Paper & Patents

Despite recent advances in colloidal quantum dot (CQD) photovoltaics, several challenges persist and hinder further improvements. In particular, the Fermi level mismatch between the iodide-treated photoactive and thiol-treated hole-transporting CQD layers creates an unfavorable energy band for hole collection. Furthermore, the numerous surface cracks in the thiol-treated CQD layer facilitate direct contact between the photoactive CQD layer and the metal electrode, consequently leading to reduced device performance. To address these issues, a polycatechol functionalized MXene (PCA-MXene) that can serve both as a dopant and an interlayer for CQD photovoltaics is developed. By achieving a uniformly dispersed mixture in a butylamine solvent, PCA-MXene enables the effective combination of MXene and CQDs. This results in the modification of the work function of CQDs and the modulation of the energy band alignment, ultimately promoting enhanced hole extraction. Moreover, the PCA-MXene employed as an interlayer effectively covers the surface cracks present in the thiol-treated CQD layer. This coverage inhibits both metal electrode penetration and moisture intrusion into the device. Owing to these advantages, the CQD photovoltaics incorporating PCA-MXene achieve a power conversion efficiency (PCE) of 13.6%, accompanied by enhanced thermal stability, in comparison to the reference device with a PCE of 12.8%.

In recent years, graph neural network (GNN) based approaches have emerged as a powerful technique to encode complex topological structure of crystal materials in an enriched repre- sentation space. These models are often supervised in nature and using the property-specific training data, learn relation- ship between crystal structure and different properties like formation energy, bandgap, bulk modulus, etc. Most of these methods require a huge amount of property-tagged data to train the system which may not be available for different prop- erties. However, there is an availability of a huge amount of crystal data with its chemical composition and structural bonds. To leverage these untapped data, this paper presents CrysGNN, a new pre-trained GNN framework for crystalline materials, which captures both node and graph level structural information of crystal graphs using a huge amount of unla- belled material data. Further, we extract distilled knowledge from CrysGNN and inject into different state of the art prop- erty predictors to enhance their property prediction accuracy. We conduct extensive experiments to show that with distilled knowledge from the pre-trained model, all the SOTA algo- rithms are able to outperform their own vanilla version with good margins. We also observe that the distillation process provides significant improvement over the conventional ap- proach of finetuning the pre-trained model. We will release the pre-trained model along with the large dataset of 800K crys- tal graph which we carefully curated; so that the pre-trained model can be plugged into any existing and upcoming models to enhance their prediction accuracy.

To enable efficient energy conversion and storage, the development of effective electrocatalysts for the oxygen evolution reaction (OER) is crucial. Single-atom catalysts (SACs) with 100% active sites for the OER are highly promising in this regard. In this study, we investigated the OER activities of Co single atoms (CoSA) adsorbed on metallic MXenes, including Ti3C2O2 and Mo2CO2, both in their stoichiometric form and with oxygen vacancies (Ov), using spin-polarized first-principles-based calculations. The rate-determining step in each case was found to be the conversion of *O from *OH. Our calculations showed that the presence of oxygen vacancies decreased the OER activity in CoSA@Ti3C2O2-δ, resulting in a higher overpotential, while it increased the OER activity in CoSA@Mo2CO2. We explain such results using insights from the density of states, charge density variation, and bonding analysis via crystal orbital Hamilton population. We also show that the hybridization between the d-states of the CoSA and the transition metal sites of the catalyst-bed (Ti/Mo) plays a decisive role.

