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At least 721 records · Page 40

Impact of LHC vector boson production in heavy ion collisions on strange PDFs

Abstract The extraction of the strange quark parton distribution function (PDF) poses a long-standing puzzle. Measurements from neutrino-nucleus deep inelastic scattering (DIS) experiments suggest the strange quark is suppressed compared to the light sea quarks, while recent studies of $$W^\pm /Z$$ W ± / Z boson production at the LHC imply a larger strange component at small x values. As the parton flavor determination in the proton depends on nuclear corrections, e.g. from heavy-target DIS, LHC heavy ion measurements can provide a distinct perspective to help clarify this situation. In this investigation we extend the nCTEQ15 nPDFs to study the impact of the LHC proton-lead $$W^\pm /Z$$ W ± / Z production data on both the flavor differentiation and nuclear corrections. This complementary data set provides new insights on both the LHC $$W^\pm /Z$$ W ± / Z proton analyses and the neutrino-nucleus DIS data. We identify these new nPDFs as nCTEQ15WZ . Our calculations are performed using a new implementation of the nCTEQ code ( nCTEQ++ ) based on C++ which enables us to easily interface to external programs such as HOPPET, APPLgrid and MCFM. Our results indicate that, as suggested by the proton data, the small x nuclear strange sea appears larger than previously expected, even when the normalization of the $$W^{\pm }/Z$$ W ± / Z data is accommodated in the fit. Extending the nCTEQ15 analysis to include LHC $$W^\pm /Z$$ W ± / Z data represents an important step as we advance toward the next generation of nPDFs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A computational pipeline to generate a synthetic dataset of metal ion sorption to oxides for AI/ML exploration

The charged mineral/electrolyte interfaces are ubiquitous in the surface and subsurface–including the surroundings of the geological disposal sites for radioactive waste. Therefore, understanding how ions interact with charged surfaces is critically important for predicting radionuclide mobility in the case of waste leakage. At present, the Surface Complexation Models (SCMs) are the most successful thermodynamic frameworks to describe ion retention by mineral surfaces. SCMs are interfacial speciation models that account for the effect of the electric field generated by charged surfaces on sorption equilibria. These models have been successfully used to analyze and interpret a broad range of experimental observations including potentiometric and electrokinetic titrations or spectroscopy. Unfortunately, many of the current procedures to solve and fit SCM to experimental data are not optimal, which leads to a non-transferable or non-unique description of interfacial electrostatics and consequently of the strength and extent of ion retention by mineral surfaces. Recent developments in Artificial Intelligence (AI) offer a new avenue to replace SCM solvers and fitting algorithms with trained AI surrogates. Unfortunately, there is a lack of a standardized dataset covering a wide range of SCM parameter values available for AI exploration and training–a gap filled by this study. Here, we described the computational pipeline to generate synthetic SCM data and discussed approaches to transform this dataset into AI-learnable input. First, we used this pipeline to generate a synthetic dataset of electrostatic properties for a broad range of the prototypical oxide/electrolyte interfaces. The next step is to extend this dataset to include complex radionuclide sorption and complexation, and finally, to provide trained AI architectures able to infer SCMs parameter values rapidly from experimental data. Here, we illustrated the AI-surrogate development using the ensemble learning algorithms, such as Random Forest and Gradient Boosting. These surrogate models allow a rapid prediction of the SCM model parameters, do not rely on an initial guess, and guarantee convergence in all cases.

Li, Chunhui↗

Battery system management through non-linear estimation of battery state of charge

Systems, methods, and computer media for battery system management and non-linear estimation of battery state of charge are provided herein. Battery data is received for a time period over which a battery system has operated. The battery data represents the actual performance of the battery system over the time period. Sub-periods of charging or discharging can be identified in the time period. For the sub-periods of time, a curve can be fit to the battery data. Using the curves for the battery data for the sub-periods of time, an expected performance of the battery system, over a range of states-of-charge, can be determined. Operating instructions for the battery system can be provided based on the expected performance.

