of 50 mL, ensuring uniform concentration for analysis. This preparation method was implemented in accordance with standard geochemical analysis protocols (e.g. USEPA SW-846 Method 3050B and ASTM D3682-13). The use of a strong acid mixture ensures complete dissolution of silicate minerals, allowing for accurate trace element analysis.

To quantify the trace elements U, Th, and K, the prepared liquid samples were analyzed at the Centre for Natural and Physical Laboratory Management UKM (ALAF-UKM) using a PerkinElmer Inductively Coupled Plasma Mass Spectrometry (ICP-MS) instrument. This instrument was selected for its high sensitivity and precision in detecting trace elements across various matrices. Additionally, X-ray fluorescence (XRF) spectrometry was used as a complementary technique to analyze the major and trace element composition of the rock samples, providing a cross-validation method alongside ICP-MS. The equipment was calibrated using a systematic approach to ensure accuracy. First, a reagent blank and a series of certified reference standards (Standard 1–6) were prepared and analyzed to establish calibration curves. Internal standards such as Sc, Y, In, Tb, and Lu were added to each sample to correct for matrix effects and signal drift. Prior to sample analysis, the instrument was tuned using a multielement tuning solution containing elements like Li, Be, Mg, Co, In, and U, ensuring optimal mass resolution and sensitivity. Periodic quality control (QC) samples and duplicates were analyzed to verify instrument stability and accuracy, ensuring that measurement deviations remained within acceptable limits.

RHP is a key physical property that quantifies the heat generated by the decay of radioactive isotopes within a unit volume of rock over time. The RHP can be calculated by considering U, Th, and K concentrations of rocks [42-46]. To calculate RHP rates, the following formula was applied:

RHP (μW/m³) = ρ(9.52×C_U+2.56×C_Th+3.48×C_K) ×10⁻⁵ (1)

Where:

• ρ is the density of the rock (in kg/m³).

• C_U is the concentration of U in the rock (in ppm).

• C_Th is the concentration of Th in the rock (in ppm).

• C_K is the concentration of K in the rock (in %).

  To accurately calculate RHP, it is essential to use realistic density values for the granite samples. Rock density (ρ) can be highly variable, depending on the specific mineral composition and texture of the rock. For this study, density was estimated using regression models based on oxide weight percentages, following the methodology outlined by [47] and [48]. These models were constructed to estimate the density of rocks based on their geochemical composition, drawing upon the foundational work of these researchers.

  We tested four distinct regression models for density estimation, each incorporating different sets of oxides or geochemical indices:

  Model 1: Seven oxides—SiO₂, Al₂O₃, MgO, FeOᵀ, CaO, Na₂O, and K₂O.

  Model 2: Three oxides—SiO₂, MgO, and CaO.

  Model 3: Four oxides—SiO₂, Al₂O₃, MgO, and Na₂O.

  Model 4: Geochemical indices—Fe-number, MALI, ASI, and maficity.

  The performance of each model was evaluated by comparing the predicted density values with the Perplex HS (high sensitivity) density calculations. Figure 3 presents a comparison of the density values from the Model and the Perplex HS results, highlighting the model’s robustness and its balance between sensitivity to compositional variations and alignment with the Perplex HS values.

  Among the four models tested for density estimation, Model 1 produced a broad density range (3000, 5000 kg/m³), significantly higher than the granite range, suggesting potential overestimation. In contrast, Model 2 exhibited the narrowest range (2754, 3043 kg/m³), though its limited oxide selection may underrepresent compositional variations. Model 3, on the other hand, generated systematically high-density values (3060, 4135 kg/m³), which were above the expected range for granitic rocks, indicating that it may not accurately reflect typical granite densities. In comparison, Model 4 provided more moderate density values and demonstrated the best correlation with the Perplex HS calculations, aligning well with the findings of [48]. This makes Model 4 the most reliable and consistent model for density estimation in this study.

  Based on our analysis, Model 4, which uses geochemical indices (Fe-number, MALI, ASI, and maficity), was found to be the most reliable for estimating density. These indices are more stable and show less variability compared to single oxides, making Model 4 a more consistent and robust tool for estimating our granite sample density. After applying the density modification, our preferred model (Model 4) for estimating density is given by:

ρ = 2486.5+14.7×Fe^∗−12×MALI+49.6×ASI+636×Maficity (2)

Where the geochemical indices are defined as:

Fe* (iron number) = C_FeOT/(C_FeOT + C_MgO)⁻¹

MALI (modified alkali-lime index) = C_Na2O + C_K2O − C_CaO

ASI (alumina saturation index) = n_Al/(n_Ca − 1.67 _nP + n_Na + n_K)⁻¹

Maficity = n_Fe + n_Mg + n_Ti

Where n is the number of moles of each specified oxide component, and FeO^T is the total iron.

The formula for calculating RHP requires K in mass percent. Because the data from ICP-MS is more reliable, the concentration of K in % mass is calculated from the ICP-MS data (average run/measurement). Calculation of K (% mass) from ICP-MS begins by adding up all the concentrations of each element in each sample. Then, the K concentration is divided by the total concentration to get the K (% mass) concentration in the sample. Finally, the division result is multiplied by the relative atomic mass of K to get the % mass of K. Since K was directly available in the ICP-MS results, it was used for calculations. However, in previous studies where K was not directly measured, it was derived from K₂O content using a conversion factor of 0.83, as applied in [13]. This approach ensures that the potassium contribution is accurately reflected in the heat production calculations.

