arXiv subjects

Arun Majumdar

Publications and source records attributed to Arun Majumdar.

15 recordsLinked to original sources

arXiv2025

Hydrogen bonding in water under extreme confinement

Fluids under extreme confinement exhibit unique structures and intermolecular bonding, distinct from their bulk analogs, driving innovative applications at the water-energy nexus. Probing confined water experimentally at the length scale of intermolecular and surface forces has, however, remained a challenge. Here, we report direct molecular-level observations of hydrogen bonding in water confined inside individual carbon nanotubes, enabled by in-situ vibrational electron energy-loss spectroscopy with nanoscale resolution. Hydrogen bonding is probed via the intramolecular O-H stretching frequency, which serves as a sensitive spectral signature of the local intermolecular bonding environment. Water in larger carbon nanotubes exhibit the bonded O-H vibrations of bulk water, but at smaller diameters, the frequency blueshifts to near the free O-H stretch found in water vapor and hydrophobic surfaces, indicating a highly dispersed, non-H-bonded environment. Theoretical analysis based on quantum vibrational oscillators indicates that enhanced damping rates, corresponding to rapid hydrogen-bond fluctuations, leads the bimodal spectral peaks to merge into a single broad feature, matching the experimental observation. Furthermore, cryogenic experiments provide insights into complex structural phase transitions of confined water. This research reveals the quantum and dynamic nature of hydrogen bonds under confinement and the potential impact of unveiling molecular-level structure and bonding in confined fluids.

physics.chem-ph↗

arXiv2025

Single-Ion Sensing in Liquid Using Fluorescent h-BN Point Defects

Understanding the chemical state of individual ions in solutions is crucial for advancing knowledge of complex systems. However, sensing systems at the single-ion level in liquid environments remains a significant challenge. A strategy is introduced that leverages the optical emission properties of point defects in hexagonal boron nitride (h-BN) as single ion sensors. The interaction of optically active h-BN defects with ions in solution leads to distinct spectral shifts, enabling precise visualization and analyzing of individual ions. Using Li+ ions in organic electrolytes as a model, spectral shifts exceeding 10 nm were observed upon ion addition. Application of an external electric field further enhanced these shifts to over 40 nm, enabling real-time monitoring of electrical field induced local perturbations of Li+ ions. Through this approach, individual point defects were shown to spectroscopically distinguish ions of varying charges (e.g., Na+, Mg2+, and Al3+) based on their local electrical field, each producing a distinct spectral shift. This platform allows direct sensing of ions and their chemical states in liquid environments, providing insights into subtle interfacial changes at the single-ion level, with measurable spectral shifts detectable at millisecond temporal resolution and at concentrations down to 10 micromolar range. This capability presents potential applications in various fields involving ions in liquids that include battery technology and environmental science.

cond-mat.mes-hall↗

arXiv2025

Defect Engineered Hexagonal-Boron Nitride Enables Ionic Conduction for Lithium Metal Batteries

The practical implementation of lithium-metal anodes has been hindered by uncontrollable dendrite formation and interfacial instability. This study presents a defect-engineering approach of a chemically stable and electrically insulating interfacial layer of hexagonal boron nitride (h-BN) that markedly enhances ionic conductivity through argon ion irradiation. Initially, the electrochemical performance from commercially available, large-area chemical vapor deposition (CVD)-grown h-BN films with industrial-scale argon ion implantation motivated our subsequent detailed investigations using lab-scale exfoliated single-crystal h-BN flakes. Integration of these exfoliated flakes into a hybrid microfluidic-microelectronic chip provided direct evidence that controlled vacancy defects transform h-BN into an efficient lithium-ion conductor while preserving its intrinsic electrical insulation. Experimental validation confirmed improved lithium-metal anode stability, achieving dendrite-free cycling with Li plating/stripping Coulombic efficiencies exceeding 99.5% about 1000 cycles. Further assemble of irradiated h-BN in lithium-sulfur batteries effectively mitigates the polysulfide shuttle effect, sustaining over 97% specific capacity around 300 cycles. These results establish a robust, scalable interface-engineering route for next-generation lithium-metal batteries that combine high ionic transport with excellent electrical insulation.

