Engineering

Abstract: Photovoltaic (PV) systems are fundamentally limited by spectral mismatch between the solar spectrum and semiconductor band gaps, resulting in thermalization and transmission losses that reduce overall efficiency. This paper presents a critical review of spectral management approaches, focusing on solar spectrum splitting as a means to improve energy conversion. Existing strategies, including multijunction solar cells, optical spectrum splitting, dispersive and diffractive systems, luminescent solar concentrators, hybrid photovoltaic–thermal systems, and photonic filtering, are analyzed and compared. While these approaches improve spectral utilization, they are often constrained by fabrication complexity, alignment sensitivity, angular dependence, or inherent energy losses. A qualitative, integrative literature review methodology is used to evaluate performance, limitations, and implementation feasibility across these technologies. The analysis shows that no current approach simultaneously achieves high efficiency, low complexity, and robust performance under diffuse illumination. Photonic spectrum splitting combined with independently operated photovoltaic channels is identified as a promising direction. However, the absence of experimental validation remains a limitation, and future work should focus on developing compact, alignment-tolerant systems for practical applications.

Abstract: This work provides an experimental comparison between classical PID, analytically compensated PID, and fuzzy control applied to the speed control of a rover actuator based on a permanent magnet DC motor. Unlike most studies, which focus on classical metrics such as transient response and steady-state error, this work incorporates kinematic indicators such as acceleration and jerk to characterize the dynamic effort applied to the actuator. The results indicate that the fuzzy controller achieves the fastest transient response and the best disturbance rejection, although at the cost of an IAJ 2.378 times higher than that of the classical PID and a peak jerk 79.36% higher under nominal conditions. The classical PID exhibits the smoothest kinematic profile under nominal operation, but under disturbances it generates jerk peaks 2.39 times higher than the fuzzy controller and an IAJ 1.67 times higher than the compensated PID, evidencing its inadequacy under variable loads. The compensated PID achieves the lowest cumulative IAJ under disturbance, outperforming the fuzzy controller by 6.7%, and provides the best overall balance between response speed, disturbance rejection, and cumulative mechanical wear.

Abstract: Water hyacinth (Eichhornia crassipes) is an invasive aquatic plant with high lignocellulosic content, offering potential as a natural fiber resource for craft-based industries. However, its extremely high initial moisture content (≈95%) presents a major challenge in fiber processing, particularly for small-scale industries that rely on traditional sun-drying methods. These methods are highly dependent on weather conditions, prone to contamination, and produce inconsistent fiber quality. This study adopts a research and development (R&D) approach to design and evaluate an innovative dryer machine specifically for water hyacinth fiber processing. The proposed system utilizes LPG-based heating and controlled airflow to achieve stable drying conditions. Experimental results show that the dryer machine can process 10 kg of wet water hyacinth within 280 minutes, significantly shorter than approximately four days required for manual drying. The system reduces the moisture content to below 10%, resulting in improved fiber cleanliness, uniformity, and usability. Although the dried mass produced by the machine is slightly lower compared to manual drying, this is attributed to more effective moisture removal, leading to lower residual water content in the final product. Productivity analysis indicates improved operational consistency and higher processing capacity over extended periods (30–180 days), particularly under varying weather conditions. These findings demonstrate that controlled drying technology provides a reliable and efficient solution for lignocellulosic fiber processing in small-scale industries, contributing to improved material utilization and sustainable biomass management.

Abstract: Sugarcane harvester performance varies substantially with field geometry, crop, and operator factors, yet separating these sources from telematics data while preserving engineering interpretability remains a methodological gap. This study models field efficiency (Eff) and harvesting capacity (Ca) separately from JDLink telematics, aligning model structure with each target's response behavior. Operational data covered 105 plots across four seasons (2019/20–2022/23) from three John Deere chopper harvesters in eastern Thailand. Six engineering-relevant predictors were retained after multicollinearity screening, and linear (MLR), additive nonlinear (GAM), and tree-based models were compared under 5-fold grouped cross-validation by BaseField (87 groups). Eff was assigned to GAM (R²CV = 0.621 ± 0.114) on the basis of its threshold-like response to turning frequency; Ca was retained for MLR (R²CV = 0.681 ± 0.121), with GAM essentially tied. Train–validation gaps were substantially smaller for additive models (0.096–0.118) than for tuned tree-based candidates (GBR 0.210–0.302, RF 0.322–0.358). Turning frequency (TF) and perimeter-to-area ratio (PAR) were the strongest predictors, and a constant-turn-time partial-out test indicated that TF's univariate effect on Eff is largely mediated by the time-budget identity. Tactical interventions (path planning, operator training, machine–field allocation) are immediately feasible, although strategic field-layout change remains constrained by smallholder land tenure.