Based on the granite classification by [15], the samples can be categorized according to their heat production values into high heat production granites (>5 μW/m³), marginal heat production granites (ranging from 3 to 5 μW/m³), and low heat production granites (<3 μW/m³). This classification provides a valuable framework for assessing the geothermal potential of the analyzed granite samples, offering a systematic approach to identifying promising areas for geothermal energy exploration.

The estimated RHP in granitic rocks from West Malaysia reveals significant variation based on the rocks' association with hot springs (HS). The study area is characterized by a wide range of RHP values, spanning from 1.5 to 17.83 μW/m³, with an overall average RHP of 5.7 μW/m³. However, when the samples are categorized into two groups, a notable difference emerges. As shown in Figure 4, granites associated with hot springs have an average RHP of 6.65 μW/m. In contrast, those not associated with hot springs have a lower average of 3.88 μW/m³.

The overall average RHP (5.7 μW/m³) is significantly higher than typical crustal values (2.04 ± 1.83 μW/m³ [49]), indicating a higher concentration of heat-producing radioactive elements (U, Th, and K) in the study area. The marked difference between HS-associated and non-HS-associated granites suggests a potential link between higher RHP and the occurrence of hot springs. The high standard deviations in both groups indicate considerable variability in RHP values, with some samples showing exceptionally high values up to 17.83 μW/m³, while others are as low as 1.5 μW/m³.

Interestingly, a significant proportion of the studied samples (47%) display RHP values ranging from 5 to 9 μW/m³. This indicates that most granitic rocks within the region display elevated levels of RHP, presumably resulting from consistent geochemical characteristics across numerous samples. A significant portion of the remaining samples displays moderate RHP levels, while a smaller percentage shows low or very high RHP levels. Although extreme measurements are recorded (reaching up to 17.83 μW/m³ and as low as 1.5 μW/m³), such values signify localized disparities in mineralogical composition and do not accurately reflect the overarching pattern.

The elevated RHP values, especially in hot spring-associated granites, could significantly influence the geothermal characteristics of the region. The distinction between HS-associated and non-HS-associated granites provides valuable insights for geothermal exploration and resource assessment. The moderate heat production observed in the majority of samples could have essential implications for crustal heat flow, heat source, and potential geothermal energy applications in West Malaysia.

This analysis underscores the importance of considering the association with hot springs when evaluating the region’s RHP potential of granitic rocks. The higher RHP values in HS-associated granites indicate areas of more significant geothermal potential, while the overall elevated RHP compared to typical crustal values suggests that the West Malaysia area is a promising region for geothermal energy exploration.

Overall, this investigation found that Peninsular Malaysia’s granitic rocks had RHP values that are much greater than the world average for Mesozoic–Cenozoic granites (3.09 ± 1.62 μW/m³, as reported by [50]). These values surpass those of highly radioactive A-type granites in the eastern and western belts, indicating a notable enrichment of radioactive elements within the granites. As shown in Table 1, the RHP values in Peninsular Malaysia exceed the reported ranges for granites in China (0.52, 10.86 μW/m³) [14], Argentina (0.63, 4.09 μW/m³) [15], Turkey (0.89, 6.98 μW/m³) [51], Germany (0.63, 4.09 μW/m³) [52], and the Northeastern Arabian Shield (1.82, 8.04 μW/m³) [53]. Furthermore, the observed RHP values are comparable to those found in high-temperature geothermal regions, such as the Cooper Basin in Australia, where RHP ranges from 7 to 10 μW/m³ [54]. In particular, the Luanchuan Region in China, known for its rich granitoid formations, recorded RHP values ranging from 1.7 to 14.44 μW/m³ in Late Mesozoic granitoid [55]. This range of RHP values aligns closely with the higher end of those found in Peninsular Malaysia, highlighting the geological similarity between the two regions, particularly in their petrogenesis, as the Luanchuan region also hosts I-type, A-type, and partly S-type granitoids. These findings emphasize that Peninsular Malaysia’s granitic rocks not only exhibit exceptionally high RHP values but also align with regions known for high geothermal gradients, suggesting that Malaysia’s granites may hold considerable potential for future geothermal exploration.

The geochemical analysis reveals a strong positive correlation between U and Th concentrations and RHP in the granite samples, as shown in Figures 5(A) and 5(B). Among the two elements, U exhibits a stronger linear relationship with RHP (R² = 0.78), while Th shows a slightly weaker but still significant correlation (R² = 0.65). These results are consistent with the well-documented role of U and Th as primary contributors to heat production in granitic rocks [56, 57].

K shows a weaker and more scattered association with RHP (Figure 5(C)), as evidenced by both its low feature importance in the machine learning model and the significant scatter in its data points. Similarly, the relationship between rock density and RHP (Figure 5(D)) is unclear, with no consistent pattern observed across the density range. These findings suggest that while U and Th are crucial to understanding the radiogenic heat budget of granites, K and rock density have minimal influence on RHP variation [50, 58].

To further assess the predictive power of these elements, a Random Forest Regressor was applied (Figure 6). The model, trained on U, Th, and K concentrations, achieved a high coefficient of determination (R² = 0.92) and a mean squared error of 0.54, reflecting strong predictive accuracy. Feature importance analysis from the model revealed that U is the most significant predictor of RHP, contributing approximately 73% to the model’s performance. Th follows with 24%, while K accounts for just 3%. This ranking not only highlights the dominant role of U in predicting heat production but also aligns with the statistical correlation results, where U showed a stronger relationship with RHP than Th.

