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Results for “Process sensitivity”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A beamline for ultrafast extreme ultraviolet magneto-optical spectroscopy in reflection near the shot noise limit

High harmonic generation (HHG) makes it possible to measure spin and charge dynamics in materials on femtosecond to attosecond timescales. However, the extreme nonlinear nature of the high harmonic process means that intensity fluctuations can limit measurement sensitivity. Here we present a noise-canceled, tabletop high harmonic beamline for time-resolved reflection mode spectroscopy of magnetic materials. We use a reference spectrometer to independently normalize the intensity fluctuations of each harmonic order and eliminate long term drift, allowing us to make spectroscopic measurements near the shot noise limit. Here, these improvements allow us to significantly reduce the integration time required for high signal-to-noise (SNR) measurements of element-specific spin dynamics. Looking forward, improvements in the HHG flux, optical coatings, and grating design can further reduce the acquisition time for high SNR measurements by 1–2 orders of magnitude, enabling dramatically improved sensitivity to spin, charge, and phonon dynamics in magnetic materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Using Separation-Enhanced Isotope Ratio Mass Spectrometry

Stable isotope ratio measurements using IRMS have been shown by LANL to be effective for tracking co-processed biogenic carbon, with results approaching that of AMS. The lower cost of an IRMS may enable deployment to refineries improving access and analysis turnaround times (≤ 2-hours), and by extension data that can allow process optimization to maximize renewable carbon in desired refinery products. This work will apply chemical separation approaches as part of the IRMS analyses, enabling biogenic carbon tracking in fuel product streams by boiling point range, by chemical class, or even by compound. This work will show IRMS to be at a minimum as reliable and comparable to AMS, by using separations to improve sensitivity at low blend ratios and enable refinery process optimization through onsite analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Novel Mode of Photoprotection Mediated by a Cysteine Residue in the Chlorophyll Protein IsiA

Oxygenic photosynthetic organisms have evolved a multitude of mechanisms for protection against high-light stress. IsiA, a chlorophyll a-binding cyanobacterial protein, serves as an accessory antenna complex for photosystem I. Intriguingly, IsiA can also function as an independent pigment protein complex in the thylakoid membrane and facilitate the dissipation of excess energy, providing photoprotection. The molecular basis of the IsiA-mediated excitation quenching mechanism remains poorly understood. In this study, we demonstrate that IsiA uses a novel cysteine-mediated process to quench excitation energy. The single cysteine in IsiA in the cyanobacterium Synechocystis sp. strain PCC 6803 was converted to a valine. Ultrafast fluorescence spectroscopic analysis showed that this single change abolishes the excitation energy quenching ability of IsiA, thus providing direct evidence of the crucial role of this cysteine residue in energy dissipation from excited chlorophylls. Under stress conditions, the mutant cells exhibited enhanced light sensitivity, indicating that the cysteine-mediated quenching process is critically important for photoprotection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An Electrical Resistance Diagnostic for Conductivity Monitoring in Laser Powder Bed Fusion

With the growing interest in metal additive manufacturing using laser powder bed fusion (LPBF), there is a need for advanced in-situ nondestructive evaluation (NDE) methods that can dynamically monitor manufacturing process-related variations, that can be used as a feedback mechanism to further improve the manufacturing process, leading to parts with improved microstructural properties and mechanical properties. Current NDE techniques either lack sensitivity beyond build layer, are costly or time-consuming, or are not compatible for in-situ integration. In this research, we develop an electrical resistance diagnostic for in-situ monitoring of powder fused regions during laser powder bed fusion printing. The technique relies on injecting current into the build plate and detecting voltage differences from conductive variations during printing using a simple, cheap four-point electrode array directly connected to the build plate. A computational model will be utilized to determine sensitivities of the approach, and preliminary experiments will be performed during the printing process to test the overall approach.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A multi-stage stochastic programming model for adaptive biomass processing operation under uncertainty

Variations of physical and chemical characteristics of biomass reduce equipment utilization and increase operational costs of biomass processing. Biomass processing facilities use sensors to monitor the changes in biomass characteristics. Integrating sensory data into the operational decisions in biomass processing will increase its flexibility to the changing biomass conditions. In this paper, we propose a multi-stage stochastic programming model that minimizes the expected operational costs by identifying the initial inventory level and creating an operational decision policy for equipment speed settings. These policies take the sensory information data and the current biomass inventory level as inputs to dynamically adjust inventory levels and equipment settings according to the changes in the biomass' characteristics. We ensure that a prescribed target reactor utilization is consistently achieved by penalizing the violation of the target reactor feeding rate. A case study is developed using real-world data collected at Idaho National Laboratory's biomass processing facility. We show the value of multi-stage stochastic programming from an extensive computational experiment. Our sensitivity analysis indicates that updating the infeed rate of the system, the processing speed of equipment, and bale sequencing based on the moisture level of biomass improves the processing rate of the reactor and reduces operating costs.

