Liquid Argon Research Articles

Performance of Hamamatsu VUV4 SiPMs for detecting liquid argon scintillation

Detection of light signals is crucial to a wide range of particle detectors. In particular, efficient detection of vacuum ultraviolet (VUV) light will provide new opportunities for some novel detectors currently being developed, but is technically challenging. In this article, we characterized the performance of Hamamatsu VUV4 silicon photomultipliers (SiPMs) for detecting VUV argon scintillation light without wavelength shifting. Using a customized cryogenic amplifier design, we operated two models of VUV4 SiPMs inside liquid argon and thoroughly examined their direct sensitivities to liquid argon scintillation. In addition to describing their cryogenic performance, we measured a photon detection efficiency of 14.7+1.1 -2.4% and 17.2+1.6 -3.0% at 128 nm for these two VUV4 models for operation at 4 V of overvoltage, with the main uncertainty arising from the SiPM reflectivity for VUV light.

Machine learning for real-time processing of ATLAS liquid argon calorimeter signals with FPGAs

The ATLAS experiment at CERN measures energy of proton-proton (p-p) collisions with a repetition frequency of 40 MHz at the Large Hadron Collider (LHC). The readout electronics of liquid-argon (LAr) calorimeters are being prepared for high luminosity-LHC (HL-LHC) operation as part of the phase-II upgrade, anticipating a pileup of up to 200 simultaneous p-p interactions. The increase of the number of p-p interactions implies that calorimeter signals of up to 25 consecutive collisions overlap, making energy reconstruction more challenging. In order to achieve the goal of the HL-HLC, field-programmable gate arrays (FPGAs) are used to process digitized pulses sampled at 40 MHz in real time and different machine learning approaches are being investigated to deal with signal pileup. The convolutional and recurrent neural networks outperform the optimal signal filter currently in use, both in terms of assigning the reconstructed energy to the correct proton bunch crossing and in terms of energy resolution. The enhancements are focused on energy obtained from overlapping pulses. Because the neural networks are implemented on an FPGA, the number of parameters, resource usage, latency and operation frequency must be carefully analysed. A very good agreement is observed between neural network implementations in FPGA and software.

Molecular dynamics study on enhanced nucleate boiling heat transfer on nanostructured surfaces with rectangular cavities

Nanostructured surfaces have been proved to bring remarkable enhancements in nucleate boiling heat transfer, which are particularly attractive in thermal energy fields. To fully understand the effects of nano-cavities on nucleate boiling and elucidate the underlying enhanced mechanisms, a comparative molecular dynamics study on nucleate pool boiling heat transfer of liquid argon over the plain copper substrate and nanostructured substrates with different rectangular cavities is performed. The nano-cavities have the same depth of 5 nm and different widths of 3 nm, 5 nm and 8 nm. The bubble dynamics behavior on various surfaces is observed based on simulation snapshots. The results manifest that the rectangular nano-cavity can significantly reduce time and wall superheat required for the onset of nucleate boiling, as well as delay the transition from nucleation boiling regime to film boiling regime. The incipient nucleation time tin can be reduced to 990 ps from 5600 ps. Additionally, compared with the plain substrate, the rectangular nano-cavity can result in a striking decrease in boiling initiation temperature, which is up to 59 K. The underlying enhanced mechanisms are well elucidated based on the structural feature of the rectangular nano-cavity and simulation results. The liquid inside the rectangular cavity can obtain additional thermal energy from sidewalls, leading to a significant local heat accumulation effect and the heat transfer efficiency reinforcement. It is found there is a coupling enhancement effect of heat accumulation when the width of rectangular cavity is smaller. Consequently, the 3 nm wide nano-cavity can achieve maximum enhancement. These findings provide crucial evidence at the nanoscale to verify that nano-cavity can significantly enhance nucleate boiling not only by reducing nucleation time but also by decreasing the boiling initiation temperature. This study is of importance to promote further insights into the enhanced mechanism of nucleate boiling at the nanoscale and provide guidance for the performance improvement in boiling surfaces for advanced thermal energy systems.

A study of events with photoelectric emission in the DarkSide-50 liquid argon Time Projection Chamber