This analysis underscores the considerable contribution of RHP to the overall heat source in geothermal systems. Higher concentrations of U, Th, and K in granites lead to increased RHP values, which significantly enhance the total heat flow in geothermal areas [59, 60]. Previous studies have demonstrated that RHP can account for up to 40%–60% of surface heat flow in certain granitic terrains [61-63], further emphasizing the importance of RHP in evaluating geothermal potential. The consistently higher RHP values observed in hot spring-associated granites suggest that these regions may possess greater geothermal energy potential due to the additional heat generated by radioactive decay [43, 64].

Figure 7 presents a 3D scatter plot depicting the relationship between silica (SiO₂) content, density, and RHP in granite rocks, both associated with hot springs (HS) and those not. The SiO₂ content ranges from approximately 45%–78%, with a concentration peak between 60% and 75%, while RHP values span from 1.5 to 17.83 μW/m³. The plot highlights a positive correlation between SiO₂ content, density, and RHP, consistent with observations from previous studies [15, 50, 51, 65]. This relationship suggests that higher SiO₂ concentrations are linked to increased levels of large ion lithophile elements (U, Th, and K), which contribute to elevated RHP values through magmatic differentiation processes.

Granites associated with hot springs generally exhibit higher RHP values and greater variability in RHP, particularly at higher SiO₂ concentrations. The variability in SiO₂ and RHP is observed to be more pronounced at elevated silica levels, while density shows a more consistent range across the different granite types. Some samples exceed 11 μW/m³, reaching up to 16 μW/m³, at approximately 70%–75% SiO₂. In contrast, nonhot spring-associated granites tend to maintain RHP values below 10 μW/m³, with a more consistent range of densities across varying SiO₂ contents. The relationship between these variables is not entirely linear. Some samples with varying SiO₂ contents (e.g. 64.36%, 65.38%, 69.68%, and 75.69%) exhibit unexpectedly low RHP values of approximately 1–2 μW/m³, suggesting that complex geochemical processes in evolved magmas can influence RHP, as noted in recent studies [14, 15, 66, 67].

These observations indicate that hot spring formation or alteration processes may concentrate heat-producing elements in hot spring-associated granites, resulting in higher and more variable RHP compared to nonassociated granites, especially at higher silica contents. The data highlight the intricate interplay between silica content, density, radiogenic element concentrations, and geological processes in determining the RHP of granitic rocks.

The Th/U ratio is a critical geochemical parameter used in characterizing granitic rocks and provides valuable insights into the source variations of these rocks [29], as this ratio remains relatively stable during partial melting processes [50, 68, 69]. The Th/U ratio also reflects the migration behaviors of U and Th, which are crucial for understanding the formation and evolution of Earth’s crust and its tectonic systems [70]. In weathered granitic plutons, the Th/U ratio can indicate environmental impacts, particularly on aquatic ecosystems under changing climatic conditions [71].

Historically, the Th/U ratio has been utilized to distinguish between different crustal levels. As per [72], the Th/U ratios of 3.8, 4.9, and 6.0, respectively, are indicative of the upper, middle, and lower crust. This variation reflects the differing contributions of U and Th in different crustal segments. Furthermore, the Th/U ratio shows a gradual decline from early Proterozoic to Paleozoic granites, with the lowest ratio of approximately 2.78 found in Archean granites, as reported by [50]. This trend suggests that younger granites are generally enriched in U relative to Th, whereas older granites display a higher concentration of Th. The global indicate ratio of Th/U is determined to be approximately 4.2 [73], providing a reference point for comparison in various geological studies.

In the current study area, the Th/U ratios from hot spring-associated granites range from 0.138 to 8.47, with an average of 2.83 (Figures 8(A) and 8(B)). Notably, Ulu Slim samples (e.g. D3: Th/U = 0.14, U = 14.855 ppm, Th = 2.054 ppm) exhibit extreme U enrichment, consistent with hydrothermal fluid activity in permeable Upper Crust zones, while a Middle Crust outlier (D4: Th/U = 5.25, Th = 42.410 ppm, U = 8.075 ppm) reflects limited fluid interaction or Th-rich magmatic sources. This average is slightly lower than the upper continental crust (UCC) reference value of 3.8 [72], indicating a relative enrichment of U compared to Th. This suggests that U is more readily mobilized than Th in these samples, likely due to hydrothermal processes [74, 75]. Conversely, nonassociated granites exhibit Th/U ratios ranging from 0.758 to 12.59, with an average of 3.90. Although this average remains above the UCC reference value, it is lower than the middle continental crust (MCC) reference value of 4.9 [72]. The elevated Th/U ratios in these nonassociated granites indicate that U plays a significant role in RHP, particularly those with ratios closer to or exceeding UCC benchmarks [56, 65, 76]. The higher Th/U values in nonassociated granites likely reflect magmatic Th retention (e.g. in monazite or zircon) and minimal hydrothermal alteration, contrasting sharply with fluid-mediated U enrichment in hot spring systems.