cond-mat.mtrl-sci↗

arXiv2025

Electron-magnon coupling at the interface of a "twin-twisted" antiferromagnet

We identify a "twin-twist" angle in orthorhombic two-dimensional magnets that maximizes interlayer orbital overlap and enables strong interfacial coupling. Focusing on the van der Waals antiferromagnet CrSBr, we show that this twist angle, near 72 deg, aligns diagonal lattice vectors across the layers, enhancing the interlayer hopping that is spin-forbidden in pristine systems and orbital-forbidden in 90-deg-twisted samples. The enhanced hopping modifies the electronic structure and activates a novel mechanism for excitation of interfacial magnons. Using optical probes we discover that excitons on one side of the interface selectively excite magnons localized on the opposite side. We show that this cross-coupling phenomenon can be understood as a consequence of the spin-transfer torque as that arises as electrons tunnel across the twin-twisted interface. Our findings demonstrate that large-angle twisting in anisotropic 2D materials offers a powerful tool for engineering spin and charge transport through controlled interlayer hybridization, opening new avenues for twisted magnetism and strongly correlated moiré physics.

cond-mat.mes-hall↗

arXiv2025

Electrochemical CO2 capture with pH-independent redox chemistry

Capture of anthropogenic CO2 is critical for mitigating climate change, and reducing the energy cost is essential for wide-scale deployment. Solubility of inorganic carbon in aqueous solutions depends on the pH, and electrochemical modulation of the pH has been investigated as a means of CO2 capture and release. However, reported methods incur unavoidable energy costs due to thermodynamic penalties. In this study, we introduce a pH-independent redox chemistry that greatly lowers the thermodynamic energy costs by changing the pH without directly changing the [H+]. We show that the redox reaction of TEMPO molecules modulates the pH for capture and release of CO2 in a flow cell with an energy cost as low as 2.6 kJ/mol of CO2 corresponding to 0.027 eV/molecule. A molecular model, supported by MD and DFT simulations, is proposed of how the pH is decreased by 7.6 while largely avoiding the entropic energy cost associated with increasing the [H+]. We believe that this work showcases the potential of pH-independent redox chemistries for practical and cost-effective CO2 capture.

physics.chem-ph↗

arXiv2024

TemperatureGAN: Generative Modeling of Regional Atmospheric Temperatures

Stochastic generators are useful for estimating climate impacts on various sectors. Projecting climate risk in various sectors, e.g. energy systems, requires generators that are accurate (statistical resemblance to ground-truth), reliable (do not produce erroneous examples), and efficient. Leveraging data from the North American Land Data Assimilation System, we introduce TemperatureGAN, a Generative Adversarial Network conditioned on months, locations, and time periods, to generate 2m above ground atmospheric temperatures at an hourly resolution. We propose evaluation methods and metrics to measure the quality of generated samples. We show that TemperatureGAN produces high-fidelity examples with good spatial representation and temporal dynamics consistent with known diurnal cycles.

cs.LG↗

arXiv2024

Atmospheric Pressure Ammonia Synthesis on AuRu Catalysts Enabled by Plasmon-Controlled Hydrogenation and Nitrogen-species Desorption