25 ENERGY STORAGE↗

Battery system management through non-linear estimation of battery state of charge

Systems, methods, and computer media for battery system management and non-linear estimation of battery state of charge are provided herein. Battery data is received for a time period over which a battery system has operated. The battery data represents the actual performance of the battery system over the time period. Sub-periods of charging or discharging can be identified in the time period. For the sub-periods of time, a curve can be fit to the battery data. Using the curves for the battery data for the sub-periods of time, an expected performance of the battery system, over a range of states-of-charge, can be determined. Operating instructions for the battery system can be provided based on the expected performance.

Crawford, Alasdair James↗

Predicting Open Quantum Dynamics with Data-Informed Quantum-Classical Dynamics

We introduce a data-informed quantum-classical dynamics (DIQCD) approach for predicting the evolution of an open quantum system. The equation of motion in DIQCD is a Lindblad equation with a flexible, time-dependent Hamiltonian that can be optimized to fit sparse and noisy data from local observations of an extensive open quantum system. We demonstrate the accuracy and efficiency of DIQCD for both experimental and simulated quantum devices. We show that DIQCD can predict entanglement dynamics of ultracold molecules (calcium fluoride) in optical tweezer arrays. DIQCD also successfully predicts carrier mobility in organic semiconductors (rubrene) with accuracy comparable to nearly exact numerical methods.

Lindblad equation↗

Mathematical modeling of hepatitis C RNA replication, exosome secretion and virus release

Hepatitis C virus (HCV) causes acute hepatitis C and can lead to life-threatening complications if it becomes chronic. The HCV genome is a single plus strand of RNA. Its intracellular replication is a spatiotemporally coordinated process of RNA translation upon cell infection, RNA synthesis within a replication compartment, and virus particle production. While HCV is mainly transmitted via mature infectious virus particles, it has also been suggested that HCV-infected cells can secrete HCV RNA carrying exosomes that can infect cells in a receptor independent manner. In order to gain insight into these two routes of transmission, we developed a series of intracellular HCV replication models that include HCV RNA secretion and/or virus assembly and release. Fitting our models to in vitro data, in which cells were infected with HCV, suggests that initially most secreted HCV RNA derives from intracellular cytosolic plus-strand RNA, but subsequently secreted HCV RNA derives equally from the cytoplasm and the replication compartments. Furthermore, our model fits to the data suggest that the rate of virus assembly and release is limited by host cell resources. Including the effects of direct acting antivirals in our models, we found that in spite of decreasing intracellular HCV RNA and extracellular virus concentration, low level HCV RNA secretion may continue as long as intracellular RNA is available. This may possibly explain the presence of detectable levels of plasma HCV RNA at the end of treatment even in patients that ultimately attain a sustained virologic response.

59 BASIC BIOLOGICAL SCIENCES↗

Cosmology intertwined: A review of the particle physics, astrophysics, and cosmology associated with the cosmological tensions and anomalies

The standard Λ Cold Dark Matter (ΛCDM) cosmological model provides a good description of a wide range of astrophysical and cosmological data. However, there are a few big open questions that make the standard model look like an approximation to a more realistic scenario yet to be found. In this paper, we list a few important goals that need to be addressed in the next decade, taking into account the current discordances between the different cosmological probes, such as the disagreement in the value of the Hubble constant H 0 , the σ 8 – S 8 tension, and other less statistically significant anomalies. While these discordances can still be in part the result of systematic errors, their persistence after several years of accurate analysis strongly hints at cracks in the standard cosmological scenario and the necessity for new physics or generalisations beyond the standard model. In this paper, we focus on the 5.0 σ tension between the Planck CMB estimate of the Hubble constant H 0 and the SH0ES collaboration measurements. After showing the H 0 evaluations made from different teams using different methods and geometric calibrations, we list a few interesting new physics models that could alleviate this tension and discuss how the next decade's experiments will be crucial. Moreover, we focus on the tension of the Planck CMB data with weak lensing measurements and redshift surveys, about the value of the matter energy density Ω m , and the amplitude or rate of the growth of structure ( σ 8 , f σ 8 ). We list a few interesting models proposed for alleviating this tension, and we discuss the importance of trying to fit a full array of data with a single model and not just one parameter at a time. Additionally, we present a wide range of other less discussed anomalies at a statistical significance level lower than the H 0 – S 8 tensions which may also constitute hints towards new physics, and we discuss possible generic theoretical approaches that can collectively explain the non-standard nature of these signals. Finally, we give an overview of upgraded experiments and next-generation space missions and facilities on Earth that will be of crucial importance to address all these open questions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Power-law inflation satisfies Penrose’s Weyl curvature hypothesis