The U enrichment observed in hot spring-associated granites enhances their RHP potential, as U decay significantly contributes to heat production [65]. The hydrothermal environment surrounding these granites likely facilitates U leaching and transport due to fluid–rock interactions, where U exhibits more solubility in hydrothermal fluids than Th [74, 75]. During such processes, Th generally remains immobile and is retained in the solid phase, while U is mobilized [74]. Petrographic evidence of chloritization and sericitization in altered zones—such as those documented in Malaysian granites [77]—supports this mechanism, as these hydrothermal alteration processes enhance U mobility by destabilizing primary U-bearing minerals [78, 79]. Consequently, the relative enrichment of U in hot spring-associated granites results in lower Th/U ratios. This pattern aligns with the interactions between hot springs and granite-hosted systems, wherein hydrothermal fluids concentrate U in the rocks, thereby decreasing Th/U ratios.

The distribution of Th/U ratios in nonassociated granites may reflect distinct magmatic processes or source compositions compared to hot spring-associated granites, potentially indicating variations in the degree of partial melting, source heterogeneity, or postmagmatic alteration [50, 71]. Examining the Th/U ratios in both sample sets reveals a stronger tendency for U enrichment in hot spring-associated granites. This distinction is likely attributed to the active hydrothermal processes within the hot spring environment, which preferentially mobilize U over Th, resulting in unique geochemical signatures [79, 80].

The wide range of Th/U ratios in both sample sets underscores the complex interplay of magmatic, hydrothermal, and postmagmatic processes in the region, which influence the distribution of these critical heat-producing elements [81]. This variability likely reflects differences in fluid chemistry, temperature, and the duration of fluid–rock interaction, all of which impact U leaching and mobilization [71, 79]. Notably, while the average Th/U ratio for hot spring-associated granites is lower than the UCC value, indicating overall U enrichment, some samples with values up to 8.47 suggest the possibility of Th enrichment in certain instances. This variability may point to differences in hydrothermal processes or source rock compositions across the study area. For example, the Ulu Slim Middle Crust outlier highlights how limited fluid interaction or assimilation of Th-rich crustal material can preserve magmatic ratios even in hydrothermally active regions. A-type granites generally have the highest Th/U ratios, followed by I-type granites, with S-type granites having the lowest ratios. This variation is attributed to source heterogeneities and U mobilization processes rather than fractional crystallization alone [82]. The lower Th/U ratios in hot spring-associated granites are consistent with U mobilization in hydrothermal environments. In comparison, the higher ratios in nonassociated granites suggest Th enrichment due to magmatic processes.

The correlation between eTh and eU in granites is complex and varies based on the rock’s mineralogical composition. Granites typically exhibit higher concentrations of Th compared to U. This disparity arises from thorium’s greater affinity for incorporation into minerals commonly found in granites, such as plagioclase and biotite [83, 84]. Consequently, the Th/U ratio in granites tends to be elevated due to thorium’s stronger retention within the rock matrix. Furthermore, Th has a tendency to generate precipitates that are insoluble throughout a broad pH range, especially in neutral to weakly alkaline environments [85]. These chemical properties contribute to thorium’s stability within the solid phase, even during the hydrothermal events associated with granite formation.

Heat flow measurements across West Malaysia demonstrate significant geothermal activity, particularly concentrated within granitic plutons. In the Western and Eastern Granite Belts, systematic variations in RHP reflect different geological histories and compositional characteristics, which in turn affect local and regional heat flow distributions. Understanding the relationship between heat flow and RHP is crucial for characterizing the region’s thermal structure. RHP influences crustal temperature distribution and surface heat flow [14]. It was found that RHP contributes more than half of the total surface heat flow, emphasizing the need for accurate correlation analysis. Mantle heat flux also affects the region’s overall heat flow [11]. It is estimated that the average natural mantle heat flux in West Malaysia is around 85 mW/m². When combined with radiogenic contributions from granite belts, the total heat flow in the region becomes exceptionally high. For instance [63], estimate that RHP in granitoids contributes approximately 65 mW/m² to the continental surface heat flux, with contributions from both the crust and mantle.

Due to the limited availability of direct borehole measurements, we employed alternative methods to assess heat flow, specifically utilizing and re-analyzing heat flow data from Curie point depth analysis reported by [11]. This method estimates subsurface temperatures by identifying the depth at which rocks lose magnetic properties, providing a reliable proxy for heat flow. The heat flow patterns in West Malaysia confirmed a strong correlation between hot springs and the depth of magnetic sources, with some regions reaching depths as shallow as 7 km. Additionally, significant relationships were identified between near-surface heat sources and magnetic anomalies. They originally reported heat flow values up to 130 mW/m², with a regional average of 85 mW/m²—exceeding the global continental average of 80 mW/m². Similar studies, such as [86] in the southeastern Tibetan Plateau, reported heat flow variations between 44 mW/m² and 108 mW/m² using Curie depth data. Collectively, these studies underscore the effectiveness of Curie point depth analysis as a reliable method for mapping heat flow in areas with limited borehole data.

Our comprehensive analysis of heat flow and RHP distribution across West Malaysia reveals distinct thermal patterns within the Western and Eastern granite belts. The heat flow map, overlaid with RHP measurement points, highlights the spatial distribution of thermal characteristics and their geological implications (Figure 8). The Western granite belt outlined by black lines, primarily composed of S-type granites formed during the Late Triassic (210, 220 Ma), displays significantly higher RHP values. These granites, derived from sedimentary protoliths, are enriched in U, Th, and K, contributing to their elevated RHP. Conversely, the Eastern granite belt represented by the white-shaded region consists of older I-type granites (230, 260 Ma) of meta-igneous origin, which exhibit lower RHP values due to their distinct mineralogical composition.