Ammonia is a key component of fertilizer and a potential clean fuel and hydrogen carrier. The Haber-Bosch process for ammonia synthesis consumes more than half of industrial hydrogen and contributes up to ~3% of global greenhouse gas emissions. Light-driven reactions via surface plasmon resonances offer a less energy-intensive pathway for ammonia production by altering reaction intermediates. Here, we report gold-ruthenium plasmonic bimetallic alloys for ammonia synthesis at room temperature and pressure, driven by visible light. We use colloidal synthesis to create AuRu$_x$ alloys (x=0.1, 0.2, 0.3) and disperse these nanoparticles on MgO supports for gas-phase ammonia synthesis. We observe a ~60 $μ$mol/g/h reactivity and ~0.12% external quantum efficiency on a AuRu$_0$$_.$$_2$ sample under 100 mW/cm$^2$ visible light. In-situ diffuse reflective infrared Fourier transform spectroscopic measurements show that hydrogenation of nitrogen adsorbates is accelerated under light compared to thermocatalysis. Combining wavelength-dependent reactivity and spectroscopic findings with semi-classical electromagnetic modeling, we show plasmonic bimetallic alloys expedite ammonia synthesis by aiding hydrogenation of adsorbed nitrogen species via plasmon-mediated hot electrons. Quantum mechanical calculations reveal hydrogen-assisted N$_2$ splitting in the excited state is key to activating the reaction under ambient conditions. Therefore, light or H$_2$ alone cannot dissociate N$_2$ -- the key bottleneck to breaking N$_2$'s triple bond. Our findings are consistent with recent hypotheses on how nitrogenase enzymes catalyze ammonia production at mild conditions and provide insights for sustainable photochemical transformations.

physics.chem-ph↗

arXiv2023

Imaging the electron charge density in monolayer MoS2 at the Ångstrom scale

Four-dimensional scanning transmission electron microscopy (4D-STEM) has recently gained widespread attention for its ability to image atomic electric fields with sub-Ångstrom spatial resolution. These electric field maps represent the integrated effect of the nucleus, core electrons and valence electrons, and separating their contributions is non-trivial. In this paper, we utilized simultaneously acquired 4D-STEM center of mass (CoM) images and annular dark field (ADF) images to determine the electron charge density in monolayer MoS2. We find that both the core electrons and the valence electrons contribute to the derived electron charge density. However, due to blurring by the probe shape, the valence electron contribution forms a nearly featureless background while most of the spatial modulation comes from the core electrons. Our findings highlight the importance of probe shape in interpreting charge densities derived from 4D STEM.

cond-mat.mtrl-sci↗

arXiv2021

EVGen: Adversarial Networks for Learning Electric Vehicle Charging Loads and Hidden Representations

The nexus between transportation, the power grid, and consumer behavior is more pronounced than ever before as the race to decarbonize the transportation sector intensifies. Electrification in the transportation sector has led to technology shifts and rapid deployment of electric vehicles (EVs). The potential increase in stochastic and spatially heterogeneous charging load presents a unique challenge that is not well studied, and will have significant impacts on grid operations, emissions, and system reliability if not managed effectively. Realistic scenario generators can help operators prepare, and machine learning can be leveraged to this end. In this work, we develop generative adversarial networks (GANs) to learn distributions of electric vehicle (EV) charging sessions and disentangled representations. We show that this model structure successfully parameterizes unlabeled temporal and power patterns without supervision and is able to generate synthetic data conditioned on these parameters. We benchmark the generation capability of this model with Gaussian Mixture Models (GMMs), and empirically show that our proposed model framework is better at capturing charging distributions and temporal dynamics.

cs.LG↗

arXiv2020

Application-Driven Synthesis and Characterization of Hexagonal Boron Nitride on Metal and Carbon Nanotube Substrates

Hexagonal boron nitride (h-BN) is unique among two-dimensional materials, with a large band gap (~6 eV) and high thermal conductivity (>400 W/m/K), second only to diamond among electrical insulators. Most electronic studies to date have relied on h-BN exfoliated from bulk crystals; however, for scalable applications the material must be synthesized by methods such as chemical vapor deposition (CVD). Here, we demonstrate single- and few-layer h-BN synthesized by CVD on single crystal platinum and on carbon nanotube (CNT) substrates, also comparing these films with h-BN deposited on the more commonly used polycrystalline Pt and Cu growth substrates. The h-BN film grown on single crystal Pt has a lower surface roughness and is more spatially homogeneous than the film from a polycrystalline Pt foil, and our electrochemical transfer process allows for these expensive foils to be reused with no measurable degradation. In addition, we demonstrate monolayer h-BN as an ultrathin, 3.33 $\unicode{x212B}$ barrier protecting MoS2 from damage at high temperatures and discuss other applications that take advantage of the conformal h-BN deposition on various substrates demonstrated in this work.

