High-precision Characterization Research Articles

A Study of Carbon Emissions during the Operational Period of an Integrated Expressway Construction Station

An integrated construction station for an expressway is characterized by complex carbon emission sources and high carbon emission intensity. Conducting carbon emissions accounting makes possible a comprehensive understanding of these characteristics, enabling targeted and guided carbon reduction efforts, which is crucial for advancing the low-carbon development of expressway construction. This paper, based on an in-depth analysis of the carbon emission structure during the operational period of an integrated expressway construction station identifies, as calculation boundaries, eight categories: residential areas, station transportation, mixing stations, precast beams, steel bar yards, artificial carbon emissions, chemical reactions during construction, and construction conditions. The study adopts a “bottom-up” approach to carbon emission measurement and constructs a carbon emission model for the production and operational period of the integrated construction station, based on the carbon emission factor method. Using the SG-2 section of the Fengqiu to Xiuwu stretch of the Changxiu Expressway as an engineering case, carbon emissions accounting for each component of the integrated construction station’s operational period was conducted, and the results were compared with the station’s monitoring system. High-precision characterization and calculation of total carbon emissions, as well as emissions from each process and piece of equipment during the operational period, were achieved. The results indicate that: (1) the relative error between the overall calculation results and actual monitoring is 3.6%, verifying the model’s accuracy; (2) the monthly carbon emissions of the integrated construction station during the operational period reached 72.15 tons; (3) there is a significant difference in carbon emissions among the different processes, with the highest emissions coming from transportation and residential areas, accounting for 43.4% and 23.7%, respectively. Therefore, electrification of transportation equipment could significantly reduce the overall carbon emissions of the integrated construction station.

EFFECT OF SILVER DOPING ON IRON OXIDE ELECTRICAL PROPERTIES

Iron silver oxide (Agx[Formula: see text]O3; [Formula: see text]) structure for photoelectrochemical (PEC) water splitting was grown by RF–DC co-sputtering of an iron–silver target in argon/oxygen plasma mixtures at 300°C, followed by thermal annealing at 560°C. The chemical composition and structure of the deposited film can be tuned by controlling the metal doping and the annealing temperature. The thermal treatment extensively improves the PEC water-splitting performances of the films. XRD patterns of AgxFe[Formula: see text]O3 shown in the figure can be indexed to the hexagonal structure of silver oxide and the rhombohedral structure of hematite and new X-ray Diffraction (XRD) peaks of AgxFe[Formula: see text]O3 structure. The annealing and doping process seems to cause a serious change in the crystal structure of the thin film, it showed a serious change in its electrical properties. The electrical parameters of resistance for thin films were measured using the Hall measurement method at room temperature. With Hall measurements, the n-type carrier concentration of the Fe2O3 structure was calculated, and it was observed that its resistance was 1[Formula: see text]M[Formula: see text]. Likewise, it was observed that AgxFe[Formula: see text]O3 exhibited an n-type carrier concentration, and its resistance was calculated to be 0.5[Formula: see text]M[Formula: see text]. The conductivity change is based on silver doping. The doping process seems to cause a change in the bandgap of the thin film, it showed a change in its optical properties. The film’s optical absorption was measured by UV–Vis photo spectroscopy. Subsequently, the structural and topographic properties of AgxFe[Formula: see text]O3 structures were investigated by high-precision characterization devices.

High-precision characterization of quantum-cascade laser frequency response using wavelength modulation spectroscopy.

This paper investigates the impact of the quantum cascade laser's frequency modulation response on its tuning rate and tunability. We show a significant disparity in laser tuning rates and tunability between single and dual-frequency modulation schemes frequently used in typical direct absorption and wavelength modulation spectroscopy (WMS) techniques. We show that the DC-characterized tuning rate of a laser can be reduced significantly under a specific set of modulation frequencies of the laser injection current. We characterize these effects by simultaneous measurements of higher harmonic WMS of methane and nitrous oxide in the 7.8 µm spectral regions. We further show that WMS signal modulation broadening mechanisms and spectral structure, i.e., its zero-crossings and turning points, can be used to quantify such laser-modulation effects and validate laser frequency response under dual modulation schemes.