Abstract: Consolidated bioprocessing (CBP), where enzyme production, substrate hydrolysis, and fermentation occur in a single bioreactor, provides a promising pathway for lignocellulosic ethanol production. Nevertheless, CBP operation involves trade-offs among ethanol titer, productivity, substrate conversion, soluble sugar accumulation, batch cycle time, and the operating severity associated with temperature and pH profiles. This study introduces a feasibility-aware multi-objective dynamic optimization approach for identifying Pareto-optimal operating policies for batch CBP processes. A simplified, mechanistically driven dynamic model is developed to represent biomass growth, enzyme activity, insoluble substrate hydrolysis, soluble sugar formation and consumption, ethanol production, and inhibition under time-varying temperature and pH profiles. The multi-objective optimization simultaneously maximizes ethanol titer, productivity, and substrate conversion while minimizing sugar accumulation, operating severity, control effort, and batch time. In the main simulation run, 120,000 dynamic policies were evaluated, resulting in 5,017 feasible policies and 328 feasible Pareto-optimal policies under a minimum conversion threshold of 0.42. The optimized dynamic policy achieved an ethanol titer of 1.265 g L−1, a maximum productivity of 0.017 g L−1 h−1, and a maximum conversion of 0.440. Compared with the best static policies, the dynamic Pareto policies improved ethanol titer, productivity, and conversion by 10.6%, 8.3%, and 14.3%, respectively. The feasibility analysis showed that a conversion threshold of 0.42 is stringent but achievable, whereas thresholds of 0.44 and 0.55 were not attainable under the current dynamic model and operating range. Independent-seed repetition confirmed the existence of a consistent high-performing region across different stochastic searches. The resulting Pareto front and operating-policy charts provide a useful basis for selecting temperature and pH profiles for CBP process operation.

Abstract: The combination of ultra-dense network deployments and high mobility results in an unfavorable outcome, rendering the task of handover more difficult than in environments typical of previous generations. 5G and 6G necessitate the deployment of heterogeneous networks and small cells to meet the demand, which at the same time introduces certain challenges. This scenario introduces small cells (such as femtocells, picocells, and microcells) that have very limited coverage areas, which, combined with the high speed of user equipment, create an excessive number of handover triggers, leading to the “ping-pong effect,” which wastes network resources and degrades the overall Quality of Service. Furthermore, high mobility means that a user might enter and exit a cell in less time than the mobile terminal’s dwell time, dropping the connection and resulting in handover failures and radio link failures. The conventional handover methods that rely on thresholds of certain factors such as the received signal strength could be insufficient for these environments. Different criteria should be balanced to avoid the drop, such as the user’s velocity, dwell time, target cell load, available bandwidth, device battery, and application latency requirements. Predictive methods could be a more efficient alternative to the existing reactive ones. This paper presents a decision-tree-based algorithm as one predictive method that learns the patterns among all the criteria mentioned and is particularly useful for avoiding ping-pongs and limiting handover failures. The classifier is trained on real multi-operator drive-test data with ping-pong events excluded from the positive class, and evaluated under Leave-One-Trace-Out cross-validation on 16 traces covering UMTS, HSUPA, HSPA+, and LTE cells. The proposed system achieves F1=0.642 and AUC =0.797 under LOTO, with a +0.052F1 lift over the best threshold-based baseline, while remaining interpretable and deployable in real time. The paper aims to present a solution applicable also to 5G NR and 6G.

