Material design of novel TiNbTaHfMo high-entropy alloys for biomedical implants: Exploring an industry-adaptable route via FAST/SPS

Material design of novel TiNbTaHfMo high-entropy alloys for biomedical implants: Exploring an industry-adaptable route via FAST/SPS Ricardo Ch´ avez-V´ asconez a,b , Cristina Ar´ evalo b , Sergio Sauceda b,c , Jeremi Leiva a , Angelo O˜ nate c , Eva M. P´ erez-Soriano b , Juan G. Lozano b , Yadir Torres b , Sheila Lascano a,* a Departamento de Ingeniería Mec´ anica, Universidad T´ ecnica Federico Santa María, Avenida Vicu˜ na Mackena 3939, Santiago, 8940572, Chile b Departamento de Ingeniería y Ciencia de los Materiales y del Transporte, Escuela Polit´ ecnica Superior, Universidad de Sevilla, Calle Virgen de ´ Africa 7, Sevilla, 41011, Spain c Departamento de Ingeniería de Materiales, Universidad de Concepci´ on, Edmundo Larenas 314, Concepci´ on, 4070409, Chile ARTICLE INFO Handling editor: SN Monteiro Keywords: Bio-high entropy alloys CALPHAD thermodynamic modeling Machine learning Materials characterization Powder metallurgy Spark plasma sintering ABSTRACT Novel non-equiatomic Ti–Nb–Ta-Hf-Mo alloys were designed using β-Ti and high-entropy alloy formulation strategies to develop low-modulus materials for load-bearing biomedical implants. Ti 40-x Nb 25 Ta 25 Hf 10 Mo x (x = 0, 5, 10 at.%) alloys were designed by combining the d-electron method for β-Ti alloys with conventional HEA design parameters, aiming to develop low-modulus materials for load-bearing biomedical implants. Compositions were optimized through CALPHAD thermodynamic modeling and validated using a random forest machine learning approach, with predictions matching phase transformations detected during sintering. Alloys were fabricated via elemental powder blending and spark plasma sintering (FAST/SPS) under varied temperatures and dwell times, achieving densification from ~90 % at 1250 ◦C/5 min to 98 % at 1350 ◦C or 10 min. Higher Mo content promoted and stabilized body-centered cubic (BCC) structures even at lower temperatures or shorter times. Mechanical testing confirmed Young’s moduli of 16–74 GPa, tunable through densification control to balance strength and mitigate stress shielding. Despite a heterogeneous microstructure, the mechanical performance was comparable to alloys produced by longer, costlier routes. This work demonstrates FAST/SPS from elemental powders as a rapid, scalable, and industrially attractive method for producing biomedical HEAs. 1. Introduction A high-entropy alloy (HEA) is an innovative concept in materials science research that is receiving significant attention across various industrial fields. First introduced by Yeh et al. [1] and Cantor et al. [2] in 2004, this strategy dramatically expands the number of alloy systems that can achieve desirable properties such as high strength, enhanced ductility, and superior fracture toughness [3]. Unlike conventional alloys, which are typically based on a single principal element with minor additions of others, HEAs consist of multiple principal elements in significant atomic fractions [4]. To qualify as an HEA, the system must include at least five elements in equiatomic or near-equiatomic proportions (typically 5–35 at.%), thereby maximizing configurational entropy and promoting the formation of solid solution phases [1,2]. Non-equiatomic HEAs have also shown promising results in recent years [5]. The multi-element nature of HEAs induces changes in free energy, phase formation, and thermodynamic stability [6,7]. Collectively, these phenomena facilitate solid solution formation, reduce grain growth, and improve hardness [8,9]. High mixing entropy and lattice distortion create atomic-level disorder, lowering Gibbs free energy and enhancing thermodynamic stability [9–11]. Five thermodynamic parameters characterize the solid solution formation in HEAS: configurational entropy (ΔSconf ), mixing enthalpy (ΔHmix), the combined effect parameter (Ω), atomic size mismatch (δ), and valence electron concentration (VEC) [12–14]. For a solid solution with n constituents, where X i represents the molar fraction of the element i, the thermodynamic parameters are calculated with Equations (1)–(7) [14–17], where R, ΔHmix AB , T m , r are the gas constant, the mixing enthalpy of binary system of i and j elements at equiatomic composition, * Corresponding author. E-mail address: [email protected] (S. Lascano). Contents lists available at ScienceDirect Journal of Materials Research and Technology journal homepage: www.elsevier.com/locate/jmrt https://doi.org/10.1016/j.jmrt.2025.09.004 Received 13 July 2025; Received in revised form 16 August 2025; Accepted 1 September 2025 Journal of Materials Research and Technology 38 (2025) 5094–5115 Available online 2 September 2025 2238-7854/© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). melting temperature, and atomic radius, respectively. ΔSconf = − R∑ n i=1 Xiln(Xi)(1) ΔHmix =∑ n i=1 i∕=j 4ΔHmix AB XiXj(2) Ω=TmΔSmix |ΔHmix|(3) Tm=∑ n i=1 Xi(Tm)i(4) δ= ∑ n i=1 Xi(1−ri r)2 √(5) r=∑ n i=1 Xiri(6) VEC =∑ n i=1 Xi(VEC)i(7) Recommended criteria to form a BCC single-phase solid solution in HEAs, includes [12,18]: ΔSconf ≥1.5R; −11.6≤ΔHmix ≤3.2kJ/mol; a reduced atomic size mismatch (δ≤6.6 %); VEC ≤6.87; and a Ω>1.1 when δ<3.6 % or Ω>10.0 for any δ. In addition, the CALPHAD (CALculation of PHAse Diagrams) approach predicts phase stability under a wide variety of processing conditions [19,20]. Machine learning models increasingly integrated with CALPHAD to enhance its predictive accuracy, and reduce experimental costs [21–24]. HEAs are being explored for use in aerospace, high-speed cutting tools, nuclear applications, hydrogen storage, and biomedical devices [9,25,26]. For biomedical applications, materials must combine biocompatibility with mechanical compatibility to minimize stress shielding at the bone-implant interface [27–30]. This phenomenon occurs due to the difference in Young’s modulus between the implant and the cortical bone (~30 GPa), and compromises the reliability of implants by promoting bone resorption and possible fracture of host tissue risking appropriate implant performance [31,32]. Conventional biomaterials, such as Ti and Ti6Al4V are the most commonly used for implantation devices due to their excellent corrosion resistance and biocompatibility [4]. However, their high Young’s modulus (~110 GPa), poor wear resistance, and potential toxicity from Al and V ion release are limitations [33–37]. To address these challenges, research has focused on developing titanium-based alloys