Manufacturing Letters最新文献

{"title":"Sample partitioning for milling stability and surface location error model uncertainty reduction","authors":"Tony Schmitz,&nbsp;Michael Gomez","doi":"10.1016/j.mfglet.2026.07.074","DOIUrl":"10.1016/j.mfglet.2026.07.074","url":null,"abstract":"<div><div>This paper describes uncertainty reduction in milling dynamics process modeling, including both stability and surface location error, using sample partitioning. In this approach, the model inputs are defined by distributions and samples are retained or rejected using stability test results. Stability maps are calculated using uncertain inputs, including modal parameters that represent the tool tip frequency response functions and cutting force model coefficients that relate the cutting force to the commanded chip area. After the uncertain inputs are partitioned by limited stability tests, the combined stability/surface location error map is predicted for final milling parameter selection. A numerical case study is provided to evaluate the approach. It is shown that 10000 initial samples were reduced to 224 samples after five tests. The maximum error between the input and output parameters was 3.8% and the minimum was -0.03%, providing initial validation of the approach.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 625-632"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrodynamic flexible spindle machining of teardrop-shaped metal additively manufactured channels","authors":"Jack Shanks,&nbsp;Patrick Chernjavsky,&nbsp;Rohit Dey,&nbsp;Yihao Zheng","doi":"10.1016/j.mfglet.2026.07.069","DOIUrl":"10.1016/j.mfglet.2026.07.069","url":null,"abstract":"<div><div>Metal additive manufacturing technologies have enabled the optimization of complex internal geometries for improved cooling, fluid transport, and weight reduction in components. A uniform smooth surface in these channels is critical to reduce particle shedding, pressure drop, corrosion nucleation and improve fatigue life. A key issue with metal additive manufacturing of these channels is the overhanging downskin surface, which is built on unsupported powder and often has much higher roughness and partially melted powders. To address this challenge, a teardrop shaped cross section, replacing the conventional circular one, is designed to minimize the overhang angle for better support of the downskin surface. However, the teardrop shaped channels are subject to non-uniform hoop stress around the lumen, elevated stress concentration, and reduced flow efficiency. To strike the balance between the printability and functionality of these complex channels, aiming for a circular cross section with a uniform, smooth surface, in this study, we introduce a novel hydrodynamic flexible (HydroFlex) machining process. HydroFlex machining, utilizing a carbide high-speed rotary cutter, driven by a flexible spindle, can navigate through a complex channel and machine the channel cross section from non-circular (e.g., teardrop) to circular. The HydroFlex cutter is submerged in coolant, and its high-speed rotation leads to a swirling coolant flow and a hydrodynamic orbital motion circling around the channel cross section, which is key to controlled material removal. To investigate the HydroFlex machining mechanism and demonstrate its capability to modify the teardrop cross section to a smooth circular cross section in metal additively manufactured channels, experiments were conducted to measure the grinding wheel motion, channel cross section geometry, surface roughness, and material removal rate. Results indicated that HydroFlex machining improved circularity by 30%, modifying the initial teardrop to a smooth ellipse cross section. This smooth ellipse cross section enabled a final HydroFlex polishing operation to improve the areal surface roughness by 75%. These results suggest that HydroFlex machining is effective in post-processing as-built metal additively manufactured internal channels to modify cross-section geometry and improve surface finishing.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 577-583"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational and Experimental Studies on Structural and Mechanical Properties of Ni-Al-Co-Cr-Cu-Mn-Ti High Entropy Alloys","authors":"Peter Ifeolu Odetola,&nbsp;Ufoma Silas Anamu,&nbsp;Peter Apata Olubambi","doi":"10.1016/j.mfglet.2026.07.037","DOIUrl":"10.1016/j.mfglet.2026.07.037","url":null,"abstract":"<div><div>This study investigates the structural and mechanical properties of a promising Ni-Al-Cr-Cu-Mn-Ti high-entropy alloy (HEA) system, known for its potential to balance high strength and ductility, using an integrated computational and experimental approach. CALPHAD-based Thermo-Calc modeling was used to predict the phase formation and stability across equiatomic and non-equiatomic compositions. The alloys were synthesized via mechanical alloying and spark plasma sintering, with microstructural and mechanical characterization performed using XRD, SEM-EDS, and hardness testing. The results reveal a complex microstructure across all compositions, primarily comprising disordered-ordered solid solutions (BCC_B2 and FCC_L12) and intermetallic phases (Heusler_L21, Cr₃Mn₅, and Ni₃Ti_D024). Notably, the equiatomic composition (Alloy A) demonstrated the highest experimental hardness (789.8 HV), which was attributed to its dominant BCC_B2#2 phase, significantly exceeding its predicted value (204.7 HV). This notable discrepancy highlights the significant contribution of processing-induced