arXiv subjects

Akshay Rao

Publications and source records attributed to Akshay Rao.

At least 19 recordsLinked to original sources

arXiv2026

Intrinsic linewidths of confined phonons in few-layer hBN

Understanding lattice vibrations in two-dimensional (2D) materials is essential for controlling thermal transport, mechanical response, and energy dissipation in nanoscale devices. However, the intrinsic lifetimes of low-energy phonon modes, particularly those that are optically silent, remain largely unexplored. Here we use helium-3 spin-echo spectroscopy to resolve low-energy phonons at the surface of hexagonal boron nitride (hBN) and measure their intrinsic linewidths. We observe the flexural and Rayleigh wave modes and extract the bending rigidity of a quasi-freestanding hBN monolayer. We further report the simultaneous observation of multiple surface-confined interlayer shear modes whose energies agree closely with linear-chain model predictions. By resolving their intrinsic linewidths, we demonstrate a strong confinement-induced reduction in phonon lifetimes, with a near order of magnitude increase in linewidth between the four- and two-layer modes. The temperature dependence of the linewidths indicates that phonon-phonon scattering dominates between 160-360K, while the systematic broadening with decreasing layer number reveals the impact of confinement on phonon decay. These results reveal how reduced dimensionality affects the decay of interlayer shearing modes in hBN, providing direct insight into the phonon lifetimes, confinement effects, and dissipation pathways that govern the dynamical behaviour of two-dimensional materials.

cond-mat.mtrl-sci↗

arXiv2026

Carrier Localization in Pnictogen-Based Chalcohalides from Defect-Bound Hot Polarons

Pnictogen-based solar absorbers have gained prominence as promising nontoxic and stable alternatives to lead-halide perovskites (LHPs), but are severely limited by carrier localization, preventing their performance from approaching those of LHPs. Recent efforts have uncovered routes to overcome carrier localization, but these early efforts only considered intrinsic factors. Herein, we push beyond these limited early efforts, examining the role of defects, not only on cold carriers but also hot carriers. Focusing on the structurally one-dimensional pnictogen chalcohalide BiSBr, we find that whilst this material intrinsically does not exhibit carrier localization, vacancies introduced during synthesis or post-treatment lead to pronounced extrinsic self-trapping via the formation of defect-bound hot polarons-excited charge-carriers strongly coupled to local defect-induced vibrational modes. These above-gap defect states divert hot carriers from cooling to the band edge, thus depleting the mobile carrier population. Our findings establish the key role of defect-bound hot polarons in mediating extrinsic localization and offer new mechanistic insights into the interplay between defects, lattice coupling, and excited-state charge-carrier transport, which are critical to designing efficient perovskite-inspired solar absorbers.

cond-mat.mtrl-sci↗

arXiv2026

Electric Field Resolved Image Formation in a Widefield Optical Microscope

Visualizing the spatiotemporal evolution of the electric field of light is fundamental to optics, from designing photonic devices to developing next-generation microscopes. However, we lack the experimental tools to directly access the electric field of light in the sample plane of an optical microscope. Here, we introduce an all-optical imaging modality that resolves the electric field of light in the plane of a traditional widefield transmission optical microscope with 100-attosecond temporal and 200-nanometer spatial resolution. With this we demonstrate the delayed buildup of scattering contrast and pulse broadening through and around a thick MoTe2 flake - dynamics inaccessible via standard simulations. We showcase our technique's versatility by additionally resolving the full in-plane vector electric field lines during photoexcitation as the optical pulse propagates through and around the MoTe2 flake.

physics.optics↗

arXiv2026

Band-Like Transport and Cation Off-Centring in Ag/Bi-Based Solar Absorbers

Ag(I)-Bi(III)-based semiconductors have gained substantial attention as nontoxic, stable alternatives to lead-halide perovskites for optoelectronics, but are widely limited by carrier localization, which severely restricts diffusion lengths. The most efficient Ag/Bi solar absorber is AgBiS2, but diffusion lengths in nanocrystal films are <50 nm. Carrier localization in this rock-salt (Fm-3m) system is believed to arise from cation disorder, and so we herein investigate the layered cation-ordered analogue. Through beyond-DFT simulations combined with neutron and X-ray powder diffraction, we reveal that off-centring of Ag+ and Bi3+ cations is energetically-favoured in this cation-ordered phase. Despite local distortions in the AgS6 and BiS6 octahedra, band-like transport takes place, which, surprisingly, also occurs in the cation-disordered rock-salt phase when these materials are made as bulk powders. The cubic-phase powders have the same degree of cation disorder as the nanocrystals that have carrier localization, which suggests that extrinsic factors play a determining role. We ascribe the intrinsic band-like transport of both phases of AgBiS2 to its close packing, ensuring high electronic dimensionality. These insights offer pathways for designing solar absorbers avoiding carrier localization limitations, and call for future efforts to enhance the efficiency of AgBiS2 photovoltaics to focus on large-grained thin films, or improved nanocrystal surface passivation.

