arXiv subjects

Gourab Roy

Publications and source records attributed to Gourab Roy.

7 recordsLinked to original sources

arXiv2026

Dispersive-phonon-driven room-temperature Ni1+-Ni2+ polaron hopping in spin-charge coupled rutile niobate

Understanding how lattice dynamics mediate polaron hopping is essential for designing multifunctional correlated oxides. Here, we demonstrate room-temperature dispersive phonon excitations and elucidate the Ni1+-Ni2+ polaron-hopping mechanism and the presence of rare spin-charge-phonon coupling even in a magnetically short-range-ordered state in rutile niobate, a rare room-temperature magnetodielectric system. We reveal room-temperature dispersive phonon excitations using inelastic neutron scattering (INS), complemented by machine-learning-based phonon calculations, to establish the microscopic origin of the polaron-hopping mechanism. Experimental evidence of dispersive phonon-driven polaron hopping is scarce. INS measurements show significant dispersive phonon excitations at 21, 33, and 47 meV, implying collective lattice dynamics that enable delocalized polaron propagation via coupled charge-spin-phonon interactions. Dispersive phonons couple to charge carriers and promote correlated NiO6 lattice distortions, facilitating delocalized polaron hopping. Low-energy magnetic excitations at 4 and 8 meV indicate the presence of local short-range magnetic correlations or spin-orbit-coupling-induced anisotropy in deformed NiO6 octahedra, which are thoroughly discussed. Machine-learning phonon calculations replicate the experimentally observed phonon excitations and demonstrate lattice instability, which is compatible with dynamic local distortions caused by polaron production. These findings provide microscopic evidence for a coupled charge-spin-phonon mechanism that mediates polaron hopping in rutile oxide systems.

cond-mat.mtrl-sci↗

arXiv2026

Interplay of Spin Waves, Crystal-Field Excitations, and Phonons in Multiferroic Ba3HoRu2O9 revealed by Inelastic Neutron Scattering, Crystal-Field Analysis, and Machine-Learned Phonon Calculations

Understanding the microscopic origin of spin-dipole coupling and high-energy excitations in correlated 4d-4f multiferroic oxides is challenging because magnetic, crystal-field, and lattice excitations frequently overlap in energy. The hexagonal 6H perovskite Ba3HoRu2O9 provides an ideal platform to investigate this interplay owing to the coexistence of Ru2O9 molecular units and localized Ho3+ moments. To identify the contributions from these different excitations, we combine inelastic neutron scattering (INS) with linear spin-wave calculations, crystal-field analysis, Raman spectroscopy, and machine-learned force field (MLFF) phonon calculations. A dispersive magnetic excitation below 6.2 meV is accurately reproduced by linear spin-wave theory, establishing its origin as a collective spin-wave excitation of the coupled Ru-Ho magnetic network. At higher energies, broad excitations centered near 20, 39, 70, and 90 meV is observed that are present far above magnetic ordering temperature. Crystal-field calculations based on the Stevens formalism place the strongest Ho3+ transitions within the experimentally observed energy window, while Raman spectroscopy and MLFF phonon calculations identify optical phonons with comparable energies. Together, these complementary results show that the broad INS feature near 39 meV is consistent with overlapping contributions from Ho3+ crystal-field excitations, lattice vibrations, and previously reported Ru2O9 molecular magnetic excitations. These findings establish a microscopic framework for understanding the interplay between spin, crystal-field, and lattice degrees of freedom in this multiferroic 4d-4f compound.

cond-mat.str-el↗

arXiv2026

Spin-Chain Incipient Magnetocaloric Effect and Rare-Earth Controlled Switching in the Haldane-Chain System, R2BaNiO5

We have experimentally investigated the magnetocaloric effect (MCE) of a prototype spin-frustrated one-dimensional spin-chain system, the famous Haldane-chain system, R2BaNiO5 (R = Nd, Gd, Er, Dy). The significant MCE is observed far above long-range ordering, even in the paramagnetic region, which is attributed to the change in magnetic entropy due to short-range spin correlation arising from (low-dimensional) magnetic frustration. Such a spin-chain incipient MCE above long-range ordering is rarely reported. Interestingly, multiple magnetocaloric switching from conventional to inverse MCE (and vice versa) are observed below long-range magnetic ordering, as a function of temperature and magnetic field, for the R = Nd, Dy, and Er members. However, such MCE switching is absent in the Gd member, which is an S-state atom (orbital moment L = 0). Our systematic investigation of this series demonstrates that the interplay between crystal-electric field (CEF), strong spin-orbit coupling (SOC) and rare earth anisotropy of R-ions play an important role in spin reorientation, leading to multiple MCE switching due to intriguing changes in magnetic and lattice entropy. The maximum change of entropy for Er, Gd, Dy and Nd is 7.8, 6.8, 4.0 and 1.0 J Kg-1 K-1 respectively. Our study presents a pathway for tuning MCE switching and the MCE effect over large temperature regions in d-f coupled spin-frustrated and spin-chain oxide systems.

cond-mat.str-el↗

arXiv2026

Spin-correlation Driven Ferroelectric Quantum Criticality in a Perovskite Quantum Spin-liquid System, Ba3CuSb2O9