containing non-toxic elements and exhibiting mechanical properties closer to those of bone [38]. The d-electron concept guides the design of β-Ti alloys with lower Young’s modulus values for reducing the stress shielding effect. The d-electron concept helps to screening the possible elements used for biomedical applications [39]. Some reviews [37,38,40] have highlighted that alloying with elements such as Nb, Ta, and Hf enhances biocompatibility and promotes a body-centered cubic (BCC) microstructure with high strength and good ductility. Ti and Hf, common in refractory HEAs, typically form BCC or HCP phases, and when combined with strong BCC stabilizers like Nb, can yield a single-phase BCC structure [41]. Following this approach, Lilensten et al. [42] developed a metastable Ti-rich HEA (Ti 35 –Zr 27.5 -Hf 27.5 -Nb 5 -Ta 5 ), demonstrating that Ti alloys design principles can be successfully applied to HEAs, improving phase prediction accuracy during its fabrication. Most HEAs are synthesized via melting techniques, which require repeated melting and remelting for homogeneity [43–47]. Powder metallurgy, including mechanical alloying and conventional sintering, often results in high porosity [48–51]. Advanced consolidation techniques, such as hot pressing, hot isostatic pressing, and FAST/SPS, achieve higher densification with shorter processing times [52–55]. In this sense, FAST/SPS is particularly attractive due to rapid heating, short sintering times, near-net-shape capability, and reduced temperatures, minimizing defects and grain growth [56–62]. In this study, novel non-equiatomic Ti–Nb–Ta-Hf-Mo (TNTH-Mo) HEAs were systematically designed by integrating titanium alloys and HEAs design principles. Designs were validated via CALPHAD and machine learning techniques, with the objective of developing materials appropriate for bone replacement applications. The alloys were synthesized by FAST/SPS using elemental powder blends to evaluate this cost-effective and scalable manufacturing route. The influence of Mo content, sintering temperature, and sintering dwell time on the microstructural evolution and mechanical performance was thoroughly examined. 2. Materials and methods Fig. 1 presents the experimental workflow. Ti–Nb–Ta-Hf-Mo alloys with low Young’s modulus were designed to reduce stress shielding, combining β-Ti and HEA strategies and validated via CALPHAD and machine learning. Three compositions (0, 5, 10 at.% Mo) were synthesized via powder metallurgy, with elemental powders cold-compacted at 650 MPa and sintered by FAST/SPS at 1250 ◦C or 1350 ◦C for 5 or 10 min. The resulting samples were characterized for their physical, microstructural, and micromechanical properties benchmarked against other candidate materials proposed for biomedical applications. 2.1. Alloy design Titanium and its alloys are widely used as metallic biomaterials. In this study, a β-phase Ti–Nb–Ta-Hf-Mo alloy with a body-centered cubic (BCC) structure was designed to reduce the elastic modulus and mitigate stress shielding. Alloy design was guided by the d-electron theory proposed by Morinaga et al. [39], which relies on the electronic parameters of the average bond order (Bo) and the average energy level of the d orbital (Md), as it has proven useful for predicting the resulting phases in a review [38]. The design target was an elastic modulus in the range of 60–70 GPa. Therefore, the alloying elements Ta, Nb, Hf, and Mo were selected based on their biocompatibility, β-phase stabilization, and high electronic parameter values of Bo and Md [63]. The electronic parameters, Bo and Md were calculated from the atomic fractions of Ti, Nb, Ta, Hf and Mo: Bo=2.790Ti +3.099Nb +3.144Ta +3.110Hf +3.063Mo (8) Md=2.447Ti +2.424Nb +2.531Ta +2.975Hf +1.961Mo (9) The coefficients accompanying each element correspond to their respective electronic properties, which can be found in Table 1. Due to the reported trend of decreasing elastic modulus when both electronic parameters are increased [38], and according to Eq. (8) and Eq. (9), the desirable atomic composition for the alloy should maximize the following function, Eq. (10): f(Ti,Nb,Ta,Hf,Mo) = Bo(Ti,Nb,Ta,Hf,Mo) + Md(Ti,Nb,Ta,Hf,Mo) =5.237Ti +5.523Nb +5.675Ta +6.085Hf +5.024Mo (10) Fig. 2 highlights the estimated exploration region within the Ti phase diagram to achieve the targeted elastic modulus. The boundaries of this region define the constraints for maximizing the function given by equation (10), which align with the five equations present in the diagram. Furthermore, to maximize the proposed expression, physical R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5095 constraints must be considered, such as ensuring that the quantity of all elements remains between 0 and 100 %, with their total summing to 100 %. Eqs. (11)–(13) are also considered as additional constraints for the optimization problem. Expression (11) specifies that Ti is the predominant element, followed by Nb and Ta. It was determined that the sum of Nb and Ta should not exceed 50 %, as indicated by expression (12), due to their heavier nature compared to Ti. Finally, expression (13) limits the content of Hf and Mo to 10 %, since Hf is a neutral element (does not stabilize the β phase), is costly, and heavy, but has high Bo and Md values; whereas Mo is the strongest β-phase stabilizer, and a higher concentration of stabilizing elements is unnecessary to achieve the desired BCC microstructure. The function described in Eq. (10) was maximized using MATLAB® (MathWorks Inc., USA) and its Optimization Toolbox, considering the mentioned constraints. Following the optimization, the Mo content was varied to study three alloys, given its role as the strongest β-phase stabilizer. Ta ≤Nb ≤Ti ≤0.7 (11) Ta +Nb ≤0.5 (12) Hf ≤0.1≥Mo (13) To further reinforce the alloy selection, additional thermodynamic parameters relevant to HEAs: configurational entropy (ΔSconf ), mixing enthalpy (ΔHmix), atomic size mismatch (δ), valence electron concentration (VEC), and combined effects (Ω), were calculated using Eqs. (1)– Fig. 1. Scheme of experimental design carried out in this research. Table 1 Physical properties of the pure elements used [63,64]. Element Crystalline structure Bo Md VEC R Tm [-] [eV] [-] [Å] [K] Ti HCP 2.790 2.447 4 1.462 1941 Nb BCC 3.099 2.424 5 1.430 2750 Ta BCC 3.144 2.531 5 1.429 3290 Hf HCP 3.110 2.975 4 1.578 2506 Mo BCC 3.063 1.961 6 1.363 2896 Fig. 2. Exploration region in Ti phase diagram for alloy design. Table 2 Calculated mixing enthalpies for atomic pairs in kJ/mol [65]. Element Ti Nb Ta Hf Mo Ti –    Nb 2–   Ta 1 0 –  Hf 0 4 3 – Mo −4−6−5−4– R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5096 (7). Required elemental properties are provided in Table 1, while Table 2 lists binary mixing enthalpies used in the ΔHmix calculation for all possible combinations. To assess thermodynamic stability of multicomponent alloys, CALPHAD calculations were performed using Thermo-Calc® (Thermo-Calc Software, Sweden) with the TCHEA6 database to analyze phase equilibrium. The results from the CALPHAD calculations were complemented by phase predictions using a machine learning approach based on an adjusted VEC criterion proposed by O˜ nate et al. [66,67]. The initial database was expanded to include 2591 alloys, compared to the previous database used for HEA predictions, which had 2434 alloys in an author’s previous work [66]. For this work, the database was further expanded to include 72 multicomponent alloys with HCP structure and 85 alloys with BCC + HCP structure. The prediction model used is Random Forest, with 80 % of the data used for training, and the remaining 20 % for testing, with a 10-fold random cross-validation scheme. Classification metrics were evaluated in terms of accuracy, precision, F1-score, and ROC AUC hyperparameter optimization was performed using a grid search with 8fold cross-validation, focusing on accuracy. The number of trees in the forest was tuned by evaluating values between 100 and 500. The optimal depth was configured with a minimum depth of 10 and increments of 20 levels, allowing the model to capture complex patterns. The model achieved an accuracy of 75 %, a precision of 76 %, an F1score of 73 %, and a ROAC AUC of 96 %. This process helps adjust the composition and appropriately select the added elements to achieve a metastable BCC structured solid solution in the high entropy alloy space, suitable for fabrication using the FAST/SPS technique. Exploratory data analysis (EDA) was conducted using thermodynamic and physical descriptors governed by the Hume-Rothery rules to understand phase stability trends, particularly for the HCP phase, as outlined by O˜ nate et al. [68]. 2.2. Powders characterization Elemental powders of Ti grade 4, Nb, Ta, Hf, and Mo (see Table 3) were characterized using laser diffraction analysis (Analysette 22, Fritsch GmbH, Germany) for particle size distribution, and scanning electron microscopy, SEM (Quattro S SEM, Thermo Fisher Scientific, USA) for morphological evaluation. Subsequently, the powders were mixed according to the three compositions established from the results obtained in the previous section. The mixing was performed using a TURBULA® T2F mixer (WAB, Switzerland) for 40 min to ensure homogeneity [69]. To determine the crystalline phases changes occurring during sintering, microstructural characterization was conducted using the indirect method of X-ray diffraction (XRD) on the powder mixtures. XRD analyses were carried out with a PANalytical X’Pert Pro diffractometer equipped with a θ/θ goniometer, using Cu K α radiation (40 kV, 40 mA), a secondary Kβ filter, and an X’Celerator detector. The diffraction angle (2θ) scanning range for obtaining the diffraction patterns of the powder mixtures was from 20◦to 90◦in step scan mode, with a step size of 0.017◦and a counting time of 400 s/step. With the metallic powder mixtures prepared and characterized, the consolidation of the study samples proceeded. 2.3. Sintering by FAST/SPS The fabrication process involved cold compaction followed by FAST/ SPS sintering. Powder blends were placed in a 20 mm diameter hardened steel die and compacted using a manual press MP24A (Across International, USA) at 650 MPa for 2 min. These conditions were selected based on the powders’ compressibility curves, to produce discs of 20 mm diameter and 5 mm thickness. After compaction, the samples’ dimensions and masses were recorded to evaluate densification and dimensional changes during sintering. Sintering was performed in a FAST/SPS KCE® FCT HP D-10 (FCT Systeme GmbH, Germany) using graphite dies and punches of 20 mm diameter under a high-purity argon atmosphere (99.95 %) and a constant uniaxial pressure of 6.3 MPa. The thermal profile consisted of an initial heating to 900 ◦C at 150 K/min, followed by a second ramp to either 1250 ◦C or 1350 ◦C at 50 K/min, held for 5 or 10 min, and then cooled at approximately 350 K/min (Fig. 3). Once the samples were consolidated, their characterization was performed to analyze their physical, microstructural, and micromechanical properties. 2.4. Physical properties and microstructural characterization Dimensional changes (diameter and thickness) between green and sintered states were measured using a Vernier caliper, and densities were calculated from sample dimensions and mass. Archimedes’ method with distilled water impregnation (ASTM B962) [70] was also employed to estimate the density and determine the total (P T ) and interconnected porosity (P i ). Three measurements per sample were performed. Samples were metallographically prepared following ASTM E3 [71]: resin mounting, grinding with SiC abrasive papers (grit sizes 400, 600, 1000, 2400, and 4000), and final polishing with non-crystallizing colloidal silica, MasterMet™ 2 (Buehler, USA). Residual porosity was quantified via image analysis of optical micrographs (Nikon Eclipse MA100 N, Nikon Corporation, Japan). using Image Pro-Plus® software (Media Cybernetics, USA), reporting total porosity (P T ), equivalent pore diameter (D eq ), and shape factor (Ff) as mean ±standard error. ANOVA and a Tukey test (using Statgraphics® Centurion software, Statgraphics Technologies Inc., USA) were conducted to evaluate the influence of composition, temperature, and sintering time on the porosity (p <0.05). Since the samples were made from an elemental blend of metal powders, the elemental was studied using SEM FEI Teneo (FEI, Netherlands) equipped with an energy-dispersive X-ray spectroscopy (EDX). To evaluate potential changes in the crystalline structure during Table 3 Characteristics of starting powders. Element Ti Nb Ta Hf Mo Supplier Alfa Aesar a AEM b AEM b AEM b AEM b Purity [%] 99.5 99.9 99.9 99.9 99.9 Particle size Mesh - 325 14–45 μ m 14–45 μ m Mesh - 325 14–45 μ m Morphology Irregular Spherical Spherical Irregular Spherical a Alfa Aesar (Thermo Fisher Scientific, USA). b Advanced Engineering Materials (AEM, China). Fig. 3. Sintering cycles for studied samples consolidation. R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5097 sintering, punch displacement curves during the sintering cycle were analyzed [72]. This information is complemented by XRD of the sintered samples, conducted under the same conditions as those used for the initial powder blends. Finally, samples exhibiting the best microstructural characteristics according to XRD results were further analyzed by using transmission electron microscopy (TEM) (FEI Talos F200S, Netherlands) at 200 kV. Lamellae were prepared using a focused ion beam (FIB) – SEM (Zeiss Auriga, Germany), employing a Ga ion beam at (30 kV, 600-50 pA) to achieve electron transparency. The crystalline structures obtained were compared with computational modeling predictions. The microstructural characteristics of the samples can be correlated with the resulting mechanical properties, which are characterized subsequently. 