19 research outputs found
31P NMR Investigation of the Superconductor LiFeP (Tc = 5 K)
We investigate the static and dynamic spin susceptibility of the 111 type
Fe-based superconductor LiFeP with Tc ~ 5 K through the measurement of Knight
shift 31K and the spin-lattice relaxation rate 1/T1 at 31P site by nuclear
magnetic resonance. The constant 31K, small magnitudes of 1/T1T, along with the
resistivity rho ~ T^2 all point to the weak spin correlations in LiFeP. 1/T1T
display small enhancement toward Tc, indicating that the superconductivity is
intimately correlated with the antiferromagnetic spin fluctuations.Comment: Accepted for publication in EP
Large Language Models for Robotics: A Survey
The human ability to learn, generalize, and control complex manipulation
tasks through multi-modality feedback suggests a unique capability, which we
refer to as dexterity intelligence. Understanding and assessing this
intelligence is a complex task. Amidst the swift progress and extensive
proliferation of large language models (LLMs), their applications in the field
of robotics have garnered increasing attention. LLMs possess the ability to
process and generate natural language, facilitating efficient interaction and
collaboration with robots. Researchers and engineers in the field of robotics
have recognized the immense potential of LLMs in enhancing robot intelligence,
human-robot interaction, and autonomy. Therefore, this comprehensive review
aims to summarize the applications of LLMs in robotics, delving into their
impact and contributions to key areas such as robot control, perception,
decision-making, and path planning. We first provide an overview of the
background and development of LLMs for robotics, followed by a description of
the benefits of LLMs for robotics and recent advancements in robotics models
based on LLMs. We then delve into the various techniques used in the model,
including those employed in perception, decision-making, control, and
interaction. Finally, we explore the applications of LLMs in robotics and some
potential challenges they may face in the near future. Embodied intelligence is
the future of intelligent science, and LLMs-based robotics is one of the
promising but challenging paths to achieve this.Comment: Preprint. 4 figures, 3 table
Disentangling superconducting and magnetic orders in NaFe_1-xNi_xAs using muon spin rotation
Muon spin rotation and relaxation studies have been performed on a "111"
family of iron-based superconductors NaFe_1-xNi_xAs. Static magnetic order was
characterized by obtaining the temperature and doping dependences of the local
ordered magnetic moment size and the volume fraction of the magnetically
ordered regions. For x = 0 and 0.4 %, a transition to a nearly-homogeneous long
range magnetically ordered state is observed, while for higher x than 0.4 %
magnetic order becomes more disordered and is completely suppressed for x = 1.5
%. The magnetic volume fraction continuously decreases with increasing x. The
combination of magnetic and superconducting volumes implies that a
spatially-overlapping coexistence of magnetism and superconductivity spans a
large region of the T-x phase diagram for NaFe_1-xNi_xAs . A strong reduction
of both the ordered moment size and the volume fraction is observed below the
superconducting T_C for x = 0.6, 1.0, and 1.3 %, in contrast to other iron
pnictides in which one of these two parameters exhibits a reduction below TC,
but not both. The suppression of magnetic order is further enhanced with
increased Ni doping, leading to a reentrant non-magnetic state below T_C for x
= 1.3 %. The reentrant behavior indicates an interplay between
antiferromagnetism and superconductivity involving competition for the same
electrons. These observations are consistent with the sign-changing s-wave
superconducting state, which is expected to appear on the verge of microscopic
coexistence and phase separation with magnetism. We also present a universal
linear relationship between the local ordered moment size and the
antiferromagnetic ordering temperature TN across a variety of iron-based
superconductors. We argue that this linear relationship is consistent with an
itinerant-electron approach, in which Fermi surface nesting drives
antiferromagnetic ordering.Comment: 20 pages, 14 figures, Correspondence should be addressed to Prof.
Yasutomo Uemura: [email protected]