cond-mat.mtrl-sci↗

arXiv2025

Learning complete and explainable visual representations from itemized text supervision

Training vision models with language supervision enables general and transferable representations. However, many visual domains, especially non-object-centric domains such as medical imaging and remote sensing, contain itemized text annotations: multiple text items describing distinct and semantically independent findings within a single image. Such supervision differs from standard multi-caption supervision, where captions are redundant or highly overlapping. Here, we introduce ItemizedCLIP, a framework for learning complete and explainable visual representations from itemized text supervision. ItemizedCLIP employs a cross-attention module to produce text item-conditioned visual embeddings and a set of tailored objectives that jointly enforce item independence (distinct regions for distinct items) and representation completeness (coverage of all items). Across four domains with naturally itemized text supervision (brain MRI, head CT, chest CT, remote sensing) and one additional synthetically itemized dataset, ItemizedCLIP achieves substantial improvements in zero-shot performance and fine-grained interpretability over baselines. The resulting ItemizedCLIP representations are semantically grounded, item-differentiable, complete, and visually interpretable. Our code is available at https://github.com/MLNeurosurg/ItemizedCLIP.

cs.CV↗

arXiv2025

Health system learning achieves generalist neuroimaging models

Frontier artificial intelligence (AI) models, such as OpenAI's GPT-5 and Meta's DINOv3, have advanced rapidly through training on internet-scale public data, yet such systems lack access to private clinical data. Neuroimaging, in particular, is underrepresented in the public domain due to identifiable facial features within MRI and CT scans, fundamentally restricting model performance in clinical medicine. Here, we show that frontier models underperform on neuroimaging tasks and that learning directly from uncurated data generated during routine clinical care at health systems, a paradigm we call health system learning, yields high-performance, generalist neuroimaging models. We introduce NeuroVFM, a visual foundation model trained on 5.24 million clinical MRI and CT volumes using a scalable volumetric joint-embedding predictive architecture. NeuroVFM learns comprehensive representations of brain anatomy and pathology, achieving state-of-the-art performance across multiple clinical tasks, including radiologic diagnosis and report generation. The model exhibits emergent neuroanatomic understanding and interpretable visual grounding of diagnostic findings. When paired with open-source language models through lightweight visual instruction tuning, NeuroVFM generates radiology reports that surpass frontier models in accuracy, clinical triage, and expert preference. Through clinically grounded visual understanding, NeuroVFM reduces hallucinated findings and critical errors, offering safer clinical decision support. These results establish health system learning as a paradigm for building generalist medical AI and provide a scalable framework for clinical foundation models.

cs.CV↗

arXiv2025

Ligand Engineering for Precise Control of Ultrathin CsPbI3 Nanoplatelet Superlattices for Efficient Light-Emitting Diodes

Strongly-confined perovskite nanoplatelets (PeNPLs) offer opportunities not found in conventional isotropic nanocubes, especially in producing linearly polarized light, as well as enhancing outcoupling through control over the transition dipole moment. But this requires ultrathin nanoplatelets with three or fewer monolayers of PbI6 octahedra across the thickness, which are challenging to synthesise uniformly, and their luminescence is strongly affected by surface defects. Together, these limit the performance of ultrathin PeNPLs in light-emitting diodes (LEDs). Here, we address these challenges with an ancillary ligand engineering strategy. We demonstrate that ligands with phosphoryl functional groups strongly bind to the perovskite surface, while having an organic backbone that is not sterically bulky ensures high ligand density. By modulating nucleation and growth, these ancillary ligands lead to monodisperse PeNPLs that stack more uniformly when self-assembled into superlattices, with suppressed agglomeration. As a result, from edge-up PeNPL superlattices, we achieve enhanced degree of polarization, while from face-down PeNPL superlattices, we achieve enhanced outcoupling that results in LEDs with 13.1% external quantum efficiency, the highest reported for ultrathin PeNPL LEDs. This work establishes ancillary ligand-induced synthesis as a decisive route to achieve uniform nanoplatelets with robust orientation control, enabling full utilization of the multifunctionality of anisotropic PeNPLs.