2.5. Micromechanical properties characterization Micromechanical characterization of the samples was performed using a combination of microhardness, instrumented microindentation, and surface roughness measurements. Vickers microhardness tests were conducted following ASTM E384 [73], using an HMV-G device (Shimadzu, Japan) applying a load of 98 mN for 10 s, performing at least ten measurements per sample. To assess mechanical behavior across different regions of the material, instrumented microindentation tests were conducted using a Microtest MTR3/50-50/NI device (Microtest S.A., Spain) with a Vickers indenter. Load-displacement curves (P-h curves) were obtained by applying a 10 N load at 10 N/min for 10 s with at least ten measurements per sample. The elastic modulus and elastic recovery were calculated from the P-h curves using the Oliver and Pharr method [74]. Surface roughness was measured with the same device using a 200 μ m Rockwell C diamond indenter under a 0.5 N load at 0.5 N/min over an 8 mm path. Roughness parameters including arithmetic mean roughness (Ra), maximum profile depth (Ry), and mean amplitude (Rz) were determined. 3. Results and discussion The main results and the subsequent discussion obtained from this research are presented following the same order as the exhibit in the methodology. 3.1. Alloy design As a result of the mathematical optimization of expression (10), the composition presented in Table 4 was obtained. This table also includes the three compositions selected for fabrication in this study to determine the stabilizing effect of Mo, and the composition of alloys of similar systems reported to be suitable for bone replacement applications in literature. For ease of nomenclature, the compositions are named TNTH, followed by the percentage of Mo added. Table 5 presents the thermodynamic stability parameters corresponding to each alloy proposed and for literature alloys. The Bo and Md parameters have values that place the three proposed compositions within the sector corresponding to the β phase on the phase composition map as well as for all the cited alloys in this work, except for Ti6Al4V alloy that correspond to an α +β alloy, as can be seen in Fig. 4. Regarding the thermodynamic parameters for phase stability in highentropy alloys, the following criteria are considered: For an alloy to be considered high entropy, it requires 11 ≤ΔSconf ≤16.5J/(mol K)[75]; for a solid solution to be formed, a δ≤6.6 % [76] must be achieved; a formed solid solution will be stable if −11.6≤ΔHmix ≤3.2kJ/mol [18]; a BCC structure will be formed if VEC <6.87 [75]; if Ω>1.1 and δ<3.6 %, only solid solutions will be formed; if 1.1<Ω<10.0 and 3.6<δ<6.6 %, both solid solutions and intermetallics will be formed; if Ω>10.0, only solid solutions will be formed [77]. Based on these criteria, it is determined that the TNTH composition corresponds to a medium-entropy alloy, as it does not meet the required number of constituent elements or configuration entropy. In contrast, the TNTH-5Mo and TNTH-10Mo compositions satisfactorily meet the requirements to be considered high-entropy alloys, and their other thermodynamic parameters are consistent with the formation of stable solid solutions without the presence of intermetallic compounds. TNTH and TNTH-xMo alloys, as well as all cited alloys from the literature with more than 3 components fall under the concept of complex concentrated alloys (CCAs) due to their multicomponent nature, with Ti as the main element, and the significant lattice distortion effects they induce to improve their mechanical compatibility with bone [78]. Fig. 5 illustrates the phase diagram, derived using CALPHAD in Thermo-Calc®, for the high-entropy alloy Ti (40-x) Nb 25 Ta 25 Hf 10 Mo x . This diagram reveals that increasing the Mo content broadens the stability range of the BCC phase, progressively lowering the transformation temperature from BCC to BCC +HCP, which is presented as the green line. This adjustment allows for an enhanced control over the phase Table 4 Composition of resulting in optimization, and compositions selected for the study and alloys of similar systems reported in literature for comparison. Alloy Ti Nb Ta Hf Mo Zr Reference [% at.] [% at.] [% at.] [% at.] [% at.] [% at.] Mathematical optimization 36.9 25.0 25.0 10.0 3.1 - This study TNTH 40.0 25.0 25.0 10.0 0.0 –This study TNTH-5Mo 35.0 25.0 25.0 10.0 5.0 –This study TNTH-10Mo 30.0 25.0 25.0 10.0 10.0 –This study Ti–33Nb–33Zr 49.0 25.3 0.0 0.0 0.0 25.7 [79] Ti–25Nb–25Zr–25Ta 43.3 22.4 11.5 0.0 0.0 22.8 [79] Ti–20Nb–20Zr–20Ta–20Mo 35.7 18.4 9.4 0.0 17.8 18.7 [79] TiZrNbTaMo 20.0 20.0 20.0 0.0 20.0 20.0 [80] TiZrNbTaMo 17.6 21.9 21.5 0.0 21.9 17.1 [81] TiZrNbTaHf 20.0 20.0 20.0 20.0 0.0 20.0 [4] Ti 37.5 Nb 12.5 Zr 25 Hf 12.5 Ta 12.5 37.5 12.5 12.5 12.5 0.0 25.0 [4] Ti 22.3 Zr 17.8 Nb 23.8 Mo 18.7 Ta 17.4 22.3 23.8 17.4 0.0 18.7 17.8 [82] Ti 20.4 Zr 15.2 Nb 21.7 Mo 22.2 Ta 20.5 20.4 21.7 20.5 0.0 22.2 15.2 [82] TaNbHfZrTi 19.7 18.9 19.7 20.5 0.0 21.2 [83] Ti 25 Zr 25 Hf 25 Nb 12.5 Ta 12.5 25.0 12.5 12.5 25.0 0.0 25.0 [84] Ti 27.78 Zr 27.78 Hf 27.78 Nb 8.33 Ta 8.33 27.8 8.3 8.3 27.8 0.0 27.8 [84] Ti 20 Ta 20 Nb 20 (ZrHf) 20 20.0 20.0 20.0 20.0 0.0 20.0 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 17.5 Mo 5 20.0 20.0 20.0 17.5 5.0 17.5 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 15 Mo 10 20.0 20.0 20.0 15.0 10.0 15.0 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 12.5 Mo 15 20.0 20.0 20.0 12.5 15.0 12.5 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 10 Mo 20 20.0 20.0 20.0 10.0 20.0 10.0 [64] R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5098 obtained according to the material processing route, resulting in greater retention of the BCC phase in compositions with higher Mo content when employing rapid cooling