Here we have experimentally demonstrated spin-correlation-driven ferroelectric quantum criticality in a prototype quantum spin-liquid system, Ba3CuSb2O9, a quantum phenomenon rarely observed. The dielectric constant follows a clear T2 scaling, showing that the material behaves as a quantum paraelectric without developing ferroelectric order. Magnetically, the system avoids long-range order down to 1.8 K and instead displays a T3/2 dependence in its inverse susceptibility, a hallmark of antiferromagnetic quantum critical fluctuations. Together with known spin-orbital-lattice entanglement in this compound, these signatures point to a strong interplay between spin dynamics and the polar lattice. Our pioneering work places this perovskite spin-liquid family at the forefront of this domain and suggest the flexibility of this family in a suitable environment by tuning chemical/ external pressure.

cond-mat.str-el↗

arXiv2025

Intriguing Magnetocaloric Effect in Multiferroic Ba3RRu2O9 (R=Ho, Gd, Tb, Nd) with Strong 4d-4f Correlations

Here we demonstrate the magnetocaloric effect (MCE) of a 4d-4f correlated system, namely Ba3RRu2O9 (R= Ho, Gd, Tb, Nd). The compound Ba3HoRu2O9 antiferromagnetically orders at 50 K where both the Ho and Ru-moments order, followed by another phase transition ~ 10 K. Whereas, the compound Ba3GdRu2O9 and Ba3TbRu2O9 orders at 14.5 and 10.5 K respectively, where the ordering of both R and Ru moments are speculated. Our results reveal robust MCE around low-T magnetic phase transition for all the heavy rare-earth members (Ho, Gd, Tb) in this family. The heavy rare-earth members exhibit an intriguing MCE behavior switching from conventional to non-conventional MCE. Interestingly, the light R-member, Ba3NdRu2O9, orders ferromagnetically below 24 K where Nd-moments order, followed by Ru-ordering below 18 K, exhibits a positive MCE below and above FM-ordering. The compelling MCE are attributed to temperature dependent complex spin-reorientations for different R-members and anisotropy.

cond-mat.str-el↗

arXiv2025

Quasiparticle Dynamics in the 4d-4f Ising-like Double Perovskite Ba2DyRuO6 studied using Neutron Scattering and Machine-Learning Framework

Double perovskites containing 4d--4f interactions provide a platform to study complex magnetic phenomena in correlated systems. Here, we investigate the magnetic ground state and quasiparticle excitations of the fascinating double perovskite system, Ba$_2$DyRuO$_6$, through Time of flight (TOF) neutron diffraction (TOF), inelastic neutron scattering (INS), and theoretical modelling. The compound Ba$_2$DyRuO$_6$ is reported to exhibit a single magnetic transition, in sharp contrast to most of the other rare-earth (R) members in this family, A$_2$RRuO$_6$ (A = Ca/Sr/Ba), which typically show magnetic ordering of the Ru ions, followed by R-ion ordering. Our neutron diffraction results confirm that long-range antiferromagnetic order emerges at $T_\mathrm{N} \approx 47$~K, primarily driven by 4d--4f Ru$^{5+}$--Dy$^{3+}$ exchange interactions, where both Dy and Ru moments start to order simultaneously. The ordered ground state is a collinear antiferromagnet with Ising character, carrying ordered moments of $\mu_{\mathrm{Ru}} = 1.6(1)~\mu_\mathrm{B}$ and $\mu_{\mathrm{Dy}} = 5.1(1)~\mu_\mathrm{B}$ at 1.5~K. Low-temperature INS reveals well-defined magnon excitations below 10~meV. SpinW modelling of the INS spectra evidences complex exchange interactions and the presence of magnetic anisotropy, which governs the Ising ground state and accounts for the observed magnon spectrum. Combined INS and Raman spectroscopy reveal crystal-electric-field (CEF) excitations of Dy$^{3+}$ at 46.5 and 71.8~meV in the paramagnetic region. The observed CEF levels are reproduced by point-charge calculations consistent with the $O_h$ symmetry of Dy$^{3+}$. A complementary machine-learning approach is used to analyse the phonon spectrum and compare with INS data. Together, these results clarify the origin of phonon and magnon excitations and their role in the ground-state magnetism of Ba$_2$DyRuO$_6$.

cond-mat.str-el↗

arXiv2023

CovidExpert: A Triplet Siamese Neural Network framework for the detection of COVID-19

Patients with the COVID-19 infection may have pneumonia-like symptoms as well as respiratory problems which may harm the lungs. From medical images, coronavirus illness may be accurately identified and predicted using a variety of machine learning methods. Most of the published machine learning methods may need extensive hyperparameter adjustment and are unsuitable for small datasets. By leveraging the data in a comparatively small dataset, few-shot learning algorithms aim to reduce the requirement of large datasets. This inspired us to develop a few-shot learning model for early detection of COVID-19 to reduce the post-effect of this dangerous disease. The proposed architecture combines few-shot learning with an ensemble of pre-trained convolutional neural networks to extract feature vectors from CT scan images for similarity learning. The proposed Triplet Siamese Network as the few-shot learning model classified CT scan images into Normal, COVID-19, and Community-Acquired Pneumonia. The suggested model achieved an overall accuracy of 98.719%, a specificity of 99.36%, a sensitivity of 98.72%, and a ROC score of 99.9% with only 200 CT scans per category for training data.

cs.CV↗