Three-Dimensional Ultrasonic Reverse-Time Migration Imaging of Submarine Pipeline Nondestructive Testing in Cylindrical Coordinates

Submarine pipelines are a safe and energy-efficient mode of gas transport. However, due to the complex manufacturing process and harsh operating environment, submarine pipelines are subject to fatigue cracks under long-term cyclic loading. A comprehensive and high-precision characterization strategy for submarine pipelines can effectively prevent potential safety hazards and have significant economic and social repercussions. As a matter of fact, pipeline defects cannot be reliably detected with current traditional 2D methods. On the other hand, in ultrasonic testing, cylindrical geometry increases the complexity of the 3D wave field in the submarine pipeline space and significantly influences the accuracy of the detection results. In this paper, we put forward a novel method for 3D ultrasonic image testing that is suitable for cylindrical coordinates. In order to accurately simulate the ultrasonic signal received from pipelines, we generalize the 3D staggered-grid finite-difference method from Cartesian coordinates to cylindrical ones and simulate the full wave field in the 3D pipeline space. Then, signal processing is performed on the ultrasound simulation records, and 3D reverse-time migration imaging of submarine pipeline defects can be effectively achieved using the reverse-time migration method and cross-correlation imaging conditions. The results obtained from simulations and real field data show that the proposed method provides high-quality 3D imaging of defects in pipelines, taking into account multiple scattering and mode conversion information at the bottom of the defects.

Self-assembled layered lithium manganese oxide shows ultra-large adsorption capacity and high selectivity for lithium

Lithium manganese oxides (LMOs) are competitive materials for lithium extraction from aqueous resources. However, traditional LMOs are yet to be industrialized based on their existing lithium adsorption capacities. In this work, Li1.90Mn1.52O4, a self-assembled layered LMO, is innovatively synthesized with an accurately measured structure using multiple high-precision characterization technologies, and its adsorbent has an ultra-large lithium adsorption capacity of 66 mg/g. Synthesis experiments and related density functional theory (DFT) calculations show that the self-assembled synthesis of Li1.90Mn1.52O4 occurs during the hydrothermal process and is abstracted into three steps: first, manganese oxide dissolves into manganese oxide octahedron [MnO6] groups; second, the [MnO6] groups form metastable and thin-layer δ-type manganese oxide (δ-MnO2) by self-assembly; third, the pre-product of Li1.90Mn1.52O4 is formed by the reaction between the δ-MnO2 and the hydroxide ions with lithium ions embedded between layers. The selectivity experiments and corresponding DFT calculations show that the selective adsorption process of H1.90Mn1.52O4 follows the selectivity order “Li+ ≫ Na+ > K+ > Ca2+ > Mg2+” and is divided into two steps: first, the hydrated metal ions from the liquid resources leave the water molecules and transfer to the surface of H1.90Mn1.52O4; second, the metal ions migrate into the adsorption sites via the ultra-narrow ion transfer channels.

Tri-functional lanthanum-based biochar for efficient phosphorus recovery, bacterial inhibition, and soil fertility enhancement

Excess phosphorus (P) in water can lead to eutrophication and upset ecological balance. In this study, biochar with ultrathin two-dimensional nanosheets from the natural mesocarp of shaddock was chosen as the carrier. The highly dispersed and small particle size of La(OH)3 on the surface of the nanosheets (MSBL3) was successfully achieved using chemical impregnation for the adsorption of P in aqueous solution, and the maximum adsorption capacity was 260.0 mg P g−1 [La]. The differences in surface crystallization of La(OH)3 on biochar at different La loadings were analyzed using the high-precision characterization methods. After six adsorption–desorption cycles, MSBL3 retained 76.7% of its initial performance in terms of the P adsorption capacity. The preparation of 1 g of MSBL3 costs about RMB 1, and it could reduce the P concentration in 2.6 ton of Laoyu River water to below the eutrophication threshold; and the inhibitory effect of MSBL3 on the eutrophication of water bodies was confirmed by the growth state of water hyacinth. Furthermore, 0.1 M MSBL3 could inhibit Escherichia coli and Staphylococcus aureus up to 98.7% and 85.0%, respectively, which indicates that MSBL3 can be used to recover P from water and also to improve water quality. In addition, the growth of the maize seedlings verified that the P-absorbed MSBL3 waste is a good soil fertilizer and can solve the problem of post-treatment of the adsorbent. In conclusion, MSBL3 prepared in this study is a promising P sorbent for application.Graphical

High-Precision Characterization of Seismicity from the 2022 Hunga Tonga-Hunga Ha'apai Volcanic Eruption