09 BIOMASS FUELS↗
DOE OSTI2024

Transitory sensitivity in automatic chemical kinetic mechanism analysis

Abstract Detailed chemical kinetic mechanisms are necessary for resolving many important chemical processes. As the chemistry of smaller molecules has become better grounded and quantum chemistry calculations have become cheaper, kineticists have become interested in constructing progressively larger kinetic mechanisms to model increasingly complex chemical processes. These large kinetic mechanisms prove incredibly difficult to refine and time‐consuming to interpret. Traditional sensitivity analysis on a large mechanism can range from inconvenient to practically impossible without special techniques to reduce the computational cost. We first present a new time‐local sensitivity analysis we term transitory sensitivity analysis. Transitory sensitivity analysis is demonstrated in an example to accurately identify traditionally sensitive reactions at an 18,000x speed up over traditional sensitivities. By fusing transitory sensitivity analysis with more traditional time‐local branching, pathway, and cluster analyses, we develop an algorithm for efficient automatic mechanism analysis. This automatic mechanism analysis at a time point is able to identify the reactions a target is most sensitive to using transitory sensitivity analysis and then propose hypotheses why the reaction might be sensitive using branching, pathway, and cluster analyses. We implement these algorithms within the reaction mechanism simulator (RMS) package, which enables us to report the automatic mechanism analysis results in highly readable text formats and in molecular flux diagrams.

Johnson, Matthew S.↗
DOE OSTI2023

A combination interferometric and morphological image processing approach to rapid quality assessment of additively manufactured cellular truss core components

Advanced manufacturing (AM) processes such as laser powder bed fusion (LPBF) are increasingly capable of fabricating components with useful and unprecedented mechanical properties by incorporating complex internal bracing structures. From the standpoint of quality control and assessment, however, internally complex assemblies present significant build-verification challenges. Here we propose a hybrid approach to the inspection involving the application of computer-aided speckle interferometry (CASI) and morphological image processing as a rapid, inexpensive, and facile method for AM quality control. The described methodology has low capital equipment costs, is full-field and non-contact, can be used in an industrial setting, and has very low requirements in terms of operator training and expertise. Consisting primarily of the combination of image processing software with a simple optical system of variable sensitivity, the method is shown to be effective for inspection of a titanium honeycomb component subjected to differential pressure. Results are compared to those achieved with computed tomography (CT), immersion ultrasound testing (UT), and optical holographic interferometry. Here we propose several possible processing strategies for automated quality assessment based on this powerful hybrid approach.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dehalogenation reactions between halide salts and phosphate compounds

Reactions between phosphoric acid [H 3 PO 4 ] or ammonium hydrogen phosphates [i.e., NH 4 H 2 PO 4 , (NH 4 ) 2 HPO 4 ] and halide salts can be used to dehalogenate (remove halides from) salt-based waste streams, where the process of removing halides yields products that have more efficient disposal pathways for repository storage. In this context, the term efficiency is defined as higher waste loadings and simplified immobilization processes with potential for recycle of certain salt components (e.g., 37 Cl as H 37 Cl or NH 4 37 Cl). The main streams identified for these processes are nuclear wastes generated during electrochemical reprocessing of used nuclear fuel as well as used halide salts from molten salt reactor operation. The potential byproducts of these reactions are fairly consistent across the range of halide species (i.e., F, Cl, Br, I) where the most common are hydrogen halides [e.g., HCl (g) ] or ammonium halides (e.g., NH 4 Cl). However, trihalide compounds (e.g., NCl 3 ), nitrogen triiodide ammine adducts [NI 3 ·(NH 3 ) x ], and ammonium triiodide (NH 4 I 3 ) are also possible. Several of these byproducts (i.e., NCl 3 , NBr 3 , NI 3 , and NH 4 I 3 ) are shock-sensitive contact explosives so their production in these processes must be tracked and carefully controlled, which includes methods of immediate neutralization upon production such as direct transport to a caustic scrubber for dissolution. Several benefits arise from utilizing H 3 PO 4 as the phosphate additive during dehalogenation reactions for making iron phosphate waste forms including more oxidized iron (higher Fe 3+ :Fe 2+ ratios), higher chemical durabilities, and the avoidance of trihalides, but the byproducts are hydrogen halides, which are corrosive and require special handling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗
DOE OSTI2022