Based on entropy considerations and the arrow of time Penrose argued that the Universe must have started in a special initial singularity with vanishing Weyl curvature. This is often interpreted to be at odds with inflation. Here we argue just the opposite, that Penrose’s persuasions are in fact consistent with inflation. Using the example of power law inflation, we show that inflation begins with a past null singularity, where Weyl tensor vanishes when the metric is initially exactly conformally flat. This initial state precisely obeys Penrose’s conditions. The initial null singularity breaks T-reversal spontaneously and picks the arrow of time. It can be regulated and interpreted as a creation of a universe from nothing, initially fitting in a bubble of Planckian size when it materializes. Penrose’s initial conditions are favored by the initial O(4) symmetry of the bubble, selected by extremality of the regulated Euclidean action. The predicted observables are marginally in tension with the data, but they can fit if small corrections to power law inflation kick in during the last 60⁢e-folds.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal hydraulic characteristics of liquid sodium and supercritical CO 2 in a diffusion bonded heat exchanger

Compact heat exchangers are being examined for use in advanced, high-temperature nuclear or concentrated solar power plants to improve thermal efficiencies and reduce capital costs. At the time of this work, no experimental investigation of liquid sodium in the popular diffusion-bonded heat exchanger design had been performed. Herein this paper describes the thermal-hydraulic and overall operations performance observed during testing of a 316/L stainless steel “zig-zag” microchannel heat exchanger operating between a (0.5 kg/s) sodium loop and a (0.3 kg/s) recuperated supercritical CO 2 system with outlet conditions up to 550 °C at 16 MPa. Observed pressure drop is presented in the form of an effective friction factor correlation which aligns closely with recent experimental data. The thermal performance of this heat exchanger, measured by its overall conductance under various flow conditions, was decomposed to examine the independent convection behaviors of both the CO 2 and sodium streams. These results are presented in the form of Nusselt correlations fitted to the experimental data. The sodium heat transfer correlation aligns closely with the widely accepted Lubarsky-Kaufman correlation, while the CO 2 heat transfer correlation lies between previous correlations developed by computational and experimental methods. This was the first long-duration use of sodium in a microchannels (~1.8 mm hydraulic diameter) heat exchanger. The use of an oxide control system enabled trouble-free operation of the heat exchanger for over 150 h of high-temperature operation. This first-of-a-kind demonstration using liquid sodium and supercritical carbon dioxide shows great promise for further application of this technology in advanced nuclear or solar power plants.

42 ENGINEERING↗

Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning

Unmanned aerial vehicles (UAV) carrying multispectral cameras are increasingly being used for high-throughput phenotyping (HTP) of above-ground traits of crops to study genetic diversity, resource use efficiency and responses to abiotic or biotic stresses. There is significant unexplored potential for repeated data collection through a field season to reveal information on the rates of growth and provide predictions of the final yield. Generating such information early in the season would create opportunities for more efficient in-depth phenotyping and germplasm selection. This study tested the use of high-resolution time-series imagery (5 or 10 sampling dates) to understand the relationships between growth dynamics, temporal resolution and end-of-season above-ground biomass (AGB) in 869 diverse accessions of highly productive (mean AGB = 23.4 Mg/Ha), photoperiod sensitive sorghum. Canopy surface height (CSM), ground cover (GC), and five common spectral indices were considered as features of the crop phenotype. Spline curve fitting was used to integrate data from single flights into continuous time courses. Random Forest was used to predict end-of-season AGB from aerial imagery, and to identify the most informative variables driving predictions. Improved prediction of end-of-season AGB (RMSE reduction of 0.24 Mg/Ha) was achieved earlier in the growing season (10 to 20 days) by leveraging early- and mid-season measurement of the rate of change of geometric and spectral features. Early in the season, dynamic traits describing the rates of change of CSM and GC predicted end-of-season AGB best. Late in the season, CSM on a given date was the most influential predictor of end-of-season AGB. The power to predict end-of-season AGB was greatest at 50 days after planting, accounting for 63% of variance across this very diverse germplasm collection with modest error (RMSE 1.8 Mg/ha). End-of-season AGB could be predicted equally well when spline fitting was performed on data collected from five flights versus 10 flights over the growing season. This demonstrates a more valuable and efficient approach to using UAVs for HTP, while also proposing strategies to add further value.