AbstractThe earthquake swarm accompanying the January 2022 Hunga Tonga-Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate-magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera-forming eruptions. We compute improved epicentroid locations, magnitudes, and regional moment tensors of seismic events from this earthquake swarm using regional to teleseismic surface-wave cross correlation and waveform modeling. Precise relative locations of 91 seismic events derived from 59,047 intermediate-period Rayleigh- and Love-wave cross-correlation measurements collapse into a small area surrounding the volcano and exhibit a southeastern time-dependent migration. Regional moment tensors and observed waveforms indicate that these events have a similar mechanism and exhibit a strong positive compensated linear vector dipole component. Precise relative magnitudes agree with regional moment tensor moment magnitude (Mw) estimates while also showing that event sizes and frequency increase during the days after the eruption followed by a period of several weeks of less frequent seismicity of a similar size. The combined information from visual observation and early geologic models indicate that the observed seismicity may be the result of a complex series of events that occurred after the explosive eruption on 15 January, possibly involving rapid resupply of the magma chamber shortly after the eruption and additional faulting and instability in the following weeks. In addition, we identify and characterize an Mw 4.5 event five days before the paroxysmal explosion on 15 January, indicating that additional seismic events preceding the main eruption could have been identified with improved local monitoring. Our analysis of the HTHH eruption sequence demonstrates the value of potentially utilizing teleseismic surface-wave cross correlation and waveform modeling methods to assist in the detailed analysis of remote volcanic eruption sequences.

A General Neural Network Model for Complex Refractive Index Extraction of Low-Loss Materials in the Transmission-Mode THz-TDS

The complex refractive index for low-loss materials is conventionally extracted by either approximate analytical formula or numerical iterative algorithm (such as Nelder-Mead and Newton-Raphson) based on the transmission-mode terahertz time domain spectroscopy (THz-TDS). A novel 4-layer neural network model is proposed to obtain optical parameters of low-loss materials with high accuracy in a wide range of parameters (frequency and thickness). Three materials (TPX, z-cut crystal quartz and 6H SiC) with different dispersions and thicknesses are used to validate the robustness of the general model. Without problems of proper initial values and non-convergence, the neural network method shows even smaller errors than the iterative algorithm. Once trained and tested, the proposed method owns both high accuracy and wide generality, which will find application in the multi-class object detection and high-precision characterization of THz materials.

Bent Crystal Design and Characterization for High-Energy Physics Experiments

Bent crystal are widely used as optics for X-rays, but via the phenomenon of planar channeling they may act as waveguide for relativistic charged particles beam as well, outperforming some of the traditional technologies currently employed. A physical description of the phenomenon and the resulting potential for applications in a particle accelerator is reported. The elastic properties of the anisotropic crystal lattice medium are discussed, introducing different types of curvature which can enable a wide array of bending schemes optimized for each different case features. The technological development of machining strategy and bending solutions useful for the fabrication of crystals suitable in high energy particle manipulations are described. As well as the high precision characterization processes developed in order to satisfy the strict requirements for installation in an accelerator. Finally, the characterization of channeling phenomenon in bent crystal is described, pointing out several experimental setups suitable to comply each specific case constrains.

A 16nm All-Digital Hardware Monitor for Evaluating Electromigration Effects in Signal Interconnects Through Bit-Error-Rate Tracking

The impact of Electromigration (EM) on the Bit-Error-Rate (BER) of signal interconnect paths was experimentally examined. An array-based test-vehicle for tracking Bit-Error-Rate (BER) degradation of signal interconnects subject to Direct-Current (DC) EM stress was implemented in a 16nm FinFET process. A unit interconnect path comprises five identical interconnect stages where each wire is driven by inverter based buffers. Accelerated EM stress testing is achieved entirely on-chip using metal heaters located directly above the devices-under-test (DUTs) and separate stress circuits driving both ends of the wire. The proposed test structure features a ring-based Voltage-Controlled-Oscillator (VCO), a bit-pattern generator and local BER sampling monitors which enable bitwise tracking of ‘0’ and ‘1’ errors separately, further simplifying the overall test-setup and allowing for high precision characterization of EM induced resistance shifts using only digital circuits. Measurement data collected from the 16nm prototype reveals unique insights into EM induced signal path degradation that was not available prior to this work. Our experimental studies suggest that monitoring the BER of an interconnect path could be used as a new metric for capturing EM induced resistance shifts in a real system, in lieu of the conventional approach which focuses on monitoring standalone wire resistances. Supplemental simulations showcasing the projected degradation in the interconnect path operating frequency as a function of stress time constructed from resistance traces sampled from identical wires implemented in the same process reaffirm the measurement trends.

