Closing Editorial: Feature Papers Collection: Celebration of the First Impact Factor of Metrology

1. Introduction and Summary

In 2025, Metrology (ISSN 2673-8244) received its first Impact Factor of 1.5, as published in the 2025 Edition of Journal Citation Reports^® (Clarivate), released in June 2025.

To celebrate this wonderful achievement, we launched this Special Issue, aiming to publish top-quality papers from Editorial Board Members and leading researchers who have been invited to submit their work by the Editorial Team. As hoped and expected, the papers provide a flavor of the typical scope of our journal, reflecting both basic metrological problems and the application of basic metrological principles to practical issues.

In this brief editorial, we celebrate the successful conclusion of this Special Issue, which has attracted eight high-quality research contributions from leading international research groups. These articles collectively address the critical challenges and opportunities in the field of metrology, covering both fundamental research and practical applications, and demonstrate the strong engagement of our field with the broader scientific community.

2. An Overview of Published Articles

The contributions to this Special Issue encompass several thematic areas that represent both the current state of the art and emerging directions in metrology.

2.1. Characterization of Geometry: From Flat, Curved, Rough to Fully 3D Robot Analysis

A perfect flat is a basic geometry, and granite surface plates are aimed at approaching such a flat surface to form the basis of dimensional measurements in the workshop. The measurement of such plates is a classical dimensional measurement problem that was considered to be solved in the early 1990s [1,2], with as a loose end the classical Moody method [3], which is still in common use today. In his paper the Editor-in-Chief shows that improvement is possible using least-squares and minimum-zone principles, using a Monte-Carlo method for the uncertainty analysis, where bias effects can be observed. When surfaces are less flat and the geometry is described by curvature metrics [4], Malenkov et al., in their paper, show that for such a description of geometry a Monte Carlo-based uncertainty evaluation reveals bias effects as well, demonstrating high sensitivity to measurement errors. Local form deviations also provide the basis for roughness measurements, where averaging parameters like Sa and Sq are most common [5]. Modern digital analysis techniques have enabled the evaluation of a greater number of parameters. Moreau et al. identify the Sdr (“developed length”) parameter as being most sensitive to temporal changes on a surface. This parameter also has promising multi-scale characteristics [6], making it a welcome alternative to other, long-established parameters. Moving to larger scales, the metrological evaluation of robot performance is elaborated by Sabol et al. Based on ISO 9283 [7], the software solutions developed simplify the process of interpretation and reduce the need for additional external tools. Based on the obtained data, the robot’s performance can be evaluated in terms of pose accuracy and pose repeatability [8]. In addition, robot parameters can be monitored and evaluated over an extended period, allowing the proposed solution to be used in predictive maintenance.

2.2. The Value of Low-Cost Metrology Solutions

Low-cost metrology solutions can be of great value if applied thoughtfully. Rodrigues-Rama et al. demonstrate the potential of low-cost metrology solutions in encapsulated digital temperature sensors [9], where the calibration allows them to reduce the manufacturer’s specification of ± 0.5 °C to uncertainties within ± 0.2 °C. Bülau et al. develop a low-cost microwave resonator for exciting a diamond sample [10], enabling optically detected magnetic resonance and enhancing the portability of quantum sensors based on this technology [11].

2.3. Metrological Assessment of pH_T

The total pH scale, represented by the pH_T value, is an essential measure for ocean acidification. In order to closely monitor this climate change-related quantity, certified reference materials (CRMs) are urgently needed [12]. Quandera et al. contribute to this subject by characterizing Harned cells with artificial seawater of varying salinities and temperatures, thus characterizing the SI-traceable metrological standards for pH_T characterization and thereby offering a practical tool for high-accuracy calibration in variable marine conditions.

2.4. Testing of Aged Glass Fiber-Reinforced Thermoplastics

Although the domains of testing and metrology have been separate for a long time, Palacios Merono and Mertiny demonstrate that a concerted metrology-based approach to testing, combined with machine learning, provides a solid basis for assessing mechanical degradation in fiber-enforced thermoplastics [13]. Taking the metrological properties into account, mass change metrology [14], tensile testing [15], and acoustic emission technologies supported by machine learning [16] were employed, and the results were confirmed by optical microscopy.