54 ENVIRONMENTAL SCIENCES↗

Substructure at High Speed. I. Inferring the Escape Velocity in the Presence of Kinematic Substructure

Abstract The local escape velocity provides valuable inputs to the mass profile of the galaxy, and requires understanding the tail of the stellar speed distribution. Following Leonard & Tremaine, various works have since modeled the tail of the stellar speed distribution as ∝ ( v esc − v ) k , where v esc is the escape velocity, and k is the slope of the distribution. In such studies, however, these two parameters were found to be largely degenerate and often a narrow prior is imposed on k in order to constrain v esc . Furthermore, the validity of the power-law form can breakdown in the presence of multiple kinematic substructures or other mis-modeled features in the data. In this paper, we introduce a strategy that for the first time takes into account the presence of kinematic substructure. We model the tail of the velocity distribution as a sum of multiple power laws as a way of introducing a more flexible fitting framework. Using mock data and data from FIRE simulations of Milky Way-like galaxies, we show the robustness of this method in the presence of kinematic structure that is similar to the recently discovered Gaia Sausage. In a companion paper, we present the new measurement of the escape velocity and subsequently the mass of the Milky Way using Gaia eDR3 data.

79 ASTRONOMY AND ASTROPHYSICS↗

The Atacama Cosmology Telescope: DR4 maps and cosmological parameters

In this paper, we present new arcminute-resolution maps of the Cosmic Microwave Background temperature and polarization anisotropy from the Atacama Cosmology Telescope, using data taken from 2013–2016 at 98 and 150 GHz. The maps cover more than 17,000 deg 2 , the deepest 600 deg 2 with noise levels below 10µK-arcmin. We use the power spectrum derived from almost 6,000 deg 2 of these maps to constrain cosmology. The ACT data enable a measurement of the angular scale of features in both the divergence-like polarization and the temperature anisotropy, tracing both the velocity and density at last-scattering. From these one can derive the distance to the last-scattering surface and thus infer the local expansion rate, H 0 . By combining ACT data with large-scale information from WMAP we measure H 0 = 67.6±1.1 km/s/Mpc, at 68% confidence, in excellent agreement with the independently-measured Planck satellite estimate (from ACT alone we find H 0 = 67.9 ± 1.5 km/s/Mpc). The ΛCDM model provides a good fit to the ACT data, and we find no evidence for deviations: both the spatial curvature, and the departure from the standard lensing signal in the spectrum, are zero to within 1σ; the number of relativistic species, the primordial Helium fraction, and the running of the spectral index are consistent with ΛCDM predictions to within 1.5–2.2σ. We compare ACT, WMAP, and Planck at the parameter level and find good consistency; we investigate how the constraints on the correlated spectral index and baryon density parameters readjust when adding CMB large-scale information that ACT does not measure. The DR4 products presented here will be publicly released on the NASA Legacy Archive for Microwave Background Data Analysis.