Influence of Mesh Density on Repeatability of FSW Process Simulation Based on DEFORM

To solve the problem of the relative error caused by mesh density is difficult to quantitatively evaluate, a process simulation model of FSW (friction stir welding) 2219 aluminum alloy is built based on DEFORM. Process simulation models with different mesh densities are solved, the influence of mesh density on simulation repeatability and time-consuming is analyzed, and the mesh density suitable for the process simulation model is determined. The evaluation method proposed offers a theoretical reference for the determination of local optimal mesh density of the FSW process simulation model based on DEFORM. This study provides a basis for high precision prediction and characterization of the temperature distribution of FSW on heavy-lift launch vehicle fuel tank.

Surface and Subsurface Quality Assessment of Polished Lu2O3 Single Crystal Using Quasi-Brewster Angle Technique

The sesquioxide Lu2O3 single crystal has attracted tremendous attention as potential host material for high-power solid-state lasers. As polishing is the terminal process of conventional ultra-precision machining, the quality of polished crystal directly impacts the crucial performance indicators of optics. The high melting point of Lu2O3 single crystal makes crystal preparation difficult. Therefore, investigations on the surface/subsurface quality inspection of polished Lu2O3 single crystal are scarce. In this paper, we utilize the quasi-Brewster angle technique (qBAT) based on ellipsometry to inspect the quality of polished Lu2O3 single crystal, achieving fast, non-destructive, and high-sensitive surface/subsurface damage assessment. A systematic crystal processing scheme is designed and polished Lu2O3 crystal samples are obtained. To verify the results of qBAT, the surface and subsurface quality are tested using optical profilometer and transmission electron microscope, respectively. The consistency of the test results demonstrates the feasibility, high sensitivity, and accuracy of the qBAT. To our knowledge, this is the first time that the qBAT is applied to investigate the polished surface/subsurface quality of Lu2O3 single crystal. In conclusion, this method provides a powerful approach to the high-precision characterization of the surface/subsurface quality of Lu2O3 single crystal, and has significant potential for material property study and process optimization during ultra-precision machining.

Improved Intra-Pixel Sensitivity Characterization Based on Diffusion and Coupling Model for Infrared Focal Plane Array Photodetector.

The high-precision characterization of the intra-pixel sensitivity (IPS) for infrared focal plane array (FPA) photodetector is of great significance to high-precision photometry and astrometry in astronomy, as well as target tracking in under-sampled remote sensing images. The discrete sub-pixel response (DSPR) model and fill factor model have been used for IPS characterization in some studies. However, these models are incomplete and lack the description of physical process of charge diffusion and capacitance coupling, leading to the inaccuracy of IPS characterization. In this paper, we propose an improved IPS characterization method based on the diffusion and coupling physical (DCP) model for infrared FPA photodetector, which considering the processes of generation and collection of the charge, can improve the accuracy of IPS characterization. The IPS model can be obtained by convolving the ideal rectangular response function with the charge diffusion function and the capacitive coupling function. Then, the IPS model is convolved with the beam spot profile to obtain the beam spot scanning response model. Finally, we calculate the parameters of IPS by fitting the beam spot scanning response map with the proposed DCP model based on the Trust-Region-Reflective algorithm. Simulated results show that when using a 3 μm beam spot to scan, the error of IPS characterization based on DCP model is 0.63%, which is better than that of DSPR model’s 3.70%. Experimental results show that the fitting error of the beam spot scan response model based on DCP model is 4.29%, which is better than that of DSPR model’s 8.31%.

