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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Janus skyrmion: Interfacial quasiparticle with two-faced helicity

Janus particles are functional particles with at least two surfaces showing asymmetric properties. Here, we show at the interface between two magnetic regions with different antisymmetric exchange interactions, an alternative species of two-dimensional topological quasiparticles can emerge, in which different helicity structures can coexist. We name such an interfacial quasiparticle a “Janus skyrmion,” in analogy to the Janus particle. As the Janus skyrmion shows helicity asymmetry, its size could vary with both the in-plane and out-of-plane magnetic fields. A vertical spin current could drive the Janus skyrmion into one-dimensional motion along the interface without showing the skyrmion Hall effect, at a speed which depends on both the in-plane spin-polarization direction and current density. Thermal fluctuations could also lead to one-dimensional random walk of a Brownian Janus skyrmion. This work uncovers unique dynamics intrinsic to interfacial quasiparticles with exotic helicity, which may be realized in interface-engineered magnetic layers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

OLEDs on planarized light outcoupling-enhancing structures in plastic

Light extraction from OLEDs remains a challenge. While consumer demand for OLEDs in display technology continues to grow as prices decline, commercial use of OLEDs in solid state lighting (SSL) applications is lagging due to low light extraction, which results in low efficiency. Previous studies have been directed toward increasing the light extraction factor η out , but cost effective approaches that will enable high throughput and potential upscaling, as well as elucidation of the extraction process, are still lagging. One promising approach is the use of buried light extraction enhancing patterns that are planarized with a high refractive index (RI) layer. When adding substrate mode extracting means, the highest external quantum efficiencies (EQEs) were achieved using a complex approach of planarized vacuum nano holes. Here we present η out -enhancing planarized extraction structures (PES) in plastic. While plastic substrates currently present long-term stability issues and other drawbacks, as we show, they provide a tool for simple, inexpensive, and rapid generation of various enhancing structures that importantly can be transferred to the preferred rigid and flexible glass substrates. Moreover, plastic substrates are attractive for biomedical applications. The successful structures we present are easily scalable periodic corrugations, e.g., with pitch a ~ 4.25 µm and pitch/depth ratio a/h ~2.4 planarized by a layer of RI ~1.9, resulting in maximal EQEs exceeding 60% for a green OLED and 48.5% for a white OLED. Comparable increased EQEs were achieved for structures with a ~ 15 and 16 µm, and a/h ~ 2.1 and 4, respectively. Enhanced extraction was also observed with a very simply fabricated quasiperiodic nanohole array, and surprisingly, with a random shallow design. The latter is at variance with simulations based on diffraction only. Results are discussed in terms of a, h, and structural parameters together with scattering matrix simulations to assess the effect of various PES parameters and the nanoparticle-embedded planarizing layer on η out . The experiments and simulations indicate contributions of diffraction, reflection, and scattering to EQE enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Finite-temperature electron-capture rates for neutron-rich nuclei near N = 50 and effects on core-collapse supernova simulations

In this paper the temperature dependence of stellar electron-capture (EC) rates is investigated, with a focus on nuclei near N = 50, just above Z = 28, which play an important role during the collapse phase of core-collapse supernovae (CCSN). Two new microscopic calculations of stellar EC rates are obtained from relativistic and nonrelativistic finite-temperature quasiparticle random-phase approximation approaches, for a conventional grid of temperatures and densities. In both approaches, EC rates due to Gamow-Teller transitions are included. In the relativistic calculation, contributions from first-forbidden transitions are also included and add strongly to the EC rates. The new EC rates are compared with large-scale shell-model calculations for the specific case of 86 Kr, providing insight into the finite-temperature effects on the EC rates. At relevant thermodynamic conditions for core collapse, the discrepancies between the different calculations of this paper are within about one order of magnitude. Numerical simulations of CCSN are performed with the spherically symmetric gr1d simulation code to quantify the impact of such differences on the dynamics of the collapse. These simulations also include EC rates based on two parametrized approximations. A comparison of the neutrino luminosities and enclosed mass at core bounce shows that differences between simulations with different sets of EC rates are relatively small (≈ 5 %), suggesting that the EC rates used as inputs for these simulations have become well constrained.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