Abstract: The human temporomandibular joint requires stable kinematics for optimal function; however, structural anomalies such as the bifid mandibular condyle severely compromise this biomechanical harmony. This study aims to quantify the precise biomechanical behaviour and fracture susceptibility of the bifid condyle using patient-specific finite element analysis. A high-fidelity 3D computational model was constructed from the cone-beam computed tomography data of a patient presenting with a right bifid condyle and concurrent fracture. To establish a comparative baseline, a geometrically healthy control model was computationally derived. Both models were subjected to a simulated, physiological multiaxial masticatory load of 1000 N. The simulation revealed that while the healthy control safely dissipated forces (peak cortical von Mises stress of 62.49 MPa), the bifid morphology fundamentally disrupted load transfer. Extreme mechanical forces concentrated directly at the anomalous inter-condylar notch, generating peak equivalent von Mises stresses approaching 500 MPa and peak compressive stresses nearing 600 MPa. Furthermore, localised strain energy density at the notch peaked at 12 MPa. These internal stress magnitudes significantly exceed the ultimate yield strength of human cortical bone, providing a direct biomechanical rationale for the clinically observed fracture. This computational evidence establishes that the bifid condyle acts as a critical structural vulnerability and energy sink. Consequently, the identification of a bifid condyle warrants proactive clinical management, as even asymptomatic presentations are highly predisposed to structural fatigue and macroscopic failure.

Abstract: Fenestration systems play a critical role in building thermal performance, particularly in cooling-dominated climates where envelope inefficiencies directly amplify electricity demand. In Saudi Arabia and other Gulf Cooperation Council (GCC) countries, cooling accounts for the majority of building energy consumption. Nevertheless, the façade and insulated glass industries are experiencing rapid market expansion. Despite this technological evolution, prevailing regulatory frameworks, including the Saudi Building Code (SBC), ASHRAE 90.1, and the International Energy Conservation Code (IECC), primarily rely on area-weighted U-values and solar heat gain coefficients (SHGC), without explicitly integrating multidimensional thermal bridge effects such as linear thermal transmittance (ψ). This paper investigates the structural omission of ψ within current energy compliance systems, evaluates its implications in cooling-dominated climates, and proposes a phased regulatory integration pathway aligned with sustainability objectives under Vision 2030. Literature synthesis indicates that thermal bridges may increase cooling loads by up to 25% and total building energy use by 5–30%, while remaining structurally omitted from compliance metrics. The findings highlight the need to transition from simplified prescriptive compliance toward physics-informed governance capable of addressing evolving façade complexity in hot-arid environments. The proposed framework offers a systematic pathway for integrating linear thermal transmittance requirements while supporting regional sustainability goals and the advancement of high-performance building technologies.

Abstract: The high energy consumption of conventional mixers equipped with active mixing elements necessitates the development of more efficient technologies for mixing bulk materials and feed mixtures. This study proposes a gravity-based mixing method based on the rotation of an inclined cylindrical chamber without the use of active mixing elements. During rotation, the mixture components move toward both end walls of the chamber and simultaneously perform circular motion along the inner cylindrical surface, which intensifies the mixing process and reduces energy consumption. A structural and technological design of the gravity mixer was developed, and an experimental prototype was manufactured. Analytical relationships were obtained to determine the critical rotational speed of the chamber, particle movement velocity, and the power required for the mixing process. Laboratory experiments showed that the average particle movement velocity was 1.21 m/s and the average friction coefficient was 0.40. Under optimal operating conditions, the mixture uniformity reached 95.7% after 4 min of mixing. The mixer productivity was 0.95 t/h, while the specific energy consumption was 0.5 kWh/t, which is 2.5 times lower than that of conventional mixers equipped with active mixing elements. The obtained results confirm the potential of the proposed gravity-based mixing method for preparing feed and organomineral mixtures in small-scale farming systems.

