Search for: All records

Three new NaBa2M3Q3(Q2) (M = Ag, Cu; Q = S, Se) chalcogenides were prepared using solid-state methods and structurally characterized using single-crystal X-ray diffraction. NaBa2Ag3Se3(Se2) and NaBa2Cu3Se3(Se2) crystallize in the monoclinic C2/m space group and have a two-dimensional structure composed of edge-sharing MSe4/4 tetrahedra separated by Na+ and Ba2+ cations, along with (Se2)2- dimers at the center of the spacings between [M3Se3]3- slabs. NaBa2Ag3S3(S2) adopts a related structure with the C2/m space group but has additional, crystallographically distinct Ag atoms in the [Ag3S3]3- layer that are linearly coordinated. NaBa2Ag3Se3(Se2) and NaBa2Ag3S3(S2) have indirect band gaps measured to be 1.2 eV and 1.9 eV, respectively, which is supported by band structures calculated using density functional theory. Mixed- anion NaBa2Cu3Se5-xSx compositions were prepared to probe for the presence of anion ordering and heteronuclear (S-Se)2- dimers. Structural analyses of the sulfoselenides indicate selenium preferentially occupies the Q-Q dimer sites, while Raman spectroscopy reveals a mixture of (S2), (Se2), and heteronuclear (S-Se) units in the sulfur-rich products. The local ordering of the chalcogens is rationalized using simple bonding concepts and adds to a growing framework for understanding ordering phenomena in mixed-anion systems. 

Lattice thermal conductivity (κL) is a crucial characteristic of crystalline solids with significant implications for thermal management, energy conversion, and thermal barrier coating. The advancement of computational tools based on density functional theory (DFT) has enabled the effective utilization of phonon quasi-particle-based approaches to unravel the underlying physics of various crystalline systems. While the higher order of anharmonicity is commonly used for explaining extraordinary heat transfer behaviors in crystals, the impact of exchange-correlation (XC) functionals in DFT on describing anharmonicity has been largely overlooked. The XC functional is essential for determining the accuracy of DFT in describing interactions among electrons/ions in solids and molecules. However, most XC functionals in solid-state physics are primarily focused on computing the properties that only require small atomic displacements from the equilibrium (within the harmonic approximation), such as harmonic phonons and elastic constants, while anharmonicity involves larger atomic displacements. Therefore, it is more challenging for XC functionals to accurately describe atomic interactions at the anharmonicity level. In this study, we systematically investigate the room-temperature κL of 16 binary compounds with rocksalt and zincblende structures using var- ious XC functionals such as local density approximation (LDA), Perdew-Burke-Ernzerhof (PBE), revised PBE for solid and surface (PBEsol), optimized B86b functional (optB86b), revised Tao-Perdew-Staroverov-Scuseria (revTPSS), strongly constrained and appropriately normed functional (SCAN), regularized SCAN (rSCAN) and regularized-restored SCAN (r2SCAN) in combination with different perturbation orders, including phonon within harmonic approximation (HA) plus three- phonon scattering (HA+3ph), phonon calculated using self-consistent phonon theory (SCPH) plus three-phonon scattering (SCPH+3ph), and SCPH phonon plus three- and four-phonon scattering (SCPH+3,4ph). Our results show that the XC functional exhibits strong entanglement with perturbation order and the mean relative absolute error (MRAE) of the computed κL is strongly influenced by both the XC functional and perturbation order, leading to error cancellation or amplification. The minimal (maximal) MRAE is achieved with revTPSS (rSCAN) at the HA+3ph level, SCAN (r2SCAN) at the SCPH+3ph level, and PBEsol (rSCAN) at the SCPH+3,4ph level. Among these functionals, PBEsol exhibits the highest accuracy at the highest perturbation order. The SCAN- related functionals demonstrate moderate accuracy but are suffer from numerical instability and high computational costs. Furthermore, the different impacts of quartic anharmonicity on κL in rocksalt and zincblende structures are identified by all XC functionals, attributed to the distinct lattice anharmonicity in these two structures. These findings serve as a valuable reference for selecting appropriate functionals for describing anharmonic phonons and offer insights into high-order force constant calculations that could facilitate the development of more accurate XC functionals for solid materials. 