An alcove at the acetyl-CoA synthase nickel active site is required for productive substrate CO binding and anaerobic carbon fixation

One of the seven natural CO 2 fixation pathways, the anaerobic Wood-Ljungdahl pathway (WLP) is unique in generating CO as a metabolic intermediate, operating through organometallic intermediates, and in conserving (versus utilizing) net ATP. The key enzyme in the WLP is acetyl-CoA synthase (ACS), which uses an active site [2Ni-4Fe-4S] cluster (A-cluster), a CO tunnel, and an organometallic (Ni-CO, Ni-methyl, and Ni-acetyl) reaction sequence to generate acetyl-CoA. Here, we reveal that an alcove, which interfaces the tunnel and the A-cluster, is essential for CO 2 fixation and autotrophic growth by the WLP. In vitro spectroscopy, kinetics, binding, and in vivo growth experiments reveal that a Phe229A substitution at one wall of the alcove decreases CO affinity thirty-fold and abolishes autotrophic growth; however, a F229W substitution enhances CO binding 80-fold. Our results indicate that the structure of the alcove is exquisitely tuned to concentrate CO near the A-cluster; protect ACS from CO loss during catalysis, provide a haven for inhibitory CO, and stabilize the tetrahedral coordination at the Nip site where CO binds. The directing, concentrating, and protective effects of the alcove explain the inability of F209A to grow autotrophically. The alcove also could help explain current controversies over whether ACS binds CO and methyl through a random or ordered mechanism. Our work redefines what we historically refer to as the metallocenter "active site". The alcove is so crucial for enzymatic function that we propose it is part of the active site. The community should now look for such alcoves in all "gas handling" metalloenzymes.

bacterial metabolism↗
DOE OSTI2020

Near-Real-Time Forecast of Satellite-Based Soil Moisture Using Long Short-Term Memory with an Adaptive Data Integration Kernel

Nowcasts, or near-real-time (NRT) forecasts, of soil moisture based on the Soil Moisture Active and Passive (SMAP) mission could provide substantial value for a range of applications including hazards monitoring and agricultural planning. To provide such a NRT forecast with high fidelity, we enhanced a time series deep learning architecture, long short-term memory (LSTM), with a novel data integration (DI) kernel to assimilate the most recent SMAP observations as soon as they become available. The kernel is adaptive in that it can accommodate irregular observational schedules. Testing over the CONUS, this NRT forecast product showcases predictions with unprecedented accuracy when evaluated against subsequent SMAP retrievals. It showed smaller error than NRT forecasts reported in the literature, especially at longer forecast latency. The comparative advantage was due to LSTM’s structural improvements, as well as its ability to utilize more input variables and more training data. The DI-LSTM was compared to the original LSTM model that runs without data integration, referred to as the projection model here. We found that the DI procedure removed the autocorrelated effects of forcing errors and errors due to processes not represented in the inputs, for example, irrigation and floodplain/lake inundation, as well as mismatches due to unseen forcing conditions. The effects of this purely data-driven DI kernel are discussed for the first time in the geosciences. Furthermore, this work presents an upper-bound estimate for the random component of the SMAP retrieval error.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Limited effects of tannin supplementation on the dairy cattle fecal microbiome with modulation of metabolites