60 APPLIED LIFE SCIENCES↗

Measurement of the W-boson mass and width with the ATLAS detector using proton–proton collisions at $\sqrt{s}=7$ TeV

Proton-proton collision data recorded by the ATLAS detector in 2011, at a centre-of-mass energy of 7 TeV, have been used for an improved determination of the W-boson mass and a first measurement of the W-boson width at the LHC. Recent fits to the proton parton distribution functions are incorporated in the measurement procedure and an improved statistical method is used to increase the measurement precision. The measurement of the W-boson mass yields a value of m w = 80,366.5 ± 9.8 (stat.) ± 12.5 (syst.) MeV = 80,366.5 ± 15.9 MeV, and the width is measured as Γ w = 2202 ± 32 (stat.) ± 34 (syst.) MeV = 2202 ± 47 MeV. The first uncertainty components are statistical and the second correspond to the experimental and physics-modelling systematic uncertainties. Both results are consistent with the expectation from fits to electroweak precision data. The present measurement of m w is compatible with and supersedes the previous measurement performed using the same data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Study of structural, transport and magneto-crystalline anisotropy in La 1-x Sr x MnO 3 (0.30 ≤ x ≤ 0.40) perovskite manganites

In this paper we present structural, transport, magnetic and magneto-crystalline anisotropy of La 1–x Sr x MnO 3 (х = 0.30, 0.33, 0.36, and 0.40) synthesized using the solid-state reaction method. The X-ray diffraction pattern of the samples is well indexed to the rhombohedral structure with R 3 - c space group. Lattice parameters and unit cell volume are found to decrease monotonically upon increasing Sr 2+ concentration at La 3+ site. X-ray photoelectron spectroscopy confirms the presence of Mn 4+ and Mn 3+ , the ratio of which (Mn 4+ /Mn 3+ ) increases from 0.44 to 0.64 with increasing Sr 2+ concentration. From the ρ(T) and M(T) data analysis, we find that T MI and M S are larger for x = 0.33 composition, suggesting a weakening of the double-exchange interaction due to competing super-exchange interactions in x = 0.30, 0.36 and 0.40 samples. We calculated MCA constant (K 1 ) by fitting the saturation magnetisation data at a higher magnetic field using the law of approach model, M = M S [1-a/H-b/H 2 ]-χH with K 1 2 = (105/8)bMs 2 and is in the order of 10 5 erg/cm 3 .

36 MATERIALS SCIENCE↗

Predicting Thermal Excursions During in situ Oxidative Regeneration of Packed Bed Catalytic Fast Pyrolysis Catalyst

Ex situ catalytic fast pyrolysis (CFP) uses a secondary reactor to upgrade biomass pyrolysis vapors to stabilized CFP oils with reduced oxygen content. In one configuration, the secondary reactor is operated as a packed-bed swing reactor system which allows coke-deactivated beds to be decarbonized in situ while other beds remain online for vapor upgrading. In situ decarbonization must be done carefully to avoid irreversible deactivation and/or physical degradation of catalyst pellets. Given that packed bed reactors are well known to have poor heat transfer characteristics, this is a critical issue impacting scaleability and commercial viability of the technology. To predict thermal excursions during regeneration, finite element computational models have been built to assist in scaling up oxidative decarbonization of a Pt/TiO2 CFP catalyst (0.5 mm spheres) from a bench scale packed bed with 100 g of catalyst to a pilot scale packed bed with 2 kg of catalyst and internal cooling tubes. Based on transient measurements of outlet temperature and effluent CO2 concentration, and using an assumed coke profile and activation energy, this paper demonstrates that specific combinations of effective thermal conductivity and wall heat transfer coefficient can fit bench scale oxidative regeneration data equally well. For the upscaled 2 kg bed, four bench-scale “best fit” parameter pairs give different predictions for location and magnitude of thermal excursions, with the maximum computed bed temperature gradients ranging from 30 °C cm-1 to as high as 3000 °C cm-1. The larger the fraction of heat removal by conduction through the cooling tubes, the greater the differences between the parameter pairs. The modelling results presented in this paper cast doubt on the industrial viability of the proposed combination of catalyst, bed and regeneration process, and point to the need for alternate reactor designs. However, there is considerable uncertainly in some of the key model parameters. The reliability of model predictions can be increased by adding more temperature measurements at key bed locations, testing additional variations in process conditions, performing careful bed dissections to determine the true coke profile, and perhaps most importantly, directly measuring the effective thermal conductivity of the catalyst pellets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamical model of J/ψ photoproduction on the nucleon