methods, such as the cooling rate during FAST/SPS synthesis (~350 K/min) or quenching heat treatments. Fig. 6 presents the phase mass fraction diagrams for the high-entropy alloy compositions TNTH and TNTH-10Mo, illustrating the amount of each phase formed according to the temperature reached by the system. Based on these results, it is likely that samples without Mo exhibit residual HCP phase content during the cooling stage due to its higher stability at elevated temperatures. However, the cooling rate after the sintering stage (~350 K/min), will limit the energy available for phase change due to the large amount of heat extracted from the thermodynamic system in a short time. Consequently, the presence of the HCP phase will also depend on the diffusion of species during the sintering stage due to the short cycle time. The phase prediction results obtained through machine learning using the random forest model are shown in Fig. 7. These results indicate an increase in the stabilization of the BCC phase with higher Mo content. However, in the TNTH-10Mo composition, a stable BCC phase across the entire temperature range is not achieved. This aligns with the CALPHAD simulation results, as depicted in the phase diagram and phase mass fraction diagram for the proposed high-entropy system in this study. An analytical analysis based on the Hume-Rothery phase stability rule determined that the valence electron concentration (VEC) criterion for BCC phase stability aligns with reports by other authors such as Ye et al. [16] and O˜ nate et al. [68]. However, valence electron concentration is not a standalone predictive parameter and must be combined with other parameters to enhance the accuracy of the predictions in Table 5 Thermodynamic stability parameters of the studied alloys and similar ones reported in literature for comparison. Composition B o M d ΔS conf ΔH mix δVEC T m ΩRef. [−] [eV] [J/(mol K)] [kJ/mol] [%] [−] [K] [−] TNTH 2.988 2.515 10.73 1.90 2.95 4.5 2537 14.3 This study TNTH-5Mo 3.001 2.491 11.98 0.84 3.28 4.6 2585 36.9 This study TNTH-10Mo 3.015 2.466 12.60 −0.14 3.55 4.7 2633 236.9 This study Ti6Al4V 2.749 2.396 4.30 0.90 0.80 5.1 1836 8.8 [4] Ti–33Nb–33Zr 2.944 2.566 8.70 2.03 4.54 4.3 2193 9.40 [79] Ti–25Nb–25Zr–25Ta 2.967 2.563 10.67 2.11 4.49 4.3 2320 11.8 [79] Ti–20Nb–20Zr–20Ta–20Mo 2.984 2.455 12.66 −1.52 5.19 4.6 2422 20.2 [79] TiZrNbTaMo 3.036 2.459 13.38 −1.76 5.46 4.8 2601 19.8 [80] TiZrNbTaMo 3.044 2.437 13.33 −2.11 5.28 4.9 2649 16.8 [81] TiZrNbTaHf 3.046 2.662 13.38 2.72 4.99 4.4 2523 12.4 [4] Ti 37.5 Nb 12.5 Zr 25 Hf 12.5 Ta 12.5 2.987 2.642 12.42 1.87 4.79 4.3 2328 15.4 [4] Ti 22.3 Zr 17.7 Nb 23.8 Mo 18.7 Ta 17.4 3.029 2.452 13.31 −1.56 5.21 4.8 2580 22.1 [82] Ti 20.4 Zr 15.2 Nb 21.7 Mo 22.1 Ta 20.5 3.035 2.425 13.31 −2.18 5.09 4.9 2634 16.1 [82] TaNbHfZrTi 3.046 2.671 13.38 2.70 5.02 4.4 2515 12.5 [83] Ti 25 Zr 25 Hf 25 Nb 12.5 Ta 12.5 3.027 2.708 12.97 2.12 4.86 4.3 2399 14.6 [84] Ti 27.78 Zr 27.78 Hf 27.78 Nb 8.33 Ta 8.33 3.016 2.734 12.32 1.57 4.67 4.2 2330 18.2 [84] Ti 20 Ta 20 Nb 20 (ZrHf) 20 3.046 2.662 13.38 2.72 4.99 4.4 2523 12.4 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 17.5 Mo 5 3.044 2.613 14.35 1.49 5.21 4.5 2552 24.6 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 15 Mo 10 3.042 2.563 14.68 0.36 5.31 4.6 2581 105.2 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 12.5 Mo 15 3.041 2.513 14.72 −0.67 5.30 4.7 2610 57.3 [64] Ti 20 Ta 20 Nb 20 (ZrHf) 10 Mo 20 3.039 2.464 14.53 −1.60 5.17 4.8 2639 24.0 [64] Fig. 4. Mapping of the proposed alloys in this study and β-Ti and HEAs reported in literature for bone replacement applications in the Ti phase diagram. R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5099 certain circumstances, such as overlap, as its effect may be negated by favoring other phases. Exploratory data analysis found that the HCP phase is stable when the atomic radius difference is less than 4.63 %, a difference found in the three proposed study alloys. Nonetheless, it was observed that increasing the Mo content raises the average atomic radius of the alloy, expanding the BCC phase stability range. This finding is consistent with the results obtained through CALPHAD and machine learning, demonstrating that the key parameters for predicting the BCC phase are, both together, the VEC parameter and atomic radius difference. 3.2. Powders characterization The SEM images and particle size distributions of the metal powders are shown in Fig. 8. Ti and Hf particles exhibit an irregular morphology, typical of the hydrogenation/dehydrogenation and selective chloride reduction routes, respectively, with particle sizes ranging from 2 to 100 μ m and averages of 40.6 μ m (Ti) and 29.9 μ m (Hf). In contrast, Nb, Ta, and Mo particles are spherical with smooth surfaces, resulting from gas atomization production, with size ranges of 10–100 μ m and average sizes of 41.4 μ m (Nb), 31.3 μ m (Ta), and 41.5 μ m (Mo). Irregular particles increase contact points and improve green-state fixation, while spherical particles offer higher apparent density but fewer contact points. Combining both morphologies can enhance consolidation, green strength, and final density [85]. However, since the particle size distribution is similar for all elements, it is likely that interstitial spaces between particles are not filled, as typically occurs when using powder mixtures with multimodal distributions [86,87]. Fig. 9 displays the diffraction patterns of the elemental powder mixtures. These diffraction patterns show the presence of peaks for all constituent elements of the material. The detected Ti and Hf peaks exhibit an HCP crystalline structure with space group P6 3 /mmc, while the other peaks correspond to a BCC crystalline structure with space group Im-3m. Some peaks tend to coalesce, showing a broader bandwidth. This is interpreted as an increased number of crystalline defects, suggesting that during the mixing stage to achieve powder homogenization, there was some reactivity between Nb and Hf powders and between Ti and Mo powders. This is possible because the free energy of the formed binary compounds is negative at room temperature, so the energy delivered to the system during agitation caused this reaction to occur. However, due to the constant separation of particles during agitation, it is practically impossible for the compound to form solely through agitation, although it is sufficient to be detected in the diffraction pattern of the metallic powder mixture. This slight reactivity Fig. 5. Phases diagram for Ti (40-x) Nb 25 Ta 25 Hf 10 Mo x HEAs. Fig. 6. Mass fraction diagrams for HEAs: (a) TNTH; (b) TNTH-10Mo. Fig. 7. Phases prediction by machine learning with random forest model. R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5100 at room temperature hints at the possible phases that may form during sintering. 