Tannins are plant secondary metabolites that bind organic carbon (C) and nitrogen (N), potentially altering substrate bioavailability for enteric fermentation in ruminants. This interaction may reduce greenhouse gas (GHG) emissions and influence nitrogen partitioning. Given tannins' resistance to ruminal degradation and persistence through the gastrointestinal tract, this study investigated the effects of a tannin-based feed additive on fecal microbial diversity, fecal chemical composition, and GHG emissions. Twenty-four early- to mid-lactation dairy cows were randomized to receive either a tannin-based feed additive (TRT; containing condensed and hydrolyzable tannins from Schinopsis quebracho-colorado [Schltdl.]) or a control diet (CON) for 64 days. Cows were blocked by parity, dry matter intake, milk yield, body weight, and days in milk. Fecal samples were collected on days 0, 16, 32, and 64 and analyzed using 16S rRNA gene amplicon sequencing. Fecal C, N, and indole-3-lactate were measured, and GHG emissions (N2O, CH4, CO2) were assessed via 14-day laboratory incubation. A total of 1,538 amplicon sequence variants were identified, with Firmicutes as the dominant phylum. Fecal phylogenetic diversity showed a significant treatment × day interaction (p < 0.01), with TRT cows exhibiting reduced microbial diversity from day 16 to 64. Fecal C and N concentrations were significantly lower (p < 0.01) in TRT cows on day 16, while indole-3-lactate levels were higher on day 64 (p = 0.02). GHG emissions did not differ significantly between treatments. The tannin-based feed additive influenced fecal microbial community structure and select chemical parameters but did not significantly affect GHG emissions from feces. These findings suggest that dietary tannins may modulate gut microbial ecology with minimal impact on downstream manure-related emissions.

Klein, Matthew L↗
DOE OSTI2023

Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment

The coronavirus disease 2019 (COVID-19) global pandemic resulted in millions of people becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and close to seven million deaths worldwide. It is essential to further explore and design effective COVID-19 treatment drugs that target the main protease of SARS-CoV-2, a major target for COVID-19 drugs. In this study, machine learning was applied for predicting the SARS-CoV-2 main protease binding of Food and Drug Administration (FDA)-approved drugs to assist in the identification of potential repurposing candidates for COVID-19 treatment. Ligands bound to the SARS-CoV-2 main protease in the Protein Data Bank and compounds experimentally tested in SARS-CoV-2 main protease binding assays in the literature were curated. These chemicals were divided into training (516 chemicals) and testing (360 chemicals) data sets. To identify SARS-CoV-2 main protease binders as potential candidates for repurposing to treat COVID-19, 1188 FDA-approved drugs from the Liver Toxicity Knowledge Base were obtained. A random forest algorithm was used for constructing predictive models based on molecular descriptors calculated using Mold2 software. Model performance was evaluated using 100 iterations of fivefold cross-validations which resulted in 78.8% balanced accuracy. The random forest model that was constructed from the whole training dataset was used to predict SARS-CoV-2 main protease binding on the testing set and the FDA-approved drugs. Model applicability domain and prediction confidence on drugs predicted as the main protease binders discovered 10 FDA-approved drugs as potential candidates for repurposing to treat COVID-19. Our results demonstrate that machine learning is an efficient method for drug repurposing and, thus, may accelerate drug development targeting SARS-CoV-2.

Research & Experimental Medicine↗
DOE OSTI2020

Investigation of countercurrent flow profile and liquid holdup in random packed column with local CFD data

Liquid holdup and mass transfer area are critical parameters used in packed column design and CO 2 capture efficiency prediction. Compared to experimental methods, 3D computational fluid dynamics (CFD) can provide high-resolution data for studying countercurrent flow hydrodynamics in a packed column. In this paper, a framework was established for modeling the liquid–gas countercurrent flow in a random packed column with pall rings. Besides the column-averaged information, the radial pall ring distribution, velocity, and liquid holdup profiles are obtained in the simulations. The radial two-phase velocity and liquid holdup profiles show significant fluctuations caused by the non-uniform pall ring distribution. The entrance effect and wall influence are also observed in the packed column. By using local countercurrent flow information, the packing specific area $a_p$ and liquid velocity $u_L$ range are significantly expanded for liquid holdup hL prediction. This enables us to develop the liquid holdup correlation with one packing size and six CFD runs only. The proposed power law of the liquid holdup correlation $h_L~u_L^{0.44}$ indicates the random packed column falls in a viscous to turbulent transition regime with a Reynolds Number range of [6.7–40.2]. The derived liquid holdup correlation is in good agreement with existing correlations that are developed using the column-averaged experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Anomalous Hall effects in chiral superconductors