Abstract: This paper presents a laboratory-validated integrated assessment framework combining Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) for the non-destructive evaluation of reinforced concrete (RC) structures. A single RC beam specimen (3000 × 300 × 200 mm; C30/37, w/c = 0.50, CEM I 42.5N; 3 × T12 at 35 mm soffit cover) was subjected to four precisely controlled deterioration states: intact dry (Model A), water-filled crack (Model B), fully saturated (Model C), and chloride-induced active corrosion (Model D). Seven ERT datasets were acquired using a Wenner-Schlumberger array at electrode spacings of a = 7, 15, and 30 mm, and three 800 MHz GPR profiles were recorded for Models A, B, and C/D respectively. The ERT results demonstrate a systematic three-orders-of-magnitude decrease in median resistivity from the intact state (ρ₀ = 558 Ω·m) to the corroded condition (ρ = 10.6 Ω·m), with a depth-preferential low-resistivity distribution at rebar depth (z ≈ 24–48 mm; ρ < 10 Ω·m) providing partial discrimination between active corrosion and bulk moisture saturation. GPR analysis at 800 MHz confirms a reference wave velocity of v = 0.096 ± 0.008 m/ns by hyperbola fitting, localised 25–35% amplitude attenuation at the water-filled crack position, and pervasive 50–65% attenuation under saturated and corroded conditions. A four-stage integrated interpretation framework is validated against known ground-truth conditions: Stage 1 establishes local reference baselines (ρ₀, A₀); Stage 2 identifies anomalies against threshold criteria; Stage 3 cross-validates co-located GPR and ERT signatures; Stage 4 assigns risk categories 1–4. Explicit failure mode analysis identifies six conditions under which the framework is unreliable, most critically the moisture–corrosion ambiguity and the invisibility of dry cracks. The framework correctly classifies all four beam conditions and provides higher diagnostic confidence than either method applied independently.

Abstract: In this study, the traffic operational effects of a pacemaker system (PMS) on the traffic operation in the Geumnam Tunnel on the Seoul–Yangyang Expressway was evaluated herein using a before–after analysis based on long-term vehicle detection system (VDS) data. Changes in spatiotemporal traffic flow and traffic capacity, and speed improvement under different levels of service (LOS) were analyzed using data from five VDS detectors installed upstream and downstream of the tunnel. After PMS installation, (i) increased average and 25th-percentile speeds at most detector locations and decreased standard deviation of speed were observed both near the tunnel exit and the downstream sections, (ii) maximum traffic volume was increased from 1661 to 1765 veh/h/lane (~6.3% increase), (iii) LOS-based speed improvement analysis showed that mean speed and 25th-percentile speed increased by ~6.5%, indicating the alleviation of speed reduction among low-speed vehicles due to PMS. These results prove that PMS increases vehicle speed, reduces speed variability, and enhances traffic flow stability and processing capability. These findings provide empirical evidence supporting the operational effectiveness of a PMS as a practical tool for mitigating phantom congestion in highway tunnel sections and reducing the speed differences between vehicles and improve traffic stream stability.

Abstract: Intense rainfall, and the resulting increase in ground saturation can significantly modify the mechanical performance of rock masses in natural slopes. This is particularly important if material fractured is present. Extended infiltration accelerates material degradation, reduces shear strength along discontinuities, and increases pore-water pressures, reducing effective stresses, and in turn, raises the probability of large-scale landslides. Evaluating these processes requires a thorough understanding of the geotechnical and hydrogeological properties controlling slope response, as well as reliable stability assessments under varying saturation conditions, including factor of safety and deformation estimates. However, in engineering practice most of the time ground exploration is limited, and laboratory testing in rocks only provides an estimation of the rock performance expected in the slope within a reduced zone. This study examines a landslide triggered in a shale–limestone slope after heavy rainfall. A back-analysis was performed within a performance-based design (PBD) framework to reproduce the observed failure and, thus, characterize representative geomechanically parameters for design validation, using three-dimensional finite difference modeling. The performance under monotonic and seismic loading of a tunnel built adjacent to the slope was analyzed as a mitigation measure, thus establishing its technical soundness, from both state limit of failure and service, of the tunnel-slope system.

Abstract: Lithium-ion batteries are prone to internal short circuits and subsequent thermal runaway under compression and impact loads during electric vehicle crashes, posing a critical safety challenge for the industry. However, existing studies lack systematic comparative analysis between quasi-static and dynamic loading conditions. In this study, 26 Ah ternary pouch lithium-ion batteries were used as research objects. A test platform for synchronous acquisition of mechanical load, electrical voltage and thermal temperature was established. Quasi-static compression and drop-weight impact tests were conducted to investigate the effects of indenter diameter, impact velocity and state of charge (SOC) on the multiphysics responses of batteries. The results show significant differences in failure modes between the two loading conditions: quasi-static loading causes progressive plastic deformation and stable short-circuit voltage decay, while dynamic loading induces brittle shear fracture and soft short-circuit voltage rebound. Under non-thermal runaway conditions, the temperature rise amplitude under dynamic impact is approximately 20% higher than that under quasi-static compression. High SOC alters the heat release pathway during thermal runaway, leading to deviations in surface temperature measurements. These findings provide critical experimental support for the crash safety design of power batteries and the formulation of thermal runaway prevention and control strategies.