microstructural features, such as nanoscale crystallite sizes (2.03-5.01 nm), which are not fully captured by the thermodynamic model, to the enhanced mechanical properties. A dual-phase structure balancing strength and ductility was observed, consistent with the valence electron concentration of 7.14, which promotes the coexistence of the FCC and BCC phases. The lightweight HEAs (density 6.78 g/cm3) demonstrate promising mechanical properties for aerospace, automotive, and energy applications. This study demonstrates that the synergy between computational modeling and experimental validation is crucial for designing and optimizing HEAs, revealing that processing-induced microstructural refinement significantly enhances properties beyond thermodynamic predictions, thereby enabling the rational design of alloys with tailored properties for demanding applications.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 283-295"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental validation of melt pool temperature and height prediction model for robotic welding","authors":"Ahmed Khalil,&nbsp;Reza Tafreshi,&nbsp;Prabhakar R. Pagilla","doi":"10.1016/j.mfglet.2026.07.047","DOIUrl":"10.1016/j.mfglet.2026.07.047","url":null,"abstract":"<div><div>This paper develops a control-oriented model to predict fillet melt-pool temperature and bead height in robotic Gas Metal Arc Welding (GMAW) and experimentally validates model’s predictions. The model is derived from first principles through coupled mass- and energy-balance equations that describe the evolution of molten-pool height and temperature using a lumped-parameter formulation suitable for real-time control. Model coefficients describing geometric behavior are calibrated from post-weld measurements of steady-state bead height trends. The model was experimentally validated on a UR10e collaborative robot executing straight fillet welds using two wire diameters (0.889 mm and 1.5875 mm) across voltages of 20-34 V and travel speeds of 8-25 mm/s. A short-wavelength infrared camera captures the in-situ thermal fields while post-weld photographs provide ground-truth geometry for validation. An image-processing pipeline converts the thermal frames into per-frame height estimates that track post-weld profiles with frame-wise deviations of approximately 3.5–10%. The model predicts that temperature increases with voltage and reinforcement decreases with travel speed, matching experimental trends with low error. For pool temperature, the mean absolute and root mean squared errors are 21.7/26.1 <span><math><mrow><mi>°</mi></mrow></math></span>C for the 0.889 mm wire and 13.4/16.3 <span><math><mrow><mi>°</mi></mrow></math></span>C for the 1.5875 mm wire. For bead height, the corresponding errors are 0.375/0.477 mm and 0.527/0.667 mm.</div><div>These results confirm that the physics-based model captures the coupled thermal and geometric behavior of fillet welding with accuracy suitable for model-based estimation and control.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 367-376"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of the Influence of Parametric Design Factors on the Mechanical Performance of Porous TPMS Bone Scaffolds","authors":"Haley Smith,&nbsp;Hannah Hanlon,&nbsp;Roozbeh Ross Salary","doi":"10.1016/j.mfglet.2026.07.049","DOIUrl":"10.1016/j.mfglet.2026.07.049","url":null,"abstract":"<div><div>Tissue engineering offers a regenerative strategy for treating bone fractures and defects by integrating biomaterials, cells, and additive manufacturing techniques to fabricate porous scaffolds that promote bone regeneration. However, the mechanical performance of these scaffolds is highly sensitive to their design parameters, which dictate porosity, surface morphology, and load-bearing capacity. While previous studies have focused extensively on material composition and biological evaluation, the influence of geometric design parameters, particularly within Triply Periodic Minimal Surface (TPMS) architectures, remains insufficiently explored. The objective of this study is to systematically investigate how key TPMS design parameters influence the structural and mechanical behavior of additively manufactured bone scaffolds. Using a mathematically defined model, several design parameters (including <em>Step Size</em>, <em>B-Spline</em>, <em>Z Slider</em>, <em>YCount</em>, <em>IsoValue</em>, and <em>Distance</em>) were systematically varied and fabricated via fused deposition modeling fabrication using SimuBone material. Compression testing was conducted to determine stiffness and deformation behavior. The results revealed that geometric and parametric variations had a significant effect on mass deposition and compression modulus. Design 7.2 (from the <em>Distance</em> group) and Design 1.1 (from the <em>Step Size</em> group) demonstrated optimal combinations of strength and efficiency, showing high stiffness despite moderate mass or density, while over-smoothed or irregular geometries exhibited reduced mechanical integrity. Overall, the findings underscore the importance of design parameter optimization for balancing porosity, structural uniformity, and mechanical strength. This work paves the way for design-guided scaffold optimization, and contributes to the development of mechanically robust scaffolds for bone tissue engineering applications.</div><div>© 2026 The Authors. Published by ELSEVIER Ltd. This is an open access article under the CC BY-NC-ND license (<span><span>https://creativecommons.org/licenses/by-nc-nd/4.0</span><svg><path></path></svg></span>)</div><div>Peer-review under responsibility of the scientific committee of the NAMRI|SME.