We report theoretical results for the electronic contribution to thermal and electrical transport for chiral superconductors belonging to even or odd-parity E 1 and E 2 representations of the tetragonal and hexagonal point groups. Chiral superconductors exhibit novel properties that depend on the topology of the order parameter and Fermi surface, and—as we highlight—the structure of the impurity potential. An anomalous thermal Hall effect is predicted and shown to be sensitive to the winding number, ν, of the chiral order parameter via Andreev scattering that transfers angular momentum from the chiral condensate to excitations that scatter off the random potential. For heat transport in a chiral superconductor with isotropic impurity scattering, i.e., point-like impurities, a transverse heat current is obtained for ν = ± 1, but vanishes for | ν | > 1. This is not a universal result. For finite-size impurities with radii of order or greater than the Fermi wavelength, R ≥ ℏ / p f, the thermal Hall conductivity is finite for chiral order with | ν | ≥ 2, and determined by a specific Fermi-surface average of the differential cross-section for electron-impurity scattering. Our results also provide quantitative formulae for analyzing and interpreting thermal transport measurements for superconductors predicted to exhibit broken time-reversal and mirror symmetries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Improving Traditional Registrational Trial End Points: Development and Application of a Desirability of Outcome Ranking End Point for Complicated Urinary Tract Infection Clinical Trials

Abstract Background Traditional end points used in registrational randomized, controlled trials (RCTs) often do not allow for complete interpretation of the full range of potential clinical outcomes. Desirability of outcome ranking (DOOR) is an approach to the design and analysis of clinical trials that incorporates benefits and risks of novel treatment strategies and provides a global assessment of patient experience. Methods Through a multidisciplinary committee of experts in infectious diseases, clinical trial design, drug regulation, and patient experience, we developed a DOOR end point for infectious disease syndromes and demonstrated how this could be applied to 3 registrational drug trials (ZEUS, APEKS-cUTI, and DORI-05) for complicated urinary tract infections (cUTIs). ZEUS compared fosfomycin to piperacillin/tazobactam, APEKS-cUTI compared cefiderocol to imipenem, and DORI-05 compared doripenem to levofloxacin. Using DOOR, we estimated the probability of a more desirable outcome with each investigational antibacterial drug. Results In each RCT, the DOOR distribution was similar and the probability that a patient in the investigational arm would have a more desirable outcome than a patient in the control arm had a 95% confidence interval containing 50%, indicating no significant difference between treatment arms. DOOR facilitated improved understanding of potential trade-offs between clinical efficacy and safety. Partial credit and subgroup analyses also highlight unique attributes of DOOR. Conclusions DOOR can effectively be used in registrational cUTI trials. The DOOR end point presented here can be adapted for other infectious disease syndromes and prospectively incorporated into future clinical trials.

Immunology↗
DOE OSTI2022

Interfacial Exchange Phenomena Driven by Ferromagnetic Domains

Abstract Interfacial proximity effects in antiferromagnetic/ferromagnetic (AFM/FM) bilayers control the exchange‐bias (EB) phenomena exploited in most spintronic devices, although still is lack of full understanding. Discordant results, including different exchange‐bias field ( H E ), coercivity ( H C ), or blocking temperature ( T B ) found even in similar systems, are usually ascribed to uncontrolled parameters, namely dissimilar interfacial defects, structure, and thicknesses. Here, it is shown in the very same sample that the magnetic domain structure during the magnetization reversal of the FM layer controls those mentioned effects. Simultaneous transport and vectorial‐resolved magnetic measurements performed in a V 2 O 3 /Co system during warming after different field cooling (FC) procedures exhibit a strong dependence on the FC angle and the domain structure of the FM layer. Remarkably, magnetization reversal analysis reveals 35 K of variation in T B and up to a factor of two in H E . These observations can be explained within the random‐field model for the interfacial exchange coupling with a fixed AFM domain structure in contact with a variable (angle‐dependent) FM domain structure. The results highlight the importance of the domain structure and magnetization reversal of the FM layer (not previously considered) in the EB phenomena, with potential to tailor interfacial effects in future spintronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2023