physics.optics↗

arXiv2025

Room temperature optical control of spin states in organic diradicals

We report a family of luminescent alternant diradicals which, at room temperature, support a ground-state spin-triplet, near-unity photoluminescence quantum yields, and optical spin addressability. These diradicals comprise trityl groups meta-linked via pyridyl or phenyl groups, enabling optically bright triplet-to-triplet and singlet-to-singlet transitions. At room temperature, we observe optically detected magnetic resonance in these systems at zero magnetic field and a strong magneto-photoluminescence (10% modulation at 2 mT applied magnetic field). Distinct photoluminescence bands (at 630 nm and 700 nm) show opposite-sign spin-optical responses, arising from spin-selective intersystem crossing between triplet and singlet manifolds. These bright, all-organic diradicals offer a new set of chemically tunable materials for room temperature spin-optical interfaces, paving the way for application as quantum sensors.

cond-mat.mtrl-sci↗

arXiv2025

Avalanche-like lithium intercalation and intraparticle correlations in graphite

Graphite is the most widely used anode material in lithium-ion batteries with over 98% market share. However, despite its first application over 30 years ago, the lithium insertion processes and associated dynamics in graphite remain poorly understood, especially for the dilute stages. A fundamental understanding of how the symmetry-breaking phase transitions occur pseudo-continuously under operating conditions is still lacking. Here, we provide a unified picture of ion intercalation dynamics during the dilute stages of graphite intercalation, using operando optical microscopy combined with random field Ising modelling. We show that during the dilute stages, single graphite particle undergoes rapid, localised avalanche-like (de)intercalation, leading to micron-sized regions (de)intercalating within seconds. These avalanches are reminiscent of phase transition behaviour seen in disordered materials such as martensitic transformations, Barkhausen noise and ferroelectric/elastic materials - associated with step changes in the order parameter, where the system changes from one phase to another under an applied driving force by jumping from one metastable state to another. Here, using a modified random field Ising model, we relate these avalanches to static disorder in graphite, which disrupts ion filling dynamics, leading to pseudo-continuous transitions between stages, accounting for the experimental electrochemistry profile as well as the temperature dependent avalanche dynamics. Finally, we develop a methodology to spatio-temporally analyse avalanches between intraparticle regions, revealing spatially heterogeneous connectivity and temporal patterns between regions during the dilute stages. Our work highlights the role of local and static disorder in eliciting unexpected phase transition behaviour, and provides new tools and concepts for studying layered battery materials.

cond-mat.mtrl-sci↗

arXiv2025

Learning neuroimaging models from health system-scale data

Neuroimaging is a ubiquitous tool for evaluating patients with neurological diseases. The global demand for magnetic resonance imaging (MRI) studies has risen steadily, placing significant strain on health systems, prolonging turnaround times, and intensifying physician burnout. These challenges disproportionately impact patients in low-resource and rural settings. Here, we utilized a large academic health system as a data engine to develop Prima, the first vision language model (VLM) serving as an AI foundation for neuroimaging that supports real-world, clinical MRI studies as input. Trained on over 220,000 MRI studies, Prima uses a hierarchical vision architecture that provides general and transferable MRI features. Prima was tested in a 1-year health system-wide study that included 30K MRI studies. Across 52 radiologic diagnoses from the major neurologic disorders, including neoplastic, inflammatory, infectious, and developmental lesions, Prima achieved a mean diagnostic area under the ROC curve of 92.0, outperforming other state-of-the-art general and medical AI models. Prima offers explainable differential diagnoses, worklist priority for radiologists, and clinical referral recommendations across diverse patient demographics and MRI systems. Prima demonstrates algorithmic fairness across sensitive groups and can help mitigate health system biases, such as prolonged turnaround times for low-resource populations. These findings highlight the transformative potential of health system-scale VLMs and Prima's role in advancing AI-driven healthcare.