Finding unequivocal evidence of dark matter interactions in a particle detector is a major goal of research in physics. Liquid argon time projection chambers offer a path to probe Weakly Interacting Massive Particles scattering cross sections on nuclei down to the so-called neutrino floor, in a mass range from a few GeV to hundreds of TeV. Based on the successful operation of the DarkSide-50 detector at LNGS, a new and more sensitive experiment, DarkSide-20k, has been designed and is now under construction. A thorough understanding of the DarkSide-50 detector response and, therefore, of all types of events observed in the detector, is essential for the optimal design of the new experiment. In this article, we report on a specific set of events, namely, standard two-pulse scintillation–ionization signals with a third small amplitude pulse, occurring within the 440μs data acquisition window of standard events. Some of these events are due to the photoionization of the TPC cathode. We compare our results with those published by collaborations using liquid xenon time projection chambers, which observed a similar phenomenon, and, in particular, with a recent paper by the LUX Collaboration (D.S. Akerib et al. Phys.Rev.D 102, 092004 (2020)) From the measured rate of these events, we estimate for the first time the quantum efficiency of the tetraphenyl butadiene deposited on the DarkSide-50 cathode at wavelengths of around 128 nm, in liquid argon. Also, both experiments observe events likely related to the photoionization of impurities in the liquid. The probability of photoelectron emission per unit length turns out to be an order of magnitude lower in DarkSide-50 than in LUX.

Freezing Temperature and Density Scaling of Transport Coefficients.

It is demonstrated that the freezing density scaling of transport coefficients in fluids, similar to the freezing temperature scaling, originates from the quasi-universal excess entropy scaling approach proposed by Rosenfeld. The freezing density scaling has a considerably wider applicability domain on the phase diagram of Lennard-Jones and related systems. As an illustration of its predictive power, we show that it reproduces with an excellent accuracy the shear viscosity coefficients of saturated liquid argon, krypton, xenon, and methane.

First measurement of inclusive electron-neutrino and antineutrino charged current differential cross sections in charged lepton energy on argon in MicroBooNE

We present the first measurement of the single-differential $\nu_e + \bar{\nu}_e$ charged-current inclusive cross sections on argon in electron or positron energy and in electron or positron scattering cosine over the full angular range. Data were collected using the MicroBooNE liquid argon time projection chamber located off-axis from the Fermilab Neutrinos at the Main Injector beam over an exposure of $2.0\times10^{20}$ protons on target. The signal definition includes a 60 MeV threshold on the $\nu_e$ or $\bar{\nu}_e$ energy and a 120 MeV threshold on the electron or positron energy. The measured total and differential cross sections are found to be in agreement with the GENIE, NuWro, and GiBUU neutrino generators.

Neutrino up-scattering via the dipole portal at forward LHC detectors

The significant neutrino flux at high rapidity at the LHC motivates dedicated forward detectors to study the properties of neutrinos at TeV energies. We investigate magnetic dipole interactions between the active neutrinos and new sterile states at emulsion and liquid argon experiments that could be located in a future Forward Physics Facility (FPF) downstream of the ATLAS interaction point. The up-scattering of neutrinos off electrons produces an electron recoil signature that can probe new regions of parameter space at the High Luminosity LHC (HL-LHC), particularly for liquid argon detectors due to low momentum thresholds. We also consider the decay of the sterile neutrino through the dipole operator, which leads to a photon that could be displaced from the production vertex. FPF detectors can test sterile neutrino states as heavy as 1 GeV produced through the dipole portal, highlighting the use of high energy LHC neutrinos as probes of new physics.

Detecting long-lived particles trapped in detector material at the LHC

We propose a two-stage strategy to search for new long-lived particles that could be produced at the CERN LHC, become trapped in detector material, and decay later. In the first stage, metal rods are exposed to LHC collisions in an experimental cavern. In the second stage, they are immersed in liquid argon at a different location, where out-of-time decays could be detected. Using a benchmark of pair-produced long-lived gluinos, we show that this experiment would have unique sensitivity to gluino-neutralino mass splittings down to 3 GeV, in previously uncovered lifetimes of days to years.

Photon detection probability prediction using one-dimensional generative neural network

Photon detection is important for liquid argon detectors for direct dark matter searches or neutrino property measurements. Precise simulation of photon transport is widely used to understand the probability of photon detection in liquid argon detectors. Traditional photon transport simulation, which tracks every photon using the Geant4 simulation toolkit, is a major computational challenge for kilo-tonne-scale liquid argon detectors and GeV-level energy depositions. In this work, we propose a one-dimensional generative model which efficiently generates features using an -layer. This model bypasses photon transport simulation and predicts the number of photons detected by particular photon detectors at the same level of detail as the Geant4 simulation. The application to simulating photon detection systems in kilo-tonne-scale liquid argon detectors demonstrates this novel generative model is able to reproduce Geant4 simulation with good accuracy and 20 to 50 times faster. This generative model can be used to quickly predict photon detection probability in huge liquid argon detectors like ProtoDUNE or DUNE.

Techniques for TPC Calibration: Application to Liquid Ar-TPCs

Large liquid argon TPCs are playing an increasingly important role in neutrino physics, and their calibration will be an essential component of their capability to reach the required performance and precision. Natural sources are extensively used but present limitations, since natural radioactivity from 39Ar is of low energy, and the rate of cosmic ray muons is low when the detectors are placed deep underground. Argon gas TPCs have been calibrated with ionizing laser beams for several decades, and more recently the technique has been further developed for use in liquid TPCs. Other recent ideas include the use of external neutron generators creating pulses that propagate into the detector. This paper reviews the development of the laser and neutron methods for the calibration of argon TPCs and describes their planned implementation in the upcoming DUNE experiment.