Asymmetric Electrode Work Function Customization via Top Electrode Replacement in Ferroelectric and Field–Induced Ferroelectric Hafnium Zirconium Oxide Thin Films

Non-volatile memory device structures such as ferroelectric random-access memory and ferroelectric tunnel junctions employ switchable spontaneous polarization to hold binary states. These devices can potentially benefit from the imposition of spontaneous internal biases and their resulting effect on the polarization properties of the ferroelectric (or field-induced ferroelectric/ antiferroelectric) layer. While HfO 2 -based thin films are ideal candidates for implementation into these devices due to their scalability and silicon compatibility, the phase purity of these oxides is sensitive to the selection of electrode material, preventing incorporation of asymmetric electrode layers into such structures. Within this work, electrode replacement following post-metallization anneal processing is introduced as a route to achieve ferroelectric and field-induced ferroelectric Hf x Zr 1–x O 2 (HZO) thin films with electrode-independent phase constitutions. The effects of this process and the corresponding internal biases imposed across the HZO layers due to asymmetric work functions are investigated. It is shown that internal biases vary in magnitude in accordance with prediction based on the work functions of the replaced electrode layers and affect remanent polarization magnitudes. Accordingly, electrode replacement presents a processing route that can readily produce HZO films with spontaneous internal biases and electrode- independent phase constitutions, facilitating implementation of these ferroelectrics into the next generation device structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Speed vs Accuracy: Effect on Ligand Pose Accuracy of Varying Box Size and Exhaustiveness in AutoDock Vina

Abstract Structure‐based virtual high‐throughput screening involves docking chemical libraries to targets of interest. A parameter pertinent to the accuracy of the resulting pose is the root mean square deviation (RMSD) from a known crystallographic structure, i. e., the ‘docking power’. Here, using a popular algorithm, Autodock Vina, as a model program, we evaluate the effects of varying two common docking parameters: the box size (the size of docking search space) and the exhaustiveness of the global search (the number of independent runs starting from random ligand conformations) on the RMSD from the PDBbind v2017 refined dataset of experimental protein‐ligand complexes. Although it is clear that exhaustiveness is an important parameter, there is wide variation in the values used, with variation between 1 and >100. We, therefore, evaluated a combination of cubic boxes of different sizes and five exhaustiveness values (1, 8, 25, 50, 75, 100) within the range of those commonly adopted. The results show that the default exhaustiveness value of 8 performs well overall for most box sizes. In contrast, for all box sizes, but particularly for large boxes, an exhaustiveness value of 1 led to significantly higher median RMSD (mRMSD) values. The docking power was slightly improved with an exhaustiveness of 25, but the mRMSD changes little with values higher than 25. Therefore, although low exhaustiveness is computationally faster, the results are more likely to be far from reality, and, conversely, values >25 led to little improvement at the expense of computational resources. Overall, we recommend users to use at least the default exhaustiveness value of 8 for virtual screening calculations.