3.3. Physical properties and microstructural characterization The dimensions, volume, geometric density, and shrinkage percentage of green and sintered samples are shown in Supplementary Table S1. A slight change in dimensions is noted, with an increase in Fig. 8. SEM images and particles size distribution of: (a) Ti; (b) Nb; (c) Ta; (d) Hf; (e) Mo. R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5101 diameter and a decrease in height, caused by the pressure applied during sintering. This pressure allows for the rearrangement of powder particles due to the clearance between the green sample and the graphite die. An increase in geometric density is observed, attributed to the sintering process where sintering necks form and porosities between powder particles tend to close. Fig. 10 depicts the percentage of shrinkage that occurred during the sintering stage, where the shrinkage values increase with sintering temperature and time, indicating better densification. However, samples sintered at 1350 ◦C for 10 min for TNTH-5Mo and TNTH-10Mo compositions show less shrinkage than those sintered at 1250 ◦C. This can be attributed to phase formation, as the theoretical density of the alloy is lower than the powder mixture density, compensating densification shrinkage with expansion from phase formation. This can be analyzed through the punch displacement vs. temperature curves during sintering, which provide information on phase formation and densification. Fig. 11 shows punch displacement vs. temperature curves during sintering in FAST/SPS. The displacement observed is relatively low (less than 0.5 mm), corresponding to additional densification, since the samples were compacted in green. Sharp slope changes at 900 ◦C correspond to changes in heating rate, with sintering cycles conducted at 150 K/min up to 900 ◦C and then at 50 K/min to the sintering temperature. Despite this, a slope change around 600 ◦C (inset in Fig. 11(a)) indicates the start of reactivity between different element powders, forming new phases, which is consistent with the mass fraction diagram presented in Fig. 6. A second slope change at 1050 ◦C suggests sufficient energy for sintering neck development and improved diffusion between powder particles, reducing sample height. Finally, at the sintering temperature, the sample height decreases, indicating densification during the temperature maintenance stage. The mentioned behavior is caused by different phenomena during heating, illustrated in Fig. 11(d). At low temperatures, the Gibbs’ free energy is not high enough to activate diffusion processes, but the temperature gradient causes the dilatation of the sample. When the temperature reaches a point where the Gibbs’ free energy activates the diffusion phenomena, there will be competition between the dilatation caused by the heating and the contraction due to necks formation by diffusion during sintering, causing a slope change, as the one found at 600 ◦C. At high temperatures, the diffusion phenomena have more energy to enhance the formation of sintering necks, which results in a contraction of the sample higher than the dilatation degree. Finally, once the sintering temperature has been reached, there is no temperature gradient, hence there is only contraction due to sintering necks formations, which is represented as the straight down line at the end of the curves. Comparing the three compositions, samples containing Mo (Fig. 11 (b) and (c)) show a greater slope change from 600 ◦C and above, which may indicate that at this temperature it reaches the energy necessary for the reactivity of Mo with other elements to form a phase. This aligns with CALPHAD simulation results (Fig. 6), where at 600 ◦C, the HCP phase ends, and the BCC phase fully forms, consistent with Mo powder reactivity observed in XRD patterns, indicating low-energy reactions. The microstructure of the fabricated samples is analyzed for further insights. Optical micrographs of sintered samples from TNTH and TNTH10Mo mixtures are shown in Fig. 12. Optical micrographs of sintered samples from TNTH-5Mo mixture are shown in Fig. S1. There can be seen residual porosity of the manufacturing process during sintering, showing a clear dependence on processing parameters: the porosity decreases with increasing sintering time and temperature, but increases with higher Mo content. The effects of higher temperature and longer sintering time are similar, as elevated temperatures enhance atomic mobility and increase the driving force for diffusion [88]. At lower temperatures, where the driving force is weaker, longer exposure to the current provides sufficient energy to obtain similar diffusion results, forming sintering necks, Fig. 9. XRD patterns of powder blends: TNTH (black), TNTH-5Mo (red), TNTH10Mo (blue). Fig. 10. Resulting contraction during sintering. R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5102 factors: (i) the formation of BCC phases, which have a lower Young’s modulus than the initial powder phases, and (ii) the increased porosity resulting from the higher sintering temperature required due to Mo’s elevated melting point. At higher temperatures and longer dwell times, densification improves, and the influence of the BCC phase becomes the dominant factor affecting the elastic modulus of the sintered alloys. This behavior is desirable to reduce the mismatch between Young’s moduli of biomaterials and natural bone to minimize the effect of the stress shielding effect in biomedical applications. Nonetheless, the TNTH sample sintered at 1250 ◦C for 10 min exhibits an estimated elastic modulus of 74 GPa, which is considerably higher than other samples. This behavior probably can be attributed to the presence of residual α ’’ phase, but also it has to been considered that instrumented micro-indentation tests (P-h curves) are static and localized tests (reduced indentation area, local phenomena), which may differ from macro behavior. In this context, this discrepancy could be associated with super-elastic deformation within the linear-elastic range of tested materials [102,103]. Furthermore, the micro-hardness and the local stiffness could be related to the localized microplasticity phenomena (stress concentration), indentation size effects (applied load, indenter tip type, etc.), as well