Experimental Study of the Positive Ion Feedback from Gas to Liquid in a Dual-Phase Argon Chamber and Measurement of the Ion Mobility in Argon Gas

The dynamics of the positive ions created by particle interactions inside argon time projection chambers plays an important role in characterizing the next generation of massive detectors planned for the direct search for dark matter and the study of neutrino properties. We have constructed a 1 L liquid argon chamber (ARION: ARgon ION experiment) with a high voltage pulse generator capable of injecting, in a controlled manner, a sizeable ion current into the drift region. This chamber is capable of reproducing a volume charge similar to that found in large detectors, allowing its effects to be studied systematically. New experimental results regarding ion dynamics in the liquid and direct demonstration of ion feedback from the gas to the liquid are discussed in this paper. In addition, a novel technique to measure the drift velocity of argon ions is introduced along with preliminary results obtained in gas.

Determination of the Frequency Dispersion Region of the Transport Coefficients of Classical Liquids Depending on the Character of Attenuation of Relaxing Flows

We consider the frequency dispersion region of the dynamic shear viscosity coefficient ηs (ω) of simple liquids obtained by the method of kinetic equations, where the equilibrium structure of a liquid is restored according to the diffusion law or exponentially. At a certain choice of the intermolecular interaction potential Φ (|r|) and the equilibrium radial distribution function g0 (|r|), the coefficient ηs (ω) for liquid argon was numerically calculated as a function of the density ρ, temperature T, and frequency ω. The obtained theoretical values of the shear viscosity ηs (ω) are in a satisfactory quantitative agreement with experimental data. It is shown that the frequency dispersion region of ηs (ω) obtained on the basis of the diffusive mechanism, i.e. structural relaxation, is large (~ 105 Hz). In the case of the exponential attenuation of the viscous stress tensor, this region is narrow (~ 102 Hz), which agrees both with acoustic measurements and the results of a phenomenological theory.

Novel approach for the study of coherent elastic neutrino-nucleus scattering

We propose the use of isotopically highly enriched detectors for the precise study of coherent-elastic neutrino-nucleus scattering (CEvNS). CEvNS has been measured for the first time in CsI and recently confirmed with a liquid argon detector. It is expected that several new experimental setups will measure this process with increasing accuracy. Taking Ge detectors as a working example, we demonstrate that a combination of different isotopes is an excellent option to do precision neutrino physics with CEvNS, test Standard Model predictions, and probe new physics scenarios. Experiments based on this new idea can make simultaneous differential CEvNS measurements with detectors of different isotopic composition. Particular combination of observables could be used to cancel systematic errors. While many applications are possible, we illustrate the idea with three examples: testing the dominant quadratic dependence on the number of neutrons, $N$, that is predicted by the theoretical models; constraining the average neutron root mean square (rms) radius; and testing the weak mixing angle and the sensitivity to new physics. In all three cases we find that the extra sensitivity provided by this method will potentially allow high-precision robust measurements with CEvNS and particularly, will resolve the characteristic degeneracies appearing in new physics scenarios.

Design and performance of the GERDA low-background cryostat for operation in water

In searching for the neutrinoless double-beta decay of 76Ge the GERmanium Detector Array (Gerda) experiment at the Infn Laboratori Nazionali del Gran Sasso has achieved an unprecedented low background of well below 10-3 cts/(keV·kg·yr) in the region of interest. It has taken advantage of the first realization of a novel shielding concept based on a large cryostat filled with a liquid noble gas that is immersed in a water tank. The germanium detectors are operated without encapsulation in liquid argon. Argon and water shield the environmental background from the laboratory and the cryostat construction materials to a negligible level. The same approach has been adopted in the meantime by various experiments. This paper provides an overview of the design and the operation experience of the 64 m3 liquid argon cryostat and its associated infrastructure. The discussion inludes the challenging safety issues associated with the operation of a large cryostat in a water tank.

Convolutional neural networks for shower energy prediction in liquid argon time projection chambers

When electrons with energies of O(100) MeV pass through a liquid argon time projection chamber (LArTPC), they deposit energy in the form of electromagnetic showers. Methods to reconstruct the energy of these showers in LArTPCs often rely on the combination of a clustering algorithm and a linear calibration between the shower energy and charge contained in the cluster. This reconstruction process could be improved through the use of a convolutional neural network (CNN). Here we discuss the performance of various CNN-based models on simulated LArTPC images, and then compare the best performing models to a typical linear calibration algorithm. We show that the CNN method is able to address inefficiencies caused by unresponsive wires in LArTPCs and reconstruct a larger fraction of imperfect events to within 5 % accuracy compared with the linear algorithm.