Optical properties of large-size and damage-free polished Lu2O3 single crystal covering the ultraviolet-visible-and near-infrared (UV–VIS–NIR) spectral region

Lu2O3 has attracted widespread attention in high-power lasers, scintillators, and semiconductors due to its high thermal conductivity, high stability, and large band gap. Due to the limitations of the growth process, high-precision characterization of polished quality and optical properties for large-size Lu2O3 single crystal is extremely scarce, which hinders the design and optimization of optics based on Lu2O3. In this study, we design a systematic machining scheme for large-size Lu2O3 single crystal thick chip to obtain polished crystal with virtually no surface and subsurface damage. The surface/subsurface quality was evaluated utilizing optical profilometer, scanning electron microscope, and transmission electron microscope. Variable-angle spectroscopic ellipsometer was employed to measure the optical constants over wide spectral region (210–1690 nm), removing the lack of optical constants of Lu2O3 single crystal in the ultraviolet region. The band gap is analyzed based on the optical constants results. The consistency of the measured data with the relevant literature verifies the reliability and accuracy of the measurement method along with the data. The surface/subsurface damage inspection method provides an effective approach for ultra-precision machining mechanism research and process optimization of Lu2O3 and other hard and brittle materials. The band gap and the optical constants in wide spectral region provide critical fundamental data for the design and performance optimization of related optics.

KASP: a genotyping method to rapid identification of resistance in Plasmodium falciparum

BackgroundThe emergence and spread of anti-malarial resistance continues to hinder malaria control. Plasmodium falciparum, the species that causes most human malaria cases and most deaths, has shown resistance to almost all known anti-malarials. This anti-malarial resistance arises from the development and subsequent expansion of Single Nucleotide Polymorphisms (SNPs) in specific parasite genes. A quick and cheap tool for the detection of drug resistance can be crucial and very useful for use in hospitals and in malaria control programmes. It has been demonstrated in different contexts that genotyping by Kompetitive Allele Specific PCR (KASP), is a simple, fast and economical method that allows a high-precision biallelic characterization of SNPs, hence its possible utility in the study of resistance in P. falciparum.MethodsThree SNPs involved in most cases of resistance to the most widespread anti-malarial treatments have been analysed by PCR plus sequencing and by KASP (C580Y of the Kelch13 gene, Y86N of the Pfmdr1 gene and M133I of the Pfcytb gene). A total of 113 P. falciparum positive samples and 24 negative samples, previously analysed by PCR and sequencing, were selected for this assay. Likewise, the samples were genotyped for the MSP-1 and MSP-2 genes, and the Multiplicity of Infection (MOI) and parasitaemia were measured to observe their possible influence on the KASP method.ResultsThe KASP results showed the same expected mutations and wild type genotypes as the reference method, with few exceptions that correlated with very low parasitaemia samples. In addition, two cases of heterozygotes that had not been detected by sequencing were found. No correlation was found between the MOI or parasitaemia and the KASP values of the sample. The reproducibility of the technique shows no oscillations between repetitions in any of the three SNPs analysed.ConclusionsThe KASP assays developed in this study were efficient and versatile for the determination of the Plasmodium genotypes related to resistance. The method is simple, fast, reproducible with low cost in personnel, material and equipment and scalable, being able to core KASP arrays, including numerous SNPs, to complete the main pattern of mutations associated to P. falciparum resistance.

Manufacturing and Characterization of Hybrid Bulk Voxelated Biomaterials Printed by Digital Anatomy 3D Printing.

The advent of 3D digital printers has led to the evolution of realistic anatomical organ shaped structures that are being currently used as experimental models for rehearsing and preparing complex surgical procedures by clinicians. However, the actual material properties are still far from being ideal, which necessitates the need to develop new materials and processing techniques for the next generation of 3D printers optimized for clinical applications. Recently, the voxelated soft matter technique has been introduced to provide a much broader range of materials and a profile much more like the actual organ that can be designed and fabricated voxel by voxel with high precision. For the practical applications of 3D voxelated materials, it is crucial to develop the novel high precision material manufacturing and characterization technique to control the mechanical properties that can be difficult using the conventional methods due to the complexity and the size of the combination of materials. Here we propose the non-destructive ultrasound effective density and bulk modulus imaging to evaluate 3D voxelated materials printed by J750 Digital Anatomy 3D Printer of Stratasys. Our method provides the design map of voxelated materials and substantially broadens the applications of 3D digital printing in the clinical research area.

Gene-Environment Interaction in the Era of Precision Medicine - Filling the Potholes Rather Than Starting to Build a New Road.

Gene–environment interaction is a key part of evolutionary biology, animal, and plant breeding, and a number of health sciences, like epidemiology and precision medicine. However, bottlenecks in models of gene–environment interaction have recently been made manifest, particularly in the field of medicine and, consequently, specific improvements have been explicitly requested—namely, an implementation of gene–environment interaction satisfactorily disentangled from gene–environment correlation. The present paper meets those demands by providing mathematical developments that implement classical models of genetic effects and bring them up to date with the prospects current available data bestow. These developments are shown to overcome the limitations of previous proposals through the analysis of illustrative examples on disease susceptibility, with special attention paid to precision medicine. Indeed, a number of misconceptions about the application of models of genetic/environmental effects to precision medicine are here identified and clarified. The theory here provided is argued to strengthen, in particular, the methodology required for high-precision characterization of strain virulence in the study of the COVID-19 pandemic.