Here, a dynamical model based on a phenomenological charm quark-nucleon (c – N) potential v cN and the Pomeronexchange mechanism is constructed to investigate the J/ψ photoproduction on the nucleon from threshold to invariant mass W = 300 GeV. The J/ψ – N potential, V J/ψN (r), is constructed by folding v cN into the wave function φ J/ψ ($c\bar{c}$) of J/ψ within a constituent quark model (CQM) of Segovia et al. [Int. J. Mod. Phys. E 22, 1330026 (2013)]. A photoproduction amplitude is also generated by v cN by a $c\bar{c}$–loop integration over the γ → $c\bar{c}$ vertex function and φ J/ψ ($c\bar{c}$). No commonly used vector meson dominance assumption is used to define this photoproduction amplitude which is needed to describe the data near the threshold. The c – N potential v cN (r) is parameterized in a form such that the predicted V J/ψN (r) at large distances has the same Yukawa potential form extracted from a lattice QCD (LQCD) calculation of Kawanai and Sasaki, [Phys. Rev. D 82, 091501(R) (2010)]. The parameters of vcN are determined by fitting the total cross-section data of Jefferson Laboratory (JLab) by performing calculations that include J/ψ – N final-state interactions (FSI). The resulting differential cross sections dσ /dt are found in good agreements with the data. It is shown that the FSI effects dominate the cross section in the very near-threshold region, allowing for sensitive testing of the predicted J/ψ – N scattering amplitudes. By imposing the constraints of J/ψ – N potential extracted from the LQCD calculation of Kawanai and Sasaki, [Phys. Rev. D 82, 091501(R) (2010)], we have obtained three J/ψ – N potentials which fit the JLab data equally well. The resulting J/ψ – N scattering lengths are in the range of a = [-0.05, -0.25] fm. With the determined v cN (r) and the wave functions generated from the same CQM, the constructed model is used to predict the cross sections of photoproduction of η c (1S) and ψ(2S) mesons for future experimental tests.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis—nonadditive interactions between amino acid substitutions—and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable β-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences—a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

biocatalysis↗

Structural and magnetic characterization of CeTa 7 ⁢O 19 and YbTa 7 ⁢ O 19 with a two-dimensional pseudospin-$\frac{1}{2}$ triangular lattice

Triangular lattice antiferromagnets are prototypes for frustrated magnetism and may potentially realize novel quantum magnetic states such as a quantum spin-liquid ground state. A recent work suggests NdTa 7 ⁢O 19 with rare-earth triangular lattice is a quantum spin-liquid candidate and highlights the large family of rare-earth heptatantalates as a framework for quantum magnetism investigation. Here, in this paper, we report the structural and magnetic characterization of CeTa 7 ⁢ O 19 and YbTa 7 ⁢ O 19 . Both compounds are isostructural to NdTa 7 ⁢O 19 with no detectable structural disorder. For CeTa 7 ⁢O 19 , the crystal field energy levels and parameters are determined by inelastic neutron scattering measurements. Based on the crystal field result, the magnetic susceptibility data could be well fitted and explained, which reveals that CeTa 7 ⁢O 19 is a highly anisotropic Ising triangular-lattice antiferromagnet (𝑔 𝑧 ⁡/𝑔 𝑥⁢𝑦 ∼ 3) with very weak exchange interaction (J ∼ 0.22 K). For YbTa 7⁢ O 19 , millimeter-sized single crystals could be grown. The anisotropic magnetization and electron spin resonance data show that YbTa 7⁢ O 19 has a contrasting in-plane magnetic anisotropy with 𝑔 𝑧 ⁡/𝑔 𝑥⁢𝑦 ∼ 0.67 similar as that of YbMgGaO 4 . The above results indicate that CeTa7⁢ O 19 and YbTa 7 ⁢O 19 with pseudospin-1/2 ground states might either be quantum spin-liquid candidate materials or find applications in adiabatic demagnetization refrigeration due to the weak exchange interaction.

Pan, Feihao↗