cs.CV↗

arXiv2025

Towards Scalable Language-Image Pre-training for 3D Medical Imaging

The scalability of current language-image pre-training for 3D medical imaging, such as CT and MRI, is constrained by the need for radiologists to manually curate raw clinical studies. In this work, we pioneer pre-training directly on uncurated studies, which both aligns more closely with the radiologist's workflow and provides a natural path to scalability. However, the unique structure of such data presents new challenges for existing model architectures, which were originally designed for 2D slices or single 3D scans. To address this, we introduce a novel hierarchical attention mechanism inspired by the intrinsic hierarchy of radiology data: slice, scan, and study. We denote our framework as Hierarchical attention for Language-Image Pre-training (HLIP). Trained on 220K studies with 3.13 million scans for brain MRI and 240K studies with 1.44 million scans for head CT, HLIP achieves state-of-the-art performance, e.g., +10.5% balanced ACC on the proposed publicly available brain MRI benchmark Pub-Brain-5; +8.3% and +1.7% macro AUC on head CT benchmarks CQ500 and RSNA, respectively. HLIP also exhibits strong generalizability on existing 3D medical language-image pre-training benchmarks, e.g., +4.3% macro AUC on the Rad-ChestCT benchmark when pre-trained on CT-RATE. These results demonstrate that, with HLIP, directly pre-training on uncurated clinical datasets is a scalable and effective direction for language-image pre-training in 3D medical imaging. The code is available at https://github.com/Zch0414/hlip.

cs.CV↗

arXiv2025

Fieldoscopy at the Quantum Limit

We demonstrate a novel concept for measuring time-varying electric field transients of petahertz-scale photons down to a single-photon regime. We observe a clear transition from classical to quantum nature of light that agrees with our Monte Carlo model. We reach unprecedented yoctojoule-level sensitivity and a dynamic range exceeding 90 decibels. We utilize this capability to measure time-dependent intrapulse light coherence - a regime inaccessible to conventional, time-averaged spectroscopy. This opens new avenues for quantum information, cryptography, and quantum light-matter interactions on sub-cycle time scales with attosecond precision.

quant-ph↗

arXiv2025

Defect-modified acoustic phonons in a single layer of MoS2

The thermal, mechanical, and electronic performance of atomically thin semiconductors is governed by their low-energy phonons, yet the impact of atomic-scale disorder on these modes remains poorly understood. Here, we report the first measurement of acoustic phonon dispersions in a quasi-freestanding monolayer semiconductor (MoS2), using helium-3 spin-echo spectroscopy. We identify a defect-driven regime change at a critical wavevector, $q_c$, marking the breakdown of continuum elastic behavior. At this length scale, the flexural mode transitions from continuum bending to defect-pinned standing waves, while the hybridized Rayleigh wave becomes vibrationally disordered in its dispersion and linewidth. We observe multiple defect-induced Van Hove singularities deep within the Brillouin zone and strongly suppressed acoustic group velocities, providing direct experimental evidence that four-phonon processes drive thermal transport in mono- and few-layer MoS2. These results offer a microscopic explanation for the anomalously low thermal conductivity widely observed in transition-metal dichalcogenides and demonstrate how atomic-scale disorder dictates energy flow in two-dimensional materials.

cond-mat.mtrl-sci↗

arXiv2024

Efficient short-wave infrared upconversion by self-sensitized holmium-doped nanoparticles

Photon upconversion, combining several low-energy photons to generate one high-energy photon is of wide interest for biomedical, catalytic and photonic applications. Lanthanide-doped nanoparticles (LnNP) are a unique type of upconversion nanoconverter, which can realize ultralarge anti-Stokes shift (>1000 nm) and high photostability, without photo-bleaching and photo-blinking. The excitation wavelength of LnNPs has been limited to the second near-infrared window (1000-1700 nm), mainly sensitized by erbium ions with absorption centered around 1.5 $\mu$m. Here, we demonstrate novel self-sensitized holmium (Ho)-doped nanoconverters to further expand the sensitization range to the short-wave infrared at 2 $\mu$m and achieve efficient upconversion to 640 nm. We show that this upconversion is a 4-photon conversion process with an underlying energy transfer upconversion mechanism. Via careful control of dopant concentration and shelling we achieve a relative upconversion-to-downconversion efficiency up to 15.2%, more than half the theoretical maximum. The placement of the Ho doped LnNPs into a plasmonic nanocavity device enables large gains in emission intensity (up to 32-fold), due to the dramatic shortening of the emission lifetime of Ho from 29 $\mu$s to <1 ns, indicating a high Purcell-enhancement factor of 3x10$^4$. These results open new possibilities at the frontier of short-wave infrared upconversion and the nanoplasmonic enhancement of LnNP emission, with potential applications in detection, theranostics, photonics and optoelectronics.

physics.optics↗

arXiv2024

High-Spin State Dynamics and Quintet-Mediated Emission in Intramolecular Singlet Fission