Abstract: Emerging technologies and cyber-physical systems have led to the development of complex mathematical models described by differential equations with multiple fractional orders. In this regard, this paper investigates the stability of control systems for this class of models, defined by state equations with multiple fractional orders ranging between 0 and 1. Matrix criteria and comparison principle for linear and nonlinear autonomous systems of different fractional orders are developed based on generalized Lyapunov functions for differential equations with multi-order fractional exponents. The results are extended to non-autonomous linear or with nonlinear components systems of different fractional orders. The application of the Yakubovich-Kalman-Popov lemma, adapted for this class of systems, allows us to obtain new stability criteria presented as frequency criteria and represented graphically by familiar frequency plots similar those of the Nyquist or Popov type. Numerical applications illustrate these results such as models of complex human-machine systems described by state equations of multivariable fractional orders. An analysis of the advantages of the proposed methods compared to procedures and techniques used in other papers regarding the study of multi-order fractional exponent systems is presented. It is demonstrated that the proposed methods minimize the computational effort required for stability criteria.

Abstract: In Jordan, the construction industry and businesses are burdened by the high prices of materials in terms of extraction, production, transportation, and purchasing, as well as the volatility of their market value. The environment is primarily affected by construction and demolition activity since the construction sector in Jordan is based on a linear economy model and does not rely on the circular economy (CE) by reusing or recycling building materials rather than discarding them. Therefore, this study aims to develop a CE framework for managing construction waste in residential buildings during the construction phase and facilitating the adoption of the proposed model within the construction sector in Jordan. Therefore, a questionnaire was distributed to 31 experts, the results were analyzed, and the Delphi technique was then applied to validate the proposed framework and study findings. The findings indicate that the CE contributes to minimizing construction waste. The researcher sought to identify the most significant challenges hindering the implementation of the CE. The most influential challenges were low demand for reused or recycled materials, limited stakeholder awareness, and difficulties in disassembly. Furthermore, the results indicated use of visual management and 5S techniques, the use of BIM to map materials and components for circular lifecycle planning, and offering tax incentives and grants for using recycled materials are the most important strategies for minimizing construction waste. This study contributes to minimizing construction waste and advancing sustainable development, while also supporting Jordan’s Vision 2025 as outlined by the Jordanian government and the Ministry of Environment.

Abstract: Programmed conservation of heritage buildings requires assessment tools capable of iden-tifying vulnerabilities in a systematic and decision-oriented manner. This study proposes and applies a methodology for calculating the vulnerability index of the National Theatre of Costa Rica, with the aim of establishing a technical baseline for monitoring, prioritizing interventions, and supporting long-term conservation management. The method struc-tures vulnerability through four dimensions (systems, environment, use, and urban pres-sure), each subdivided into specific risk variables weighted through the Analytic Hierar-chy Process (AHP) and pairwise comparison matrices. The building was assessed through 33 spaces grouped into 17 zones, based on two on-site evaluation campaigns, and the re-sults were consolidated into a global assessment matrix. The findings indicate an overall low vulnerability index for the building (1.391), with similarly low values recorded for systems (1.549), use (1.450), environment (1.268), and urban pressure (1.198). However, the South Façade (1.824) and the Foyer (1.778) reached medium vulnerability levels, while several additional spaces were close to that threshold. The results suggest that use-related conditions exert the greatest influence on the overall index, whereas systems-related is-sues—particularly electrical installations—remain a relevant field for intervention. The study supports the applicability of the proposed method as an objective instrument for programmed conservation of built heritage.

Abstract: p-GaN gate enhancement-mode GaN HEMTs are promising normally-off power devices, but their high-temperature reliability is strongly affected by the gate contact scheme. This study compares Pd-ohmic and Ni-Schottky p-GaN gate HEMTs fabricated on the same GaN-on-Si epitaxial platform by combining temperature-dependent electrical characterization, post-temperature-dependent-test (TDT) room-temperature recovery analysis, and thermoreflectance thermal mapping. Electrical measurements were performed from room temperature to 500 °C using gate leakage, transfer, and output characteristics, while thermal maps were obtained before and after TDT under identical bias conditions. The Pd-ohmic devices exhibited higher initial current drive but larger operating gate-current penalty and stronger degradation of normalized on-state characteristics at elevated temperature. After TDT, reduced transconductance and maximum drain current were accompanied by weaker active-channel heating, indicating degradation-type cooling associated with reduced gate-channel modulation efficiency. In contrast, the Ni-Schottky devices showed lower gate-current penalty and better normalized output retention up to approximately 300 °C; however, post-TDT increases in transconductance and drain current occurred together with degraded subthreshold swing and persistent localized heating, indicating apparent on-state activation with weakened gate/depletion control. These results show that p-GaN gate reliability should be assessed through coupled electrical and thermal signatures rather than single electrical or thermal metrics.