The Western Granite Belt, situated along longitude 100-101°E, exhibits significantly higher RHP values, ranging from 2.14 to 17.83 µW/m³, with a mean of 6.31 µW/m³. These elevated RHP values in Figure 9 show a clear concentration along the western margin, primarily attributed to the enrichment of U, Th, and K during the formation of S-type granites from sedimentary source materials. Consistently, heat flow measurements in this belt generally exceed 90 mW/m², forming a distinctive north-south trending high-heat-flow zone.

Within this belt, several notable hotspots further reinforce the strong correlation between RHP and heat flow, such as the central region, where two samples in Bukit Berapit record exceptionally high RHP values of 15.98 and 15.14 µW/m³, corresponding to heat flows of 90.96 and 90.21 mW/m², respectively. Similarly, the Taiping sample in location recorded the highest RHP value of 17.83 µW/m³, consistent with the overall high RHP trend. However, its corresponding heat flow (88.15 mW/m²) is slightly lower than expected, suggesting minor localized variations in thermal conductivity or geological composition that may influence heat transfer efficiency. Despite this slight deviation, the western region as a whole continues to exhibit a strong correlation between elevated RHP and high heat flow, further evidenced by the presence of hot springs, particularly in the northern section around 6°N, where heat flow values exceed 100 mW/m². In some areas, such as the Manjung District, elevated RHP is observed, yet the absence of hot springs presents a puzzling scenario. This could indicate that fluid mobilization is restricted due to insufficient permeability or that deep-seated radiogenic sources are isolated from shallow systems. The significant subsurface RHP in the district, without corresponding surface thermal features, suggests that low-permeability lithologies or inadequate fracture networks may hinder fluid circulation, preventing heat from reaching the surface. Alternatively, it is possible that radiogenic heat sources are concentrated in deeper crustal layers, decoupled from the shallow hydrological systems. To clarify these mechanisms, targeted investigations, including thermal conductivity profiling of local rock units, structural mapping of fault systems, and subsurface hydrology modeling, are essential. Without such studies, the geothermal potential of the region and the processes masking its thermal expression will remain speculative, leaving valuable scientific and economic opportunities untapped.

In contrast, the Eastern granite belt, situated between 103°E and 104°E, exhibits lower RHP values, ranging from 1.50 to 9.19 µW/m³, with a mean value of 4.12 µW/m³. These values are predominantly in the lower range (<3 µW/m³), with some moderate to high RHP values (>4 µW/m³ and >8 µW/m³) also present. The heat flow pattern in this region is characterized by lower values, typically between 60 and 80 mW/m². The generally low RHP values contribute to the reduced heat flow in this region, although isolated anomalies persist. For example, a sample at approximately 2.30°N, 103.66° E near Segamat town Johor, exhibits a higher RHP value of 9.16 µW/m³, which corresponds to a localized heat flow anomaly of 103.58 mW/m², demonstrating the direct influence of increased RHP on heat flow. In the southern region of the Eastern belt, where RHP values remain between 1.5 and 3.0 µW/m³, corresponding heat flows around 69 mW/m² reflect the meta-igneous origin and older geological age of the granites, further supporting the correlation between RHP and heat flow.

Figure 10 illustrates the relationship between RHP and heat flow across Peninsular Malaysia’s Western and Eastern Granite Belts. The data reveals a nonlinear correlation characterized by three distinct behavioral zones. A moderate positive correlation is observed in the Western Belt (R = 0.60), while the Eastern Belt shows a stronger correlation (R = 0.75). These R-values highlight regional differences in how RHP influences heat flow, with the remaining variability attributed to crustal thickness, fluid circulation, and geological heterogeneity.

In the RHP zone (<5 µW/m³), heat flow increases steadily at 1.8 mW/m² per µW/m³, reflecting mantle-derived heat transfer through conduction. This pattern shifts in the transitional zone (5, 8 µW/m³), where nonlinear trends and significant data scatter emerge. Samples like D127 (6.42 µW/m³, 87.5 mW/m²) and D132 (7.46 µW/m³, 94.6 mW/m²) exemplify this variability, suggesting competing contributions from mantle heat (dominant at lower RHP) and radiogenic heat (increasingly influential above 5 µW/m³). The scatter likely arises from localized factors such as fault-controlled fluid convection or variations in thermal conductivity. Notably, even at 7.46 µW/m³ (D132), radiogenic heat begins to dominate, justifying an upward revision of the transitional zone’s upper threshold to 8 µW/m³.

The radiogenic-dominant zone (>8 µW/m³) exhibits a steeper heat flow increase (3.2 mW/m² per µW/m³), with values consistently exceeding 90 mW/m². Western Belt samples such as D7 (15.98 µW/m³, 90.96 mW/m²) and D8 (15.14 µW/m³, 90.21 mW/m²) underscore this trend, where radiogenic heat becomes the primary driver. This threshold adjustment (from >7 µW/m³ to >8 µW/m³) better aligns with observed inflection points in the polynomial fits and sample-specific behavior. The nonlinearity across all zones reflects crustal heterogeneity, including depth-dependent RHP distribution and fluid dynamics. For instance, groundwater circulation near fault systems may amplify heat flow in localized areas, particularly in the Eastern Belt, where older rocks (230, 260 Ma) introduce additional variability in thermal properties.