We propose an effective strategy to significantly enhance the thermoelectric power factor (PF) of a series of 2D semimetals and semiconductors by driving them towards a topological phase transition (TPT). Employing first-principles calculations with explicit consideration of electron-phonon interactions, we analyze the electronic transport properties of germanene across the TPT by applying hydrogenation and biaxial strain. We reveal that the nontrivial semimetal phase, hydrogenated germanene with 8% bi- axial strain, achieves a considerable fourfold PF enhancement, attributed to the highly asymmetric electronic structure and semimetallic nature of the nontrivial phase. We extend the strategy to another two representative 2D materials—stanene and HgSe— and observe a similar trend, with a marked sixfold and fivefold increase in PF, respectively. The wide selection of functional groups, universal applicability of biaxial strain, and broad spectrum of 2D semimetals and semiconductors render our approach highly promising for designing novel 2D materials with superior thermoelectric performance. 

Phonons, as quantized vibrational modes in crystalline materials, play a crucial role in determining a wide range of physical properties, such as thermal and electrical conductivity, making their study a cornerstone in materials science. In this study, we present a simple yet effective strategy for deep learning harmonic phonons in crystalline solids by leveraging existing phonon databases and state-of-the-art machine learning techniques. The key of our method lies in transforming existing phonon datasets, primarily represented in interatomic force constants, into a force-displacement representation suitable for training machine learning universal interatomic potentials. By applying our approach to one of the largest phonon databases publicly available, we demonstrate that the resultant machine learning universal harmonic interatomic potential not only accurately predicts full harmonic phonon spectra but also calculates key thermodynamic properties with remarkable precision. Furthermore, the restriction to a harmonic potential energy surface in our model provides a way of assessing uncertainty in machine learning predictions of vibrational properties, essential for guiding further improvements and applications in materials science. 

Optomechanical systems have been exploited in ultrasensitive measurements of force, acceleration and magnetic fields. The fundamental limits for optomechanical sensing have been extensively studied and now well understood—the intrinsic uncertainties of the bosonic optical and mechanical modes, together with backaction noise arising from interactions between the two, dictate the standard quantum limit. Advanced techniques based on non-classical probes, in situ ponderomotive squeezed light and backaction-evading measurements have been developed to overcome the standard quantum limit for individual optomechanical sensors. An alternative, conceptually simpler approach to enhance optomechanical sensing rests on joint measurements taken by multiple sensors. In this configuration, a pathway to overcome the fundamental limits in joint measurements has not been explored. Here we demonstrate that joint force measurements taken with entangled probes on multiple optomechanical sensors can improve the bandwidth in the thermal-noise-dominant regime or the sensitivity in the shot-noise-dominant regime. Moreover, we quantify the overall performance of entangled probes with the sensitivity–bandwidth product and observe a 25% increase compared with that of classical probes. The demonstrated entanglement-enhanced optomechanical sensors would enable new capabilities for inertial navigation, acoustic imaging and searches for new physics. 

Squeezed light has long been used to enhance the precision of a single optomechanical sensor. An emerging set of proposals seeks to use arrays of optomechanical sensors to detect weak distributed forces, for applications ranging from gravity-based subterranean imaging to dark matter searches; however, a detailed investigation into the quantum-enhancement of this approach remains outstanding. Here, we propose an array of entanglement-enhanced optomechanical sensors to improve the broadband sensitivity of distributed force sensing. By coherently operating the optomechanical sensor array and distributing squeezing to entangle the optical fields, the array of sensors has a scaling advantage over independent sensors (i.e.,$$\sqrt{M}\to M$$$\sqrt{M}\to M$, whereMis the number of sensors) due to coherence as well as joint noise suppression due to multi-partite entanglement. As an illustration, we consider entanglement-enhancement of an optomechanical accelerometer array to search for dark matter, and elucidate the challenge of realizing a quantum advantage in this context.