Design and Optimisation of a Three Layers Thermal Neutron, Fast Neutron and Gamma-Ray Imaging System

The design and configuration of a multi-layered imaging system with the ability to detect thermal neutrons, fast neutrons and gamma rays has been developed and its efficacy demonstrated. The work presented here numerically determines the systems efficiency and spatial resolution, using 252Cf and 137Cs as a case study. The novelty of this detection system lies in the use of small form factor detectors in a three-layer design, which utilises neutron elastic scattering and Compton scattering simultaneously. The current configuration consists of 10 mm thick natural lithium glass (GS10) scintillator integrated with a 20 mm thick plastic scintillator (EJ-204) in the first layer, a 15 mm thick lithium glass (GS10) scintillator in the second and a 30 mm thick CsI(Tl) scintillator forming the final layer. Each of these layers is backed with an 8 x 8 silicon photomultiplier diode (SiPM) array. The overall size of the imaging system is 27 mm x 27 mm x 135 mm. MCNPv6.1 and Geant4-10.04 were alternatively used to optimise the overall configuration and to investigate detection modalities. Results show promising performance with high precision source localisation and characterization abilities. Measurements were virtually obtained of two gamma-ray sources within steel enclosures at angles of 15°, 30° and 50° separation in order to test spatial resolution ability of the system. With the current active size of the system and the 8x8 SiPM configuration, the results estimate the spatial resolution to be close to 30°. The ability of the system to characterise and identify sources based on the type and energy of the radiation emitted, has been investigated and results show that for all radiation types the system can identify the source energy within the energy range of typical reported sources in literature.

Applying Machine Learning to Nanoindentation Data of (Nano-) Enhanced Composites

Carbon fiber reinforced polymers (CFRPs) are continuously gaining attention in aerospace and space applications, and especially their multi-scale reinforcement with nanoadditives. Carbon nanotubes (CNTs), graphene, carbon nanofibers (CNFs), and their functionalized forms are often incorporated into interactive systems to engage specific changes in the environment of application to a smart response. Structural integrity of these nanoscale reinforced composites is assessed with advanced characterization techniques, with the most prominent being nanoindentation testing. Nanoindentation is a well-established technique, which enables quantitative mapping of nanomechanical properties with the μm surficial and nm indentation resolution scale and high precision characterization. This feature enables the characterization of the interface in a statistical and quantitative manner and the correlation of (nano-) reinforcement to interface properties of CFRPs. Identification of reinforcement is performed with k-Nearest Neighbors and Support Vector Machine classification algorithms. Expertise is necessary to describe the physical problem and create representative training/testing datasets. Development of open source Machine Learning algorithms can have an influential impact on uniformity of nanometry data creation and management. The statistical character of nanoindentation is a key factor to supply information on heterogeneity of multiscale reinforced composites. Both the identification of (nano-) reinforcement and quality assessment of composites are provided by involving artificial intelligence.

Performance Analysis of a Reduced Form-Factor High Accuracy Three-Axis Teslameter

In the framework of the SwissFEL project at the Paul Scherrer Institute (PSI), a Hall probe bench is being developed for the high-precision magnetic characterization of the insertion devices for the ATHOS soft X-ray beamline. For this purpose, a novel three-axis teslameter has been developed, which will be placed between the undulator and its outer shell in a very limited volumetric space of 150 x 50 x 45 mm. Together with a Hall probe at the center of the cross sectional area of the undulator, the setup will traverse along the undulator length on a specifically designed rig with minimal vibrations. This teslameter has all the analog signal conditioning circuitry for the Hall probe and also has on board 24-bit digitization. The instrument also handles an interface to a linear absolute encoder. The old instrumentation used only had analog signal conditioning circuitry whilst digitization was done off board. The new instrument also provides a very accurate magnetic field map in the µT range with simultaneous readings from the position encoder at an accuracy of ±3 µm. In this paper, a series of tests are described, which were performed at PSI in order to establish the measuring precision and repeatability of the instrument.