High-spin states in molecular systems hold significant interest for a wide range of applications ranging from optoelectronics to quantum information and singlet fission (SF). Quintet and triplet states play crucial roles, particularly in SF systems, necessitating a precise monitoring and control of their spin dynamics. Spin states in intramolecular SF (iSF) are of particular interest, but tuning these systems to control triplet multiplication pathways has not been extensively studied. Additionally, whilst studies in this context focus on participation of triplet pathways leading to photoluminescence, emission pathways via quintet states remain largely unexplored. Here, we employ a set of unique spin-sensitive techniques to investigate high-spin state formation and emission in dimers and trimers comprising multiple diphenylhexatriene (DPH) units. We demonstrate the formation of pure quintet states in all these oligomers, with high-spin state optical emission via quintet states dominating delayed fluorescence up to room temperature. For triplet formation, we distinguish between the ability to form weakly exchange-coupled triplet pairs and the efficiency-reducing pathway of intersystem crossing (ISC), identifying the trimer Me-(DPH)$_3$ as the only oligomer exhibiting exclusively the desired SF pathways. Conversely, linear (DPH)$_3$ and (DPH)$_2$ show additional or exclusive triplet pathways via ISC. Our comprehensive analysis provides a detailed investigation into high-spin state formation, control, and emission in intramolecular singlet fission systems.

cond-mat.mtrl-sci↗

arXiv2024

Measuring vacancy-type defect density in monolayer semiconductors

Two-dimensional (2D) materials have attracted wide-spread interest due to their unique and tunable properties. Their optoelectronic, mechanical, and thermal properties are greatly influenced by crystal defects, which are, in turn, used to control these properties. However, experimental quantification of the density of defects, whether deliberately introduced or inherent, is very difficult in these atomically thin materials. Here we show that helium atom micro-diffraction can be used to measure the defect density in 15x20um monolayer MoS2, a prototypical 2D semiconductor, quickly and easily compared to standard methods. We present a simple analytic model, the lattice gas equation, that fully captures the relationship between atomic Bragg diffraction intensity and defect density. The model, combined with ab initio scattering calculations, shows that our technique can immediately be applied to a wide range of 2D materials, independent of sample chemistry or structure. Additionally, wafer-scale characterization is immediately possible.

physics.app-ph↗

arXiv2024

Circularly polarised electroluminescence from chiral excitons in vacuum-sublimed supramolecular semiconductor thin films

Materials with chiral electronic structures are of great interest. We report a triazatruxene, TAT, molecular semiconductor with chiral alkyl side chains that crystallises from solution to form chirally-stacked columns with a helical pitch of 6 TATs (2.3 nm). These crystals show strong circularly polarised, CP, green photoluminescence, with dissymmetry of 24%. Electronic structure calculations using the full crystal structure, show that this chiral stacking associates angular momentum to the valence and conduction states and thus gives rise to the observed CP luminescence. Free-standing crystals are not useful for active semiconductor devices, but we have discovered that co-sublimation of TAT as the guest in a structurally mismatched host enables the fabrication of thin films where the chiral crystallization is achieved in-situ by thermally-triggered nano-phase segregation of dopant and host whilst preserving the integrity of the film. This enables fabrication of bright (green) organic light-emitting diodes with unexpectedly high external quantum efficiencies of up to 16% and electroluminescence dissymmetries above 10%. These materials and this process method offer significant application potential in spintronics, optical displays and multidimensional optoelectronics.

cond-mat.mtrl-sci↗

arXiv2024

Optical read and write of spin states in organic diradicals

Optical control and read-out of the ground state spin structure has been demonstrated for defect states in crystalline semiconductors, including the diamond NV- center, and these are promising systems for quantum technologies. Molecular organic semiconductors offer synthetic control of spin placement, in contrast to current limitations in these crystalline systems. Here we report the discovery of spin-optical addressability in a diradical molecule that comprises two trityl radical groups coupled via a fluorene bridge. We demonstrate the three important properties that enable operation as a spin-photon interface: (i) triplet and singlet spin states show photoluminescence peaked at 640 and 700 nm respectively; this allows easy optical measurement of ground state spin. (ii) the ground state spin exchange is small (~60 {\mu}eV) that allows preparation of ground state spin population. This can be achieved by spin-selective excited state intersystem crossing, and we report up to 8% microwave-driven contrast in photoluminescence. (iii) both singlet and triplet manifolds have near-unity photoluminescence quantum yield, which is in contrast to the near-zero quantum yields in prior reports of molecular diradicals. Our results establish these tuneable open-shell organic molecules as a platform to engineer tailor-made spin-optical interfaces.

cond-mat.mtrl-sci↗