as, the influence of the surface roughness and the oxide layer inherent in the sintering process. Finally, the sensitivity of the load cell and the linear variable differential transformer, etc., must also be considered. Higher sintering temperatures generally reduce porosity and increase elastic modulus; however, in this study, higher temperatures led to a lower elastic modulus despite reduced porosity. This is attributed to the formation of the BCC phase, which has a lower elastic modulus than the initial HCP phases. Across all synthesis conditions, using 1350 ◦C and 10 min of sintering achieves more stable elastic modulus values, approximately 45 GPa. Considering the inherent porosity from the manufacturing process, the elastic modulus of the material without porosity would be around 55–60 GPa, consistent with the design target from Eq. (10). Statistical analysis (ANOVA) hows that Mo content, temperature, and sintering time significantly affect Young’s modulus (p <0.05). Of the three variables, sintering time has the greatest effect on the elastic modulus behavior, primarily because short times do not form robust sintering necks, increasing porosity and significantly reducing the resulting elastic modulus. It is noteworthy that the achieved Young’s moduli for the proposed alloys are lower than the Young’s moduli of each constituent elements, where the stiffer material is Mo and the less stiff is Hf with elastic moduli of 329 and 78 GPa, respectively. In the literature HEAs have been reported from similar elemental systems such as Nb-Ta-Ti-Zr [105] or Ti-Zr-Nb-Ta-Mo [11], where the achieved elastic moduli were in the range of 115–155 GPa, regardless the processing route employed (arc melting or FAST/SPS). On the other hand, Yang et al. [84] developed Ti–Zr-Hf-Nb-Ta HEAs using arc melting with Fig. 18. Microhardness variation due to processing parameters in rich zones of: (a) Ti/Hf; (b) Nb; (c) Ta; (d) Mo. R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5109 Young’s moduli in the range of 56–79 GPa, achieving the decrease of the elastic modulus for the application of the proposed material for biomedical applications. Considering potential biomedical applications, the elastic moduli obtained in this study – in the range between 15 and 50 GPa – are suitable for bone tissue replacement bearing in mind that bone elastic modulus in comprised between 2 and 30 GPa, depending on whether it is trabecular or cortical bone [91,106]. Regarding hardness, it behaves similarly to the elastic modulus, decreasing with shorter synthesis times and increased Mo content due to inherent porosity. Similarly, increasing temperature decreases hardness values, as the formed BCC crystalline structure is softer than the initial HCP structure in Ti and Hf powders. The effect of synthesis time and temperature is more pronounced in this property, with a noticeable change in hardness when comparing samples sintered for 5 min, showing similar behavior with slight shifts due to porosity’s effect on mechanical properties. In contrast, comparing samples sintered for 10 min reveals a significant change in the curve slope, indicating substantial microstructural changes attributed to BCC phase formation. However, all data show large standard deviations, due to the lack of a homogeneous phase throughout the material volume as a consequence Fig. 19. P-h curves of samples produced from powders blend of: (a) TNTH; (b) TNTH-5Mo; (c) TNTH-10Mo. Table 8 Representative values of microindentation measurements. Composition Time Temperature Porosity Maximum penetration Absolute elastic recovery Relative elastic recovery [min] [◦C] [%] [ μ m] [ μ m] [%] TNTH 5 1250 9.2 ±0.7 22 ±3 6 ±1 28 ±4 1350 8.6 ±0.2 19 ±3 4 ±0 21 ±5 10 1250 8.8 ±0.8 15 ±3 3 ±0 18 ±7 1350 7.5 ±0.9 13 ±1 3 ±0 24 ±3 TNTH-5Mo 5 1250 10.1 ±0.3 22 ±2 4 ±0 16 ±3 1350 8.9 ±0.7 21 ±2 5 ±1 25 ±6 10 1250 10.1 ±0.2 16 ±1 3 ±0 16 ±2 1350 8.2 ±0.8 15 ±1 3 ±0 22 ±2 TNTH-10Mo 5 1250 12.1 ±0.8 26 ±2 5 ±1 19 ±2 1350 10.2 ±0.2 25 ±2 4 ±1 18 ±2 10 1250 11.2 ±0.8 17 ±1 3 ±0 16 ±2 1350 10.1 ±0.9 18 ±3 3 ±0 15 ±1 R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5110 of the short synthesis times, with contributions from phases with varying hardness levels (as shown in Fig. 17) and inherent manufacturing porosity. Fig. 21 shows the roughness profile obtained of a sample made from the TNTH-10Mo blend sintered at 1350 ◦C for 10 min. The roughness parameters obtained from roughness measurements are presented in Table 10. The R a values are in the range of 0.58–3.13 μ m, which correspond to smooth surfaces with the presence of porosity. Higher roughness values can be compared to the ones achieved by means of surface modifications such as grit blasting or acid etching [107]. In the literature there are studies [108,109] that have shown that osteoblastic cells attach, spread and proliferate more rapidly on smooth surfaces than on rough surfaces, while the cellular differentiation is enhanced by rough surfaces. On the other hand, R y and R z provide insights into the depth of the pores [91], where the measured values are below 6 μ m, being lower than the particles size from the samples were consolidated, which will not have an additional effect than the mentioned. Hence, based on the roughness values exhibited by the samples produced in this study, it can be stated that the samples could present an adequate cellular behavior at early stages for cellular attachment, spreading and Table 9 Mechanical properties of the produced samples, bone and similar alloys reported in literature for comparison. Composition Time Temp. Phases Elastic modulus Microhardness Ref. [min] [◦C] [GPa] [GPa] TNTH 5 1250 β + α ’’ 16 ±3 1.33 ±0.34 This study 1350 β29 ±4 1.46 ±0.64 This study 10 1250 β + α ’’ 74 ±5 2.38 ±0.34 This study 1350 β45 ±7 3.57 ±0.72 This study TNTH-5Mo 5 1250 β + α ’’ +β ′ 32 ±4 1.01 ±0.41 This study 1350 β +β ′ 20 ±5 1.32 ±0.53 This study 10 1250 β + α ’’ +β ′ 49 ±10 2.10 ±0.29 This study 1350 β +β ′ 42 ±5 2.75 ±0.52 This study TNTH-10Mo 5 1250 β +β ′ 15 ±4 0.79 ±0.21 This study 1350 β +β ′ 20 ±4 0.87 ±0.11 This study 10 1250 β +β ′ 42 ±5 1.96 ±0.34 This study 1350 β +β ′ 42 ±3 1.56 ±0.59 This study Cortical bone – – – 20 0.76 [104] Trabecular bone – – – 11 0.23 [104] 316L – – γ 196 2.44 [4] CoCrMo – – α + ε 223 4.21 [4] Ti6Al4V – – α +β128 3.32 [4] Ti–33Nb–33Zr – – β +β ′ 66 2.42 a [79] Ti–25Nb–25Zr–25Ta – – β +β ′ 73 3.17 a [79] Ti–20Nb–20Zr–20Ta–20Mo – – β +β ′ 88 4.44 a [79] TiZrNbTaMo – – β +β ′ 153 4.90 [80] TiZrNbTaMo – – β + α 113 4.99 a [81] TiZrNbTaHf – – β 113 3.14 [4] Ti 37.5 Nb 12.5 Zr 25 Hf 12.5 Ta 12.5 – – β 99 3.02 [4] Ti 22.3 Zr 17.7 Nb 23.8 Mo 18.7 Ta 17.4 – – β +β ′ 159 6.70 [82] Ti 20.4 Zr 15.2 Nb 21.7 Mo 22.1 Ta 20.5 – – β +β ′ 140 6.50 [82] TaNbHfZrTi – – β – 3.80 [83] Ti 25 Zr 25 Hf 25 Nb 12.5 Ta 12.5 – – β 68 2.90 [84] Ti 27.78 Zr 27.78 Hf 27.78 Nb 8.33 Ta 8.33 – – β 56 2.80 [84] Ti 20 Ta 20 Nb 20 (ZrHf) 20 – – β 140 4.66 a [64] Ti 20 Ta 20 Nb 20 (ZrHf) 17.5 Mo 5 – – β +β ′ 130 4.60 a [64] Ti 20 Ta 20 Nb 20 (ZrHf) 15 Mo 10 – – β +β ′ 121 4.19 a [64] Ti 20 Ta 20 Nb 20 (ZrHf) 12.5 Mo 15 – – β +β ′ 156 4.95 a [64] Ti 20 Ta 20 Nb 20 (ZrHf) 10 Mo 20 – – β +β ′ 154 5.46 a [64] a Obtained from HV values. Fig. 20. Effect of porosity on: (a) Young’s modulus; (b) Vickers microhardness. R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5111 proliferation, bearing in mind also the presence of biocompatible elements. Nonetheless, it is necessary to conduct further investigation to verify the proposed statement. 