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

Molecular dynamics perspective of condensation over a hybrid wetting surface

ABSTRACT The aim of the present study is to investigate relative effect of philic/phobic fraction and philic–phobic patterning on nanoscale condensation over a hybrid wetting surface through molecular dynamics simulations. A three-phase Argon–Platinum system has been considered, where the argon atoms are bounded by the two Platinum (Pt) surfaces. Initially a liquid argon layer is placed on the bottom Platinum surface and the rest of the simulation domain is filled with argon vapour. Following necessary equilibration, the temperature of the bottom surface is rised to induce evaporation, while that of the top surface with hybrid wetting characteristics is maintained at equilibration temperature to tempt condensation. Variation in hybrid wetting condition of the condensing wall is assumed by changing the relative percentage of philic/phobic portion and the size of philic–phobic pattern strip. It has been found that a higher amount of argon atoms is condensed in cases with higher hydrophilic contents. Also, for a fixed philic–phobic fraction, a smaller strip size of philic–phobic patterning results in faster condensation. Early-stage condensation, i.e. nucleation and subsequent condensate growth mode has been distinctive and related to the distribution of local liquid–vapour interfacial surface tension near the condensing wall for different hybrid wetting conditions.

Molecular Dynamics Study on the Combined Effects of the Nanostructure and Wettability of Solid Surfaces on Bubble Nucleation

In this paper, molecular dynamics (MD) simulations are conducted to investigate the bubble nucleation process of liquid argon on surfaces with a nanostructure of different wettabilities. To account for the combined effects of the nanostructure and surface wettability on bubble nucleation, the variation of the bubble volume, the nucleation starting time, as well as the heat flux between the solid surface and fluid are examined. It is found that the position of bubble nucleation depends on the pillar wettability. Bubble nucleation occurs in the bulk of fluid when the pillar is hydrophilic, while it occurs on the pillar surface when the pillar is hydrophobic. Under an integrated influence of the free-energy barrier of nucleation and heat transfer, the nucleation occurs later as the wettability of the pillar gets weaker over surfaces with the hydrophilic pillar, while it occurs earlier as the wettability of the pillar gets weaker over surfaces with the hydrophobic pillar. Moreover, the peak heat flux decreases with the decrease of the pillar wettability over surfaces with the hydrophilic pillar, while it increases with the decrease of the pillar wettability over surfaces with the hydrophobic pillar, which can be explained from the perspective of the heat transfer efficiency and the timing of phase change occurrence. Finally, a new surface with mixed-wettable pillars is proposed, which is verified to be conducive to both bubble nucleation and heat transfer.

Rb83/Kr83m production and cross-section measurement with 3.4 MeV and 20 MeV proton beams

$^{83m}\mathrm{Kr}$, with a short lifetime, is an ideal calibration source for liquid xenon or liquid argon detectors. The $^{83m}\mathrm{Kr}$ isomer can be generated through the decay of the $^{83}\mathrm{Rb}$ isotope, which is usually produced by proton beams bombarding natural krypton atoms. In this paper, we report a successful production of $^{83}\mathrm{Rb}/^{83m}\mathrm{Kr}$ with a proton beam energy of 3.4 MeV, and the first measurement of the production rate with such low-energy proton beams. Another production attempt is performed using the newly available 20 MeV proton beam in China, and the measured production rate is consistent with previous measurements. The produced $^{83m}\mathrm{Kr}$ source has been successfully injected into the PandaX-II liquid xenon detector, yielding enough statistics for detector calibration.

Scintillation and optical properties of xenon-doped liquid argon

Liquid argon (LAr) is a common choice as detection medium in particle physics and rare-event searches. Challenges of LAr scintillation light detection include its short emission wavelength, long scintillation time and short attenuation length. The addition of small amounts of xenon to LAr is known to improve the scintillation and optical properties. We present a characterization campaign on xenon-doped liquid argon (XeDLAr) with target xenon concentrations ranging from 0 to 300 ppm by mass encompassing the measurement of the photoelectron yield Y, effective triplet lifetime τ 3 and effective attenuation length λ att. The measurements were conducted in the Subterranean Cryogenic ARgon Facility, Scarf, a 1 t (XeD)LAr test stand in the shallow underground laboratory (UGL) of TU-Munich. These three scintillation and optical parameters were observed simultaneously with a single setup, the Legend Liquid Argon Monitoring Apparatus, Llama. The actual xenon concentrations in the liquid and gaseous phases were determined with the Impurity DEtector For Investigation of Xenon, Idefix, a mass spectrometer setup, and successful doping was confirmed. At the highest dopant concentration we find a doubling of Y, a tenfold reduction of τ 3 to ∼90 ns and a tenfold increase of λ att to over 6 m.