These findings have direct implications for geothermal exploration. High-RHP regions in the Western Belt (e.g. 4.5°N–5°N) with values >8 µW/m³ are prime targets, as they consistently yield heat flow >90 mW/m². The steep response slope (3.2 mW/m² per µW/m³) in these zones suggests fluid-assisted heat transfer, as seen near active hot springs. However, the transitional zone’s scatter emphasizes the need for complementary studies, such as magnetotelluric surveys, to map subsurface fluid pathways and de-risk exploration in areas where heat redistribution complicates the RHP-heat flow relationship.

The geospatial variation in RHP-heat flow relationships strongly correlates with granite type and age. The Western Belt’s S-type granites exhibit higher and more variable RHP values, with a strong correlation between RHP and heat flow, indicating efficient heat transfer mechanisms. This is evident in the map, where clusters of high RHP values (>9 µW/m³) coincide with regions of elevated heat flow, particularly in the central and southern parts of the belt. These areas, represented by warmer colors in the heat flow map, also correspond to the locations of multiple hot springs, suggesting active geothermal processes. In contrast, the Eastern Belt’s I-type granites display more consistent but lower RHP values, with a moderate correlation to heat flow. This is reflected in the thermal mapping, where lower and more uniform heat flow patterns dominate, aligning with the geological characteristics of older, meta-igneous granite formations.

The total heat flow pattern integrates both radiogenic and mantle heat contributions, with the mantle heat flux providing a significant baseline contribution to the regional heat flow. Regions where RHP exceeds 12 µW/m³, particularly within the younger Western granite belt, consistently demonstrate elevated heat flows above 85 mW/m². This pattern persists even in areas lacking surface geothermal manifestations, indicating that RHP serves as a fundamental control on the region’s thermal regime. Western Belt locations with high RHP (>15 µW/m³) maintain heat flows above 90 mW/m², suggesting significant geothermal potential.

This comprehensive analysis demonstrates that while RHP significantly influences regional heat flow, its impact is modulated by granite type, age, and structural setting. The Western Belt, with its younger S-type granites and higher RHP values, exhibits strong geothermal potential, even in areas without surface manifestations, as evidenced by the spatial correlation between high RHP values, elevated heat flow, and hot spring occurrences. In contrast, the Eastern Belt, dominated by older I-type granites, displays lower RHP and heat flow values, with localized anomalies likely reflecting geological heterogeneities. The strong correlation between high RHP values and increased heat flow in the Western Belt suggests that enriched radioactive elements play a key role in geothermal activity. These findings have significant implications for geothermal energy potential in Malaysia, particularly in regions with high heat flow and active hot springs, which may serve as prime targets for geothermal exploration and development.

Structural geology plays a pivotal role in governing the spatial distribution of RHP across diverse terrains. A combination of factors—including tectonic configurations, granite classifications, and the age of rock formations—contributes to variations in RHP [24]. The geological structure of Peninsular Malaysia is primarily defined by two major tectonic units: the Western Belt, which is part of the Sibumasu Block, and the Eastern Belt, which belongs to the East Malaya Block [31, 34]. This tectonic division is reflected in the distinct characteristics of the granitic provinces and their associated RHP patterns. High heat-producing granites, defined by RHP values exceeding 8 μW/m³, are frequently associated with tectonic environments that facilitate the concentration of heat-producing elements [87]. As evident in Figure 11(A) (RHP map), the most striking feature is the pronounced concentration of high RHP values along the western belt of the peninsula, corresponding to the Western Granitoid Province. This observation underscores how the granitic provinces of Peninsular Malaysia display significant variations in RHP, shaped by their complex geological histories, tectonic environments, and mineralogical compositions.

The spatial distribution of RHP and its constituent radioactive elements (U, Th, and K) exhibits complex patterns across Peninsular Malaysia in Figure 11. The distribution of total RHP shows a pronounced west-east dichotomy, with significantly elevated values (averaging approximately 6.31 μW/m³) concentrated in the western belt (Figure 11(A)). U distribution exhibits a strong positive correlation with total RHP, particularly pronounced in the western belt (Figure 11(B)). This observation is quantitatively substantiated and confirmed by the correlation analysis presented in Figure 4(A), which demonstrates the highest correlation coefficient between RHP and U concentrations. Th distributions reveal moderate concentrations within the western belt (Figure 11(C)), with Graph 1b confirming this secondary influence through a moderate positive correlation between RHP and Th values. K distribution patterns display notably diminished values in this region (Figure 11(D)), consistent with the weakest correlation coefficient observed in Graph 1 between RHP and K concentrations, further validating the subordinate role of K in controlling RHP variability in the study area. This elemental fractionation, with high U, moderate Th, and low K in the Western Belt, likely reflects the transitional I-S type nature of the Western Range Granite and its complex geological history, including significant hydrothermal alteration. In contrast, the Eastern Belt granites show lower RHP values, consistent with their predominantly I-type nature and different tectonic settings.