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 387-398"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving bending force prediction in L-die bending process","authors":"Saowalak Kongiang,&nbsp;Masahiko Jin,&nbsp;Sutasn Thipprakmas","doi":"10.1016/j.mfglet.2026.07.056","DOIUrl":"10.1016/j.mfglet.2026.07.056","url":null,"abstract":"<div><div>Reducing production costs in sheet-metal forming is often accomplished by carefully matching the press machine capacity to the required forming force. Consequently, press machine capacity can be selected more appropriately when the forming force is predicted more accurately. Existing formulas for L-die bending force calculation demonstrate limited accuracy in predicting the actual force required during the bending process. In this research, the calculation of the L-die bending force was revised based on the L-die bending mechanism, using both the finite element method (FEM) and experimental analysis. Because the bending mechanisms differ between a 90° die angle and a die angle greater than 90°, the L-die bending force prediction required specific modifications for each case. Accordingly, this research proposes two improved bending force prediction models for the L-die bending process under two specific conditions: a die angle of 90° and a die angle greater than 90°. By comparison with the experimental data, the accuracy of the improved L-die bending force predictions was re-evaluated. The results were also compared with the L-die bending force calculation methods currently in use. When comparing the bending forces obtained from experimental work with those predicted by the existing L-die bending force formulas, significant inaccuracies were observed—exceeding 40% for a 90° die angle and 80% for a die angle greater than 90°. However, when comparing the improved L-die bending force predictions proposed in this research with the experimental results, the prediction error was reduced to less than approximately 1%.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 453-464"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-situ Sensing of Recoating Force in Metal Binder Jetting and a Preliminary Investigation of Its Relationship to Packing Density","authors":"Chen Qian,&nbsp;Chinedum Okwudire","doi":"10.1016/j.mfglet.2026.07.101","DOIUrl":"10.1016/j.mfglet.2026.07.101","url":null,"abstract":"<div><div>Metal binder jetting (MBJ) is an additive manufacturing process that offers advantages such as a wide range of compatible materials, high speed, and low residual stress. A major hurdle in the application of MBJ is the low density of the printed part compared to other additive manufacturing processes. We propose to use closed-loop feedback control in the powder spreading process in MBJ to improve the density of the printed part. To implement the closed-loop feedback control, an in-situ, real-time packing density measurement method needs to be created. This research experimentally verified the hypothesis that there is a positive correlation between packing density and the reaction force from the powder bed during the recoating process (i.e, recoating force) with a modified Desktop Metal Innovent+ 3D printer. However, limitations exist. Anomalies existed in the calibration curve, the recoating force measurement was noisy, and the collected dataset size was small. The future work will focus on taking multi-modal measurements, improving the mechanical design, and taking finer measurements to address the limitations in the current setup.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 868-875"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-stage Intelligent Dynamic Scheduling Framework for Re-entrant Blocking Flow Shops with Central Buffer","authors":"Donghai Wang,&nbsp;Jing Zou,&nbsp;Xinan Zhou,&nbsp;Yang Xiang,&nbsp;Ziyun Huang,&nbsp;Sun Jin","doi":"10.1016/j.mfglet.2026.07.029","DOIUrl":"10.1016/j.mfglet.2026.07.029","url":null,"abstract":"<div><div>Re-entrant blocking flow shops are commonly encountered in modern discrete manufacturing processes, where jobs revisit stations and blocking occurs without intermediate buffers. To improve efficiency and minimize makespan, this study proposes a two-stage intelligent dynamic scheduling framework for re-entrant blocking flow shops with a central buffer. A system-level disjunctive graph is constructed to model interactions among operations, machines, and the buffer, and the scheduling problem is reformulated as a two-stage Markov Decision Process. A hybrid Graph Neural Network – Long Short Term Memory Network is developed to encode spatial–temporal features, while a hierarchical policy alternates between operation–resource selection and job assignment. Experimental results across multiple cases show that the proposed method clearly outperforms representative heuristic rules, achieving an average makespan improvement of 8%. Moreover, it attains solution quality comparable to genetic algorithm optimization with extended computation time while maintaining millisecond-level inference latency. These results demonstrate the framework’s effectiveness, scalability, and real-time applicability for intelligent scheduling in complex manufacturing environments.