cond-mat.mtrl-sci↗

arXiv2019

Machine Learning for AC Optimal Power Flow

We explore machine learning methods for AC Optimal Powerflow (ACOPF) - the task of optimizing power generation in a transmission network according while respecting physical and engineering constraints. We present two formulations of ACOPF as a machine learning problem: 1) an end-to-end prediction task where we directly predict the optimal generator settings, and 2) a constraint prediction task where we predict the set of active constraints in the optimal solution. We validate these approaches on two benchmark grids.

cs.LG↗

arXiv2014

Temperature Gated Thermal Rectifier

Heat flow control is essential for widespread applications of heating, cooling, energy conversion and utilization. Here we demonstrate the first observation of temperature-gated thermal rectification in vanadium dioxide beams, in which an environment temperature actively modulates asymmetric heat flow. In this three terminal device, there are two switchable states, which can be accessed by global heating: Rectifier state and Resistor state. In the Rectifier state, up to 28% thermal rectification is observed. In the Resistor state, the thermal rectification is significantly suppressed (below 4%). This temperature-gated rectifier can have substantial implications ranging from autonomous thermal management of micro/nanoscale devices to thermal energy conversion and storage.

cond-mat.mtrl-sci↗

arXiv2010

High temperature thermoelectric response of double-doped SrTiO$_3$ epitaxial films

SrTiO$_3$ is a promising $n$-type oxide semiconductor for thermoelectric energy conversion. Epitaxial thin films of SrTiO$_3$ doped with both La and oxygen vacancies have been synthesized by pulsed laser deposition (PLD). The thermoelectric and galvanomagnetic properties of these films have been characterized at temperatures ranging from 300 K to 900 K and are typical of a doped semiconductor. Thermopower values of double-doped films are comparable to previous studies of La doped single crystals at similar carrier concentrations. The highest thermoelectric figure of merit ($ZT$) was measured to be 0.28 at 873 K at a carrier concentration of $2.5\times10^{21}$ cm$^{-3}$.

cond-mat.mtrl-sci↗

arXiv2009

Thermal Probing of Energy Dissipation in Current-Carrying Carbon Nanotubes

The temperature distributions in current-carrying carbon nanotubes have been measured with a scanning thermal microscope. The obtained temperature profiles reveal diffusive and dissipative electron transport in multi-walled nanotubes and in single-walled nanotubes when the voltage bias was higher than the 0.1-0.2 eV optical phonon energy. Over ninety percent of the Joule heat in a multi-walled nanotube was found to be conducted along the nanotube to the two metal contacts. In comparison, about eighty percent of the Joule heat was transferred directly across the nanotube-substrate interface for single-walled nanotubes. The average temperature rise in the nanotubes is determined to be in the range of 5 to 42 K per micro watt Joule heat dissipation in the nanotubes.

cond-mat.mes-hall↗

arXiv2008

Anomalously large measured thermoelectric power factor in Sr$_{1-x}$La$_x$TiO$_3$ thin films due to SrTiO$_3$ substrate reduction

We report the observation that thermoelectric thin-films of La-doped SrTiO3 grown on SrTiO3 substrates yield anomalously high values of thermopower to give extraordinary values of power factor at 300K. Thin-films of Sr0.98La0.02TiO3, grown via pulsed laser deposition at low temperature and low pressure (450C, 10-7Torr), do not yield similarly high values when grown on other substrates. The thin-film growth induces oxygen reduction in the SrTiO3 crystals, doping the substrate n-type. It is found that the backside resistance of the SrTiO3 substrates is as low (~12ohm/square) as it is on the film-side after film growth.

cond-mat.mtrl-sci↗