Abstract: Food fraud is a persistent global threat estimated to cost the food industry over USD 30 billion annually. The integration of artificial intelligence (AI) with analytical instrumentation has generated significant research activity directed at developing detection systems capable of identifying adulteration, mislabeling, and substitution across diverse food matrices. This systematic review critically examines the extent to which AI-assisted instrumental technologies contribute to food fraud prevention, and identifies the structural limitations that constrain their real-world implementation. A systematic search of peer-reviewed literature published between 2021 and 2026 yielded 72 eligible studies after application of predefined inclusion criteria. Studies were required to report quantitative performance metrics (accuracy, R², RMSE, AUC, sensitivity, specificity), describe methodological limitations, and mention laboratory or industrial implementation contexts. Data were extracted into a structured seven-sheet workbook covering study characteristics, instrumental technologies, AI architectures, performance metrics, industrial validation status, implementation evidence, and methodological quality. The corpus reveals a systematic pattern of high reported analytical accuracy—frequently exceeding 95% and in many cases reaching 100%—under controlled laboratory conditions. However, 75% of studies (54/72) conducted no external validation, 100% of studies reported no pilot-scale or routine monitoring application, and no study achieved inter-laboratory validation. The predominant technology was NIR spectroscopy (26/72 studies, 36%), followed by gas chromatography-based systems (14/72, 19%) and electronic noses (8/72, 11%). Classical machine learning—predominantly SVM, Random Forest, and ANN—dominated methodological approaches (43/72, 60%), with deep learning architectures accounting for 26% of studies. Technology Readiness Levels were unreported in 97% of studies. Methodological quality was predominantly moderate (42/72 studies scoring 3/5), with 19 studies scoring 2/5 and only one achieving the maximum score. This review identifies a structural gap between detection and prevention as the central finding: the scientific literature consistently demonstrates high analytical precision in laboratory settings while providing minimal evidence of real-world industrial deployment, regulatory integration, or measurable impact on the prevention of food fraud events. The findings demonstrate that the limitation is not primarily technological but systemic, highlighting the need for a paradigm shift from performance-driven research toward validation-driven, deployment-oriented frameworks.

Abstract: An approach for the control of linear control systems with a single time-delay is proposed. The main contribution is the inclusion of a symmetric-injection virtual reference trajectory into the controller to render stability robustness of single-delay linear control systems. The dynamics of the virtual trajectory is included into the closed-loop dynamics allowing theoretical computation of the critical time-delay before losing stability. Moreover, an energy-based symmetry interpretation of the proposed approach is drawn. Numerical simulations considering stable and unstable linear systems are shown, and experiments to control a DC-motor with time-delay measurements validate our proposal.

Abstract: Emerging materials often face challenges in market adoption due to limited comparability and reliability of measurement-based material information, despite their potential to drive technological innovation. While standardization is widely recognized as an important mechanism for market diffusion, existing approaches provide limited insight into how material specifications facilitate the comparative evaluation of material characteristics and their use in market decision-making. This study proposes a complementary perspective that interprets standardization as an infrastructure for organizing the generation, sharing, and evaluation of measurement-based material information across industry, standard development organizations (SDOs), and markets. Within this framework, the study distinguishes between two complementary types of standards for material specifications. Type A standards enable the structured disclosure of measured characteristic values and associated measurement uncertainties, allowing application-specific evaluation without predefined acceptance criteria. In contrast, Type B standards define predefined characteristic values and compliance criteria, providing a basis for conformity assessment, certification, and quality assurance. These two types may be understood as complementary mechanisms that fulfill different functions of comparability and compliance under varying technological and market conditions in emerging material systems. Consequently, they contribute to both innovation-oriented market evaluation and quality-assured market acceptance.