The Western Belt is distinguished by transitional I- and S-type granites, characterized by high initial Sr⁸⁷/Sr⁸⁶ ratios (>0.710) and negative εNd values (−6, −10) [37, 40]. These granites, derived from both igneous and sedimentary sources, contain higher concentrations of radiogenic elements such as potassium (K), rubidium (Rb), and lead (Pb), while exhibiting lower strontium (Sr) levels and depleted light rare earth elements. The presence of muscovite and biotite, enriched in U and Th, significantly enhances their RHP, leading to average values of approximately 6.31 μW/m³, which are notably higher than those observed in the central and eastern regions. The elevated RHP in the Western Belt results from subduction and collision processes involving the Sibumasu and East Malaya blocks [35]. This strong correlation between high RHP values and geothermal manifestations is evident in the alignment of hot springs along the western coast, as illustrated in the RHP and hot spring distribution maps (figures 11(A) and 12). Additionally, the transitional I-S characteristics of these relatively younger granites, combined with age-related variations across the belt, influence geothermal gradients and surface heat flux intensity in these regions. In contrast, the Eastern Belt is dominated by I-type granites, which formed in a precollisional arc setting [88]. These granites exhibit lower RHP values due to their metaluminous composition, characterized by biotite and hornblende as the primary mafic minerals. Unlike the Western Belt granites, they lack peraluminous and peralkaline minerals and contain moderate levels of aluminum oxide (Al₂O₃) and high sodium oxide (Na₂O). Additionally, their composition includes lower concentrations of U and Th, the primary contributors to RHP, which further explains the reduced RHP levels. The central and eastern regions of the peninsula, encompassing both the Central Granitoid Province (Upper Triassic to Lower Jurassic) and the Eastern Belt Province (Permian to Triassic) [33, 34], show a noticeable decline in RHP, as illustrated in Figure 11 . This trend aligns with the expected exponential decrease in RHP with increasing geological age, particularly in I-type granites [24, 76, 89].

Mineralogical factors further influence the distribution of RHP across the granites of Peninsular Malaysia. The presence of U, Th, and K in granite rocks is largely due to radioactive accessory minerals such as zircon, monazite, and apatite, which host substantial amounts of Th and U. The distribution and abundance of these minerals are influenced by factors such as source rock composition, degree of melting, magma characteristics, and hydrothermal activity [90, 91]. Extensive hydrothermal alteration in the granites introduces secondary minerals like chlorite and sericite, which increase the overall radiogenic element content [88].

In the Western Belt, granites are characterized by high biotite content, which is rich in U and Th, contributing to elevated RHP [13, 36]. In contrast, Eastern Belt granites predominantly feature hornblende, a mafic mineral typical of I-type granites, which is associated with lower RHP values [30]. Accessory minerals such as titanite, allanite, and rutile also play a crucial role in the RHP of granitoids [38, 92, 93]. These minerals, enriched in U and Th, are found in both amphibole-bearing granites and mafic microgranular enclaves, where they contribute substantially to RHP [94]. In the Western Belt, this enrichment complements the already high RHP associated with biotite and hydrothermal alteration. Additionally, muscovite, a secondary mineral, indirectly influences RHP by redistributing U and Th through feldspar alteration [95]. The varying abundance of these minerals—alongside muscovite, chlorite, and sericite—between the Eastern and Western Belts reflects differences in hydrothermal activity, which could further explain the observed RHP variations [37]. Consequently, the interplay between primary rock composition, accessory mineral content, and secondary mineralization collectively determines the radiogenic potential of the granitoids in Peninsular Malaysia.

Faults significantly impact RHP by acting as conduits for hydrothermal fluid circulation, which enhances U and Th mobility and concentration in granitoids [96]. Structural complexities, such as fault intersections and shear zones, often correlate with elevated RHP and geothermal anomalies in tectonically active regions [97]. As illustrated in Figure 12, RHP values range from low (1, 4.9 μW/m³) to extreme (>13.5 μW/m³), with a strong spatial correlation to major fault systems and their intersections. The Western Granite Belt, primarily composed of younger (210, 220 Ma) S-type granites, exhibits higher RHP values, averaging 6.31 μW/m³, compared to the older (230, 260 Ma) I-type granites of the Eastern Belt, which average 4.12 μW/m³. This disparity in heat production is largely attributed to differences in mineralogical and geochemical properties, particularly the radiogenic element content of each granite type. Fault systems and younger granite intrusions play a key role in redistributing U and Th, the primary contributors to RHP, with structural pathways such as the Bentong-Raub suture acting as conduits for hydrothermal fluid migration. The alignment of NW-SE trending magnetic faults with hot springs and intersecting minor faults further suggests that these structures facilitate U concentration and heat retention near S-type granitoid intrusions [6]. The influence of these fault systems and younger granite intrusions explains the localized enhancement of RHP in certain regions, reinforcing the critical role of structural complexity in geothermal activity.

Structural complexity significantly influences RHP distribution, particularly in the Western Belt, where RHP values systematically increase near major faults and their intersections (Figure 12). Statistical analysis of the dataset reveals that nonfaulted regions exhibit the lowest RHP values, averaging 3.2 ± 1.1 μW/m³ (range: 2.1–4.3 μW/m³), while single fault zones show elevated values, averaging 6.59 ± 1.2 μW/m³ (range: 5.28–8.03 μW/m³). The highest RHP values occur at fault intersections, particularly along major NW-SE and N-S trending faults, where values range from 8.2 to 10.5 μW/m³. These intersections enhance RHP by approximately 40% compared to single fault zones and 65% higher than in nonfaulted areas. The redistribution of U along fault-controlled zones further amplifies this effect, as low-magnetization areas intruded by younger granites suggest the presence of concealed geothermal and mineral-rich zones [98]. This pattern underscores the critical role of fault intersections in heat concentration and transport, particularly in geothermal systems.