4. Conclusions Ti 40-x Nb 25 Ta 25 Hf 10 Mo x (x =0, 5, 10 at. %) alloys were designed by combining the d-electron method for β-Ti alloys with the conventional parameters for HEAs design and successfully fabricated via FAST/SPS from elemental mixed powders under different processing parameters. The effect of Mo content, sintering temperature and time on the microstructure and mechanical properties led to the following conclusions. •The phase formations of the designed alloy were predicted by means of CALPHAD and machine learning using the random forest algorithm. The phase diagram calculated using CALPHAD aligned with the phase transformations detected during sintering stage, demonstrating the effect of Mo content to form and stabilize the BCC crystalline structure when higher Mo contents were used, despite the short sintering time or low sintering temperature. •The densification degree of the samples via this processing route are acceptable, being lower when using the 1250 ◦C and 5 min with values around 90 %. An increase of 100 ◦C in the sintering temperature from 1250 ◦C to 1350 ◦C is equivalent to duplicate the dwell time up to 10 min in terms of the densification and interdiffusion of species achieved by the produced samples, irrespectively of the blend of powders used, reaching densification values up to 98 %. Hence, the sintering parameters could be raised in order to achieve a fully dense material, although it is probable that the formed phases are going to be the same based on the phase separation behavior reported in HEAs of similar systems. •Mechanical properties measurements confirmed the feasibility for biomedical of the produced samples, which exhibit Young’s moduli between 16 and 74 GPa, attributed mainly to the BCC structure. Even though, controlling the densification degree could tune the Young’s modulus to reach an adequate balance between sufficient strength and low stress shielding effect in bone replacement applications. •The use of FAST/SPS to produce HEAs from elemental powders blends is a cost-effective route to achieve results similar to the ones obtained by mechanical alloying or casting processes. Despite the FAST/SPS of elemental powder blends route exhibit a heterogeneous microstructure, the mechanical behavior at macroscale is similar to the ones found in materials which exhibit homogeneous microstructure and have considerably long and expensive processing routes. Hence, the proposed methodology developed in this work is attractive for its implementation in industrial environments. CRediT authorship contribution statement Ricardo Ch´ avez-V´ asconez: Conceptualization, Methodology, Investigation, Validation, Formal analysis and Writing – Original draft; Cristina Ar´ evalo: Methodology, Investigation, Formal analysis, Supervision, Writing – Review and editing, Resources, Funding acquisition; Sergio Sauceda-Martínez: Investigation, Formal analysis and Writing – Original draft; Jeremi Leiva: Data curation, Investigation; Angelo O˜ nate: Software, Investigation, Formal analysis, Writing – Original draft; Eva M. P´ erez-Soriano: Investigation, Formal analysis; Juan G. Lozano: Investigation, Formal analysis; Yadir Torres: Formal analysis, Resources, Funding acquisition, Writing – Review and editing; Sheila Lascano: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Visualization, Supervision, Funding acquisition and Project administration. Data availability The raw and processed data requested to replicate these results cannot be made available at this time, as they are also part of an inprogress research study. Funding sources This work was supported by the Agencia Nacional de Investigaci´ on y Desarrollo (ANID) of Chile government (FONDEQUIP EQM170156, Scholarship Program/DOCTORADO/2021–21211274 and Scholarship Program/DOCTORADO/2021–21210700), the Direcci´ on de Posgrados y Progamas of the Universidad T´ ecnica Federico Santa María through the Incentive Program for Scientific Initiation (PIIC) and Universidad de Fig. 21. Roughness profile of a TNTH-10Mo sample. Table 10 Roughness parameters obtained on the surface of sintered samples. Composition Time Temperature Ra Ry Rz [min] [◦C] [ μ m] [ μ m] [ μ m] TNTH 5 1250 3.13 4.37 5.79 1350 0.96 2.15 2.07 10 1250 0.58 1.20 0.85 1350 0.66 1.58 1.28 TNTH-5Mo 5 1250 1.92 3.28 3.64 1350 1.66 3.03 2.82 10 1250 2.32 3.09 3.52 1350 1.76 2.64 2.59 TNTH-10Mo 5 1250 1.56 2.86 2.71 1350 1.84 3.63 3.77 10 1250 2.59 3.78 3.88 1350 1.93 2.83 2.82 R. Ch´ avez-V´ asconez et al. Journal of Materials Research and Technology 38 (2025) 5094–5115 5112 Sevilla with Microscopy Services at CITIUS (VII PPIT-2023-I.5 Cristina Ar´ evalo Mora). 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. Acknowledgement The authors thank the laboratory technicians Jesús Pinto at Universidad de Sevilla (Spain), Claudio Aravena, Gabriel Cornejo at Universidad T´ ecnica Federico Santa María (Chile), M´ onica Uribe at Universidad de Concepci´ on (Chile) for their support carrying out the microstructure characterization and mechanical testing and Angelo O˜ nate to the VRID Initiation Project, of the Universidad de Concepci´ on (Chile) (VRID N◦2025001319INI). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.jmrt.2025.09.004. References [1] Yeh JW, Chen SK, Lin SJ, Gan JY, Chin TS, Shun TT, Tsau CH, Chang SY. Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes. Adv Eng Mater 2004;6:299–303. [2] Cantor B, Chang ITH, Knight P, Vincent AJB. Microstructural development in equiatomic multicomponent alloys. Mater Sci Eng, A 2004;375–377:213–8. [3] Couzini´ e J-P, Dirras G. 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