EUCLID Sensitivity Database

This report documents the EUCLID sensitivity database along with its several use-cases. EUCLID computed sensitivities for the following integral responses: Criticality of ICSBEP critical assemblies, LLNL pulsed-sphere neutron-leakage spectra, reaction rates in selected ICBSEP critical assemblies, delayed neutron factions of selected ICSBEP critical assemblies, reactivity coefficients in two ICSBEP critical assemblies, sub-critical assembly responses and Rossi-alpha of selected critical assemblies. It is described for each response what the reported observable constitutes, the method we used to obtain the sensitivities, and which integral experiments were studied. It is also documented briefly in what format these sensitivities are stored. These sensitivities were used for many aspects of the EUCLID project, like ML-supported large-scale nuclear-data validation, or optimization of integral experiments. But these sensitivities can also be applied for more established processes in the nuclear-data application field such as adjustment or assessing the upper sub-critical limit.

Delayed Neutron Fraction↗
DOE OSTI2022

Integrating Data From In Vitro New Approach Methodologies for Developmental Neurotoxicity

Abstract In vivo developmental neurotoxicity (DNT) testing is resource intensive and lacks information on cellular processes affected by chemicals. To address this, DNT new approach methodologies (NAMs) are being evaluated, including: the microelectrode array neuronal network formation assay; and high-content imaging to evaluate proliferation, apoptosis, neurite outgrowth, and synaptogenesis. This work addresses 3 hypotheses: (1) a broad screening battery provides a sensitive marker of DNT bioactivity; (2) selective bioactivity (occurring at noncytotoxic concentrations) may indicate functional processes disrupted; and, (3) a subset of endpoints may optimally classify chemicals with in vivo evidence for DNT. The dataset was comprised of 92 chemicals screened in all 57 assay endpoints sourced from publicly available data, including a set of DNT NAM evaluation chemicals with putative positives (53) and negatives (13). The DNT NAM battery provides a sensitive marker of DNT bioactivity, particularly in cytotoxicity and network connectivity parameters. Hierarchical clustering suggested potency (including cytotoxicity) was important for classifying positive chemicals with high sensitivity (93%) but failed to distinguish patterns of disrupted functional processes. In contrast, clustering of selective values revealed informative patterns of differential activity but demonstrated lower sensitivity (74%). The false negatives were associated with several limitations, such as the maximal concentration tested or gaps in the biology captured by the current battery. This work demonstrates that this multi-dimensional assay suite provides a sensitive biomarker for DNT bioactivity, with selective activity providing possible insight into specific functional processes affected by chemical exposure and a basis for further research.

Carstens, Kelly E.↗
DOE OSTI2022

Comprehensive Analysis of the Neutrino Process in Core-collapsing Supernovae

We investigate the neutrino flavor change effects due to neutrino self-interaction and shock wave propagation, as well as the matter effects on the neutrino process in core-collapsing supernovae (CCSNe). For the hydrodynamics, we use two models: a simple thermal bomb model and a specified hydrodynamics model for SN1987A. For the presupernova model, we take an updated model, adjusted to explain SN1987A, which employs recent developments in the (n, γ) reaction rates for nuclei near the stability line (A ~ 100). As for the neutrino luminosity, we adopt two different models: equivalent neutrino luminosity and nonequivalent luminosity models. The latter is taken from a synthetic analysis of CCSN simulation data, which quantitatively presented the results obtained by various neutrino transport models. Relevant neutrino-induced reaction rates are calculated using a shell model for light nuclei and a quasiparticle random phase approximation model for heavy nuclei. For each model, we present abundances of the light nuclei ( 7 Li, 7 Be, 11 B, and 11 C) and the heavy nuclei ( 92 Nb, 98 Tc, 138 La, and 180 Ta) produced by the neutrino process. The light nuclei abundances turn out to be sensitive to the Mikheyev–Smirnov–Wolfenstein (MSW) region around O-Ne-Mg layer while the heavy nuclei are mainly produced prior to the MSW region. Through detailed analyses, we find that neutrino self-interaction becomes a key ingredient, in addition to the MSW effect, for understanding the neutrino process and the relevant nuclear abundances. The normal mass hierarchy is shown to be more compatible with the meteorite data. The main nuclear reactions for each nucleus are also investigated in detail.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Alpha-decay induced shortening of fission tracks simulated by in situ ion irradiation