Agarwal, Rupesh↗
DOE OSTI2022

Energy and mechanical properties predictions in Fe-Ni binary system by ab initio calculations

Here, the fcc random solid solutions in Fe-Ni binary system were investigated using ab initio calculations. Density functional theory (DFT) was applied along with supercells generated by the Special Quasi-Random Structure (SQS) method to predict the enthalpy of mixing and magnetic and elastic properties. The results were compared with relevant experimental and computational data produced by other groups. The effect of SQS supercell size and relaxation procedure on the predicted properties of the alloys were also studied. Our calculations show that 16-atoms SQS model provides adequate approach to the mixing energy of the alloy. However, calculation of mechanical properties requires larger supercell. Excellent agreement between experimental and calculated elastic properties was found in fcc region of Fe-Ni system.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Larger than uncorrelated vacancy diffusion contributions in chemically disordered crystalline materials

Arising from a variational approach to compute diffusion coefficients, we introduce “superkinetic kinosons”, which are contributions to the diffusion flux of mobile defects and atomic species by single jump mechanisms that can exceed their uncorrelated values. In vacancy-mediated diffusion in crystalline random and high entropy materials, these contributions primarily arise from intermittent jumps of slow moving atoms that remove the vacancy out of correlation traps and enable a quantification of such effects on the diffusion coefficients. They can be significant contributors to diffusion, even when faster moving atoms have infinite percolation networks. Furthermore, their existence and importance provide fundamental insights about underlying aspects of vacancy diffusion such as formation of localized correlation traps and deviation of vacancy diffusion from percolation behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Lattice Dynamics and Optoelectronic Properties of Vacancy-Ordered Double Perovskite Cs 2 TeX 6 (X = Cl – , Br – , I – ) Single Crystals

The soft, dynamic lattice of inorganic lead halide perovskite CsPbX 3 (X = Cl ⁻ , Br ⁻ , I ⁻ ) leads to the emergence of many interesting photophysical and optoelectronic phenomena. However, probing their lattice dynamics with vibrational spectroscopy remains challenging. The influence of the fundamental octahedral building block in the perovskite lattice can be better resolved in zero-dimensional (0D) vacancy-ordered double perovskites of form A 2 BX 6 . Here we study Cs 2 TeX 6 (X = Cl ⁻ , Br ⁻ , I ⁻ ) single crystals to yield detailed insight into the fundamental octahedral building block and to explore the effect that its isolation in the crystal structure has on structural and electronic properties. The isolated [TeX 6 ] 2- octahedral units serve as the vibrational, absorbing, and emitting centers within the crystal. Serving as the vibrational centers, the isolated octahedra inform the likelihood of a random distribution of 10 octahedral symmetries within the mixed-halide spaces, as well as the presence of strong exciton-phonon coupling and anharmonic lattice dynamics. Serving as the absorbing and emitting centers, the isolated octahedra exhibit compositionally tunable absorption (1.50-3.15 eV) and emission (1.31-2.11 eV) energies. Due to greater molecular orbital overlap between neighboring octahedra with increasing halide anion size, there is a transition from a more molecule-like electronic structure in Cs 2 TeCl 6 and Cs 2 TeBr 6 -as expected from the effective 0D nature of these single crystals-to a dispersive electronic structure in Cs 2 TeI 6 , typical of three-dimensional (3D) bulk single crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Survival of itinerant excitations and quantum spin state transitions in YbMgGaO 4 with chemical disorder

A recent focus of quantum spin liquid (QSL) studies is how disorder/randomness in a QSL candidate affects its true magnetic ground state. The ultimate question is whether the QSL survives disorder or the disorder leads to a “spin-liquid-like” state, such as the proposed random-singlet (RS) state. Since disorder is a standard feature of most QSL candidates, this question represents a major challenge for QSL candidates. YbMgGaO 4 , a triangular lattice antiferromagnet with effective spin-1/2 Yb 3+ ions, is an ideal system to address this question, since it shows no long-range magnetic ordering with Mg/Ga site disorder. Despite the intensive study, it remains unresolved as to whether YbMgGaO 4 is a QSL or in the RS state. Here, through ultralow-temperature thermal conductivity and magnetic torque measurements, plus specific heat and DC magnetization data, we observed a residual κ 0 /T term and series of quantum spin state transitions in the zero temperature limit for YbMgGaO 4 . These observations strongly suggest that a QSL state with itinerant excitations and quantum spin fluctuations survives disorder in YbMgGaO 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