Recent research indicates that the spatial distribution of hot springs is closely linked with fault structures, particularly along NW-SE and N-S trending faults [2-4, 99]. In the Western Belt, prevalent fault intersections combined with high RHP from S-type granites facilitate enhanced geothermal fluid migration, generating localized geothermal anomalies and elevating geothermal potential. In contrast, the Eastern Belt exhibits fewer hot springs and lower RHP values, likely due to older, less radiogenic granites, the masking influence of thick sedimentary covers, and potential limitations in water availability or fault permeability. These findings underscore that even in regions characterized by high RHP and pronounced fault structures, the absence of sufficient water or permeability constraints can inhibit hot spring formation, thereby emphasizing the necessity for an integrated geological and hydrological approach in geothermal exploration strategies.

Granite age further modulates RHP distribution across the region. The younger S-type granites in the Western Belt sustain higher heat production, due to their greater residual radioactive isotope content, while the older I-type granites in the Eastern Belt exhibit more presence of younger granite intrusions, particularly in structurally complex areas. This plays a pivotal role in local heat anomalies, as evidenced by the spatial relationship between RHP, fault zones, and hot spring occurrences. These findings reinforce the combined influence of lithology, fault activity, and geological age on regional heat production, further explaining why geothermal activity is more prominent in the Western Belt compared to the Eastern Belt.

Statistical analyses reveal a strong positive correlation between RHP and U (R² = 0.78) as well as Th (R² = 0.65), confirming that radiogenic element concentrations are the primary drivers of heat production in the region. Furthermore, the spatial association between high-RHP zones, fault intersections, and hot spring distributions, as illustrated in Figure 12, underscores the critical influence of structural complexity and lithological characteristics on heat distribution. The consistent alignment of high-RHP areas with geothermal features, such as hot springs, further reinforces the substantial role of radiogenic heat in the regional geothermal system. These findings have significant implications for geothermal resource exploration, particularly within the Western Belt, where the presence of younger granites (210, 220 Ma), a dense fault network, and systematically clustered hot springs collectively indicate high geothermal potential. The most prospective exploration targets are concentrated along major NW-SE and N-S trending fault structures, where elevated RHP values and intensified geothermal fluid activity are observed. In contrast, while the Eastern Belt exhibits comparatively lower radiogenic heat output due to the presence of older granitoids (230, 260 Ma), it retains localized geothermal potential, particularly in proximity to fault intersections where structural controls may enhance heat accumulation and fluid circulation.

West Malaysia exhibits high thermal flow, with granitoid rocks serving as a major heat source for geothermal energy. This study analyzes the RHP of 139 granitic samples from three major granite belts, revealing RHP values from 1.5 to 17.83 μW/m³, with an average of 5.3 μW/m³—higher than typical crustal levels, indicating an enrichment of radioactive elements. Notably, 47% of the specimens display RHP values between 5 and 9 μW/m³, indicating consistently elevated RHP levels across many samples. Although extreme values (reaching 17.83 μW/m³ and dipping to 1.5 μW/m³) are observable, they signify localized discrepancies rather than reflecting the general trend. Granites associated with thermal springs have a higher average RHP (6.65 μW/m³) compared to those without springs (3.88 μW/m³), suggesting a strong correlation between RHP and geothermal activity. The Western Belt shows the highest average RHP (6.31 μW/m³), aligning with the distribution of thermal springs. U is the main driver of RHP variability, especially in the Western Belt, with Th as a secondary contributor.

The spatial distribution of RHP reflects Peninsular Malaysia’s complex tectonic evolution, with younger, more radioactive granites in the west likely tied to recent subduction and collision events. Minerals such as biotite, titanite, allanite, and rutile, rich in U, Th, and K, contribute to the elevated RHP in the Western Belt. Fault systems and younger granitoid intrusions further redistribute U, increasing RHP in localized areas. This analysis reveals the geothermal potential existing in West Malaysia, notably in the Western Belt, while reinforcing the urgent need for systematic exploration in the vicinity of fault zones in conjunction with detailed geological and geochemical studies to pinpoint viable geothermal sites.

To augment our understanding and promote geothermal advancements in the region, forthcoming studies should emphasize the enhancement of essential knowledge and empirical evaluations. These initiatives ought to encompass the execution of borehole temperature logs, the conduction of thermophysical parameter evaluations, the more precise determination of heat flow, and the thorough examination of the deep thermal regime. Furthermore, the amalgamation of these RHP data with supplementary geophysical and geological datasets will be imperative for the refinement of geothermal resource assessments and the direction of focused exploration efforts in West Malaysia. This holistic methodology will significantly improve our capacity to effectively utilize the considerable geothermal potential present within the region.

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

The authors declare that they have no conflicts of interest that could have appeared to influence the work reported in this article.

This study was financially supported by the Fundamental Research Grant Scheme (FRGS) [FRGS/1/2022/STG08/UKM/02/2] under the project titled Characterization of Geothermal System in Malaysia Using Geosciences Techniques for Sustainable Hydrothermal Cycle for Green Renewable Energy.

Supplementary data associated with this article (including detailed geochemical data tables and additional figures) can be found in the online version. All supplementary materials are available upon request from the corresponding author.