The diffusion of defects (e.g., vacancies and interstitials) and elements used for dating (e.g., He and Pb) in a mineral structure is a thermal process: This is the primary assumption used to determine the age and thermal history of minerals. For instance, thermal history reconstruction, through the number and length distribution of tracks produced by spontaneous fission of 238 U, is obtained by assuming a thermal event to be the only energy source for shortening of fission tracks. Here, we report a new, non-thermal energy source that induces additional shortening of fission tracks by the irradiation of alpha-recoils from the alpha-decay of 238 U and 232 Th. We simulate alpha-decay induced track-shortening by combining ion accelerator irradiations with transmission electron microscopy. This allows for the first observation of track-shrinkage during in situ ion irradiation. We show that rather than alpha-particles, alpha-recoils induce a significant shortening of fission tracks by nuclear-collisions. The shortening of track-length can be quantified as a function of alpha-decay event dose. However, apatite is less sensitive than zircon to this non-thermal process. Furthermore, the findings exemplify the interactions among different types of self-irradiation from alpha-particles, alpha-recoils and fission-fragment nuclei in single mineral grains and have important implications for the use of zircon and apatite for radiometric dating and thermochronology.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Bipolar Membrane Capacitive Deionization for pH-Assisted Ionic Separations

Selective ionic separations represent an increasingly important technical area for the strategic interests of the U.S. economy–for example, securing critical minerals and materials and circular economy aspirations that include recovering organic acids from processed biomass. This work disseminates bipolar membrane (BPM) capacitive deionization for selective ionic separations from multicomponent, ionic species mixtures. The selective separations are guided by the Pourbaix diagram and acid–base equilibria principles. BPM capacitive deionization was demonstrated to generate alkaline or acidic process streams depending upon the location of the BPM in the electrochemical cell. The role of system operating parameters, such as the cell voltage, residence time, and feed concentration on effluent stream pH was studied. It was observed that the pH adjustment in BPM-CDI/MCDI (MCDI, membrane capacitive deionization) was more sensitive to the cell voltage when compared to the process stream residence time and salt feed concentration. The BPM-MCDI gave over 6 times higher percentage of copper(II) removal when compared to sodium ion removal from brine mixtures. Lastly, BPM-MCDI demonstrated over 40% greater removal for copper ions from brine mixtures and fivefold higher removal for itaconic acid from brine mixtures when benchmarked against a traditional flow-by-MCDI setup.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Re-evaluating cloud chamber constraints on depositional ice growth in cirrus clouds – Part 1: Model description and sensitivity tests

Abstract. Ice growth from vapor deposition is an important process for the evolution of cirrus clouds, but the physics of depositional ice growth at the low temperatures (<235 K) characteristic of the upper troposphere and lower stratosphere is not well understood. Surface attachment kinetics, generally parameterized as a deposition coefficient αD, control ice crystal habit and also may limit growth rates in certain cases, but significant discrepancies between experimental measurements have not been satisfactorily explained. Experiments on single ice crystals have previously indicated the deposition coefficient is a function of temperature and supersaturation, consistent with growth mechanisms controlled by the crystal's surface characteristics. Here we use observations from cloud chamber experiments in the Aerosol Interactions and Dynamics in the Atmosphere (AIDA) aerosol and cloud chamber to evaluate surface kinetic models in realistic cirrus conditions. These experiments have rapidly changing temperature, pressure, and ice supersaturation such that depositional ice growth may evolve from diffusion limited to surface kinetics limited over the course of a single experiment. In Part 1, we describe the adaptation of a Lagrangian parcel model with the Diffusion Surface Kinetics Ice Crystal Evolution (DiSKICE) model (Zhang and Harrington, 2014) to the AIDA chamber experiments. We compare the observed ice water content and saturation ratios to that derived under varying assumptions for ice surface growth mechanisms for experiments simulating ice clouds between 180 and 235 K and pressures between 150 and 300 hPa. We found that both heterogeneous and homogeneous nucleation experiments at higher temperatures (>205 K) could generally be modeled consistently with either a constant deposition coefficient or the DiSKICE model assuming growth on isometric crystals via abundant surface dislocations. Lower-temperature experiments showed more significant deviations from any depositional growth model, with different ice growth rates for heterogeneous and homogeneous nucleation experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme

Abstract. An earlier study evaluating dust life cycle in the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1) has revealed that the simulated global mean dust lifetime is substantially shorter when higher vertical resolution is used, primarily due to significant strengthening of dust dry removal in source regions. This paper demonstrates that the sequential splitting of aerosol emissions, dry removal, and turbulent mixing in the model's time integration loop, especially the calculation of dry removal after surface emissions and before turbulent mixing, is the primary reason for the vertical resolution sensitivity reported in that earlier study. Based on this reasoning, we propose a revised numerical process coupling scheme that requires the least amount of code changes, in which the surface emissions are applied before turbulent mixing instead of before dry removal. The revised scheme allows newly emitted particles to be transported aloft by turbulence before being removed from the atmosphere, and hence better resembles the dust life cycle in the real world. Sensitivity experiments show that the revised process coupling substantially weakens dry removal and strengthens vertical mixing in dust source regions. It also strengthens the large-scale transport from source to non-source regions, strengthens dry removal outside the source regions, and strengthens wet removal and activation globally. In transient simulations of the years 2000–2009 conducted using 1∘ horizontal grid spacing, 72 vertical layers, and unchanged tuning parameters of emission strength, the revised process coupling leads to a 40 % increase in the global total dust burden and an increase of dust lifetime from 1.8 to 2.5 d in terms of 10-year averages. Weakened dry removal and increased mixing ratios are also seen for other aerosol species that have substantial surface emissions, although the changes in mixing ratio are considerably smaller for the submicron species than for dust and sea salt. Numerical experiments confirm that the revised coupling scheme significantly reduces the strong and non-physical sensitivities of model results to vertical resolution in the original EAMv1. This provides a motivation for adopting the revised scheme in EAM as well as for further improvements on the simple revision presented in this paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Investigating the eco‐evolutionary response of microbiomes to environmental change

Abstract Microorganisms are the primary engines of biogeochemical processes and foundational to the provisioning of ecosystem services to human society. Free‐living microbial communities (microbiomes) and their functioning are now known to be highly sensitive to environmental change. Given microorganisms' capacity for rapid evolution, evolutionary processes could play a role in this response. Currently, however, few models of biogeochemical processes explicitly consider how microbial evolution will affect biogeochemical responses to environmental change. Here, we propose a conceptual framework for explicitly integrating evolution into microbiome–functioning relationships. We consider how microbiomes respond simultaneously to environmental change via four interrelated processes that affect overall microbiome functioning (physiological acclimation, demography, dispersal and evolution). Recent evidence in both the laboratory and the field suggests that ecological and evolutionary dynamics occur simultaneously within microbiomes; however, the implications for biogeochemistry under environmental change will depend on the timescales over which these processes contribute to a microbiome's response. Over the long term, evolution may play an increasingly important role for microbially driven biogeochemical responses to environmental change, particularly to conditions without recent historical precedent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Characterization of the First Prototype of the L1K65n Differential-Output Charge-Sensitive Preamplifier ASIC for High-Performance, Low-Background HPGe Detector Readout

Next-generation neutrinoless double-beta (0νββ) decay searches require a large detector/isotope mass and very low radioactive backgrounds. The upcoming LEGEND-1000 experiment (Large Enriched Germanium Experiment for Neutrinoless double-beta Decay) constitute a ton-scale array of several hundred high-purity germanium (HPGe) detectors enriched in 76Ge, the isotope of interest. It aims to reach a sensitivity beyond 10 28 years on the 0νββ decay half-life of 76Ge, necessitating an order of magnitude reduction in background with respect to the state of the art. This will require the implementation of a dedicated application specific integrated circuit (ASIC) preamplifier that will significantly lower background contribution compared to the conventional low-mass front end (LMFE) employed in the Majorana Demonstrator and LEGEND-200 experiments while maintaining or improving energy resolution and other performance parameters. Features include a high (9 MeV) dynamic range with noise low enough to achieve a trigger threshold of <1 keV, a single power supply to reduce background-inducing cabling, and a differential output to maintain signal integrity over several meters of transmission line. The chip would be optimized to operate in liquid argon (87 K) and be able to do so reliably for ten years. Following on from an earlier 180-nm prototype, we have developed a differential-output charge-sensitive preamplifier ASIC fabricated in a 65-nm process, 1×2 mm in size, that addresses these needs. Here, we present recent results from the successful testing and characterization of the first version of this device.

ASIC↗