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 195-203"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wearable-IMU Machine Learning for Exertion and Fatigue Assessment with an Occupational Exoskeleton in Manufacturing","authors":"Sachin Prabhakar,&nbsp;Armin Moghadam,&nbsp;Fatemeh Davoudi Kakhki","doi":"10.1016/j.mfglet.2026.07.032","DOIUrl":"10.1016/j.mfglet.2026.07.032","url":null,"abstract":"<div><div>Exoskeletons are increasingly used to reduce physical strain in manual material handling, yet their true influence on worker exertion and fatigue remains challenging to quantify due to the lack of scalable and objective assessment methods. This study introduces a wearable-sensor framework that links subjective workload perception to quantifiable biomechanical responses during realistic industrial tasks, performed with (Exo) and without (NoExo) passive shoulder exoskeleton assistance. Twenty participants completed three representative tasks including loading, overhead screwing, and palletizing, while wearing ten IMUs positioned on the upper trapezius, deltoids, biceps, lumbar erector spinae, and hamstrings. Accelerometer signals (at 148 Hz) were converted to magnitude, segmented into 0.5 s windows with 50% overlap, and reduced to six biomechanical features per sensor, yielding 60 features per window. The dataset comprised 36,901 NoExo and 38,023 Exo windows, each labeled through task-specific Borg-scale mappings. Machine-learning models were evaluated using Leave-One-Participant-Out cross-validation. Random Forest and XGBoost achieved the highest performance (median accuracy = 0.83, F1-weighted = 0.82), outperforming Logistic Regression and Linear Discriminant Analysis. Exoskeleton use decreased inter-participant variability and reduced misclassifications, with top models reaching near-perfect separability for several individuals (<span><math><mrow><mi>AUC</mi><mo>&gt;</mo><mn>0.95</mn></mrow></math></span>). Feature-importance analyses consistently identified the lower back and hamstrings as the most informative sensor locations, enabling up to a 70% reduction in sensor count with minimal performance degradation. Critically, the proportion of hard-exertion windows decreased by nearly 75% with exoskeleton assistance, demonstrating measurable ergonomic benefit. These results establish a deployment-ready approach for real-time, objective assessment of physical workload in manufacturing environments. The proposed framework advances scalable evaluation of assistive technologies, supports data-driven ergonomic design and training, and offers the first evidence that wearable IMU-based machine-learning models can reliably quantify exoskeleton effectiveness in complex, real-world occupational settings.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 228-239"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Edge-Modified Parameters and Heat Treatment on Ni50.4Ti49.6 LPBF Trabecular Structures for Biomedical Applications","authors":"Flavia Tucci,&nbsp;Rachele Bertolini,&nbsp;Andrea Ghiotti,&nbsp;Stefania Bruschi","doi":"10.1016/j.mfglet.2026.07.041","DOIUrl":"10.1016/j.mfglet.2026.07.041","url":null,"abstract":"<div><div>Among smart materials, nickel-titanium (NiTi) alloys stand out as one of the most widely employed materials for biomedical devices. This is largely due to its unique properties, such as superelasticity and shape memory effect, as well as its biocompatibility. The growing demand for personalized medical devices with mechanical and structural performances increasingly resembling natural human bone has positioned additive manufacturing (AM) as the preferred technology to meet these needs, enabling the production of complex, patient-specific architectures that traditional methods cannot efficiently achieve, such as trabecular structures. These architectures have been demonstrated to promote improved osseointegration at the implant-bone interface. However, the combined challenges of AM processes and the complex behavior of NiTi require careful choices to fully exploit the potential of this approach. In particular, the alloy is very sensitive to printing parameters, which can cause surface defects and varying levels of porosity. This study investigates how local adjustment of laser parameters at the structure edges, together with heat treatment (HT), affects Ni_50.4Ti₄₉.₆ trabecular architectures produced using laser powder bed fusion (LPBF). Three different sets of parameters were examined: one homogeneous (H) and two modified conditions at the edges (EM1, EM2) that had varying energy densities at the edges, higher and lower, respectively. The influence of energy input and heat treatment on chemical composition, transformation temperatures, porosity, surface morphology, and mechanical performance was systematically evaluated. The results showed that adjusting the energy at the edges helped reduce surface defects and composition differences, while heat treatment helped stabilize the austenitic phase (A_f &lt; 25 °C), enabling superelastic behavior at room temperature. The combination of homogeneous energy input and post-AM heat treatment provided well-balanced overall performance, increasing compressive failure force and a stable oxide formation, whereas edge-modified conditions improved surface characteristics that may be beneficial for osseointegration. These results highlight that accurate adjustment of LPBF parameters and heat treatment can lead to the fabrication of NiTi trabecular structures with optimized structural and functional properties, suitable for advanced and more customizable implant applications.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 321-329"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}