We present an efficient and scalable computational approach for conducting projected population analysis from real-space finite-element (FE)-based Kohn–Sham density functional theory calculations (DFT-FE). This work provides an important direction toward extracting chemical bonding information from large-scale DFT calculations on materials systems involving thousands of atoms while accommodating periodic, semiperiodic, or fully nonperiodic boundary conditions. Toward this, we derive the relevant mathematical expressions and develop efficient numerical implementation procedures that are scalable on multinode CPU architectures to compute the projected overlap and Hamilton populations. The population analysis is accomplished by projecting either the self-consistently converged FE discretized Kohn–Sham orbitals or the FE discretized Hamiltonian onto a subspace spanned by a localized atom-centered basis set. The proposed methods are implemented in a unified framework within the DFT-FE code where the ground-state DFT calculations and the population analysis are performed on the same FE grid. We further benchmark the accuracy and performance of this approach on representative material systems involving periodic and nonperiodic DFT calculations with LOBSTER, a widely used projected population analysis code. Finally, we discuss a case study demonstrating the advantages of our scalable approach to extract the quantitative chemical bonding information of hydrogen chemisorbed in large silicon nanoparticles alloyed with carbon, a candidate material for hydrogen storage.

BaTiO3 (BTO) typically demonstrates a strong n-type character with absorption only in the ultraviolet (λ ≤ 390 nm) region. Extending the applications of BTO to a range of fields necessitates a thorough insight into how to tune its carrier concentration and extend the optical response. Despite significant progress, simultaneously inducing visible-light absorption with a controlled carrier concentration via doping remains challenging. In this work, a p-type BTO with visible-light (λ ≤ 600 nm) absorption is realized via iridium (Ir) doping. Detailed analysis using advanced spectroscopy/microscopy tools revealed mechanistic insights into the n- to p-type transition. The computational electronic structure analysis further corroborated this observation. This complementary data helped establish a correlation between the occupancy and the position of the dopant in the band gap with the carrier concentration. A decrease in the Ti3+ donor-level concentration and the mutually correlated oxygen vacancies upon Ir doping is attributed to the p-type behavior. Due to the formation of Ir3+/Ir4+ in-gap energy levels within the forbidden region, the optical transition can be elicited from or to such levels, resulting in visible-light absorption. This newly developed Ir-doped BTO is a promising semiconductor with imminent applications in solar fuel generation and optoelectronics.

The Hall scattering factor of Sc2CF2, Sc2CO2 and Sc2C(OH)2 is calculated using Rode’s iterative approach by solving the Boltzmann transport equation. This is carried out in conjunction with calculations based on density functional theory. The electrical transport in Sc2CF2, Sc2CO2 and Sc2C(OH)2 is modelled by accounting for both elastic (acoustic and piezoelectric) and inelastic (polar optical phonon) scattering. Polar optical phonon (POP) scattering is the most significant mechanism in these MXenes. We observe that there is a window of carrier concentration where Hall factor acts dramatically; Sc2CF2 obtains an incredibly high value of 2.49 while Sc2CO2 achieves a very small value of approximately 0.5, and Sc2C(OH)2 achieves the so called ideal value of 1. We propose in this paper that such Hall factor behaviour has significant promise in the field of surface group identification in MXenes, an issue that has long baffled researchers.

The record-high responsivity of 0.34 A W−1 is achieved by flexible and transparent Ti3C2Tx-platformed photodetectors (PDs) in self-powered operation. Transparent technology is suitable for future human electronic interface. The Ti3C2Tx/3D semiconductor (Tx = –F, –OH, –O, –Cl) structure has gained considerable attention in the design of high-performance optoelectronic devices. In particular, the unique mechanical and hydrophilic properties of Ti3C2Tx are favored for large-scale flexible photodetectors. However, the self-powered operation and transparency have remained unexplored for Ti3C2Tx/3D semiconductor-based flexible PDs. To access portable and implantable electronic devices, Ti3C2Tx was comprehensively utilized as an active electrical window and charge-transporting layer for transparent PDs. Density functional theory revealed the better charge-transporting channel due to the Ti3C2Tx-functional layer, resulting in the elevated pyro-phototronic current of Ti3C2Tx/Al2O3/ZnO/Ti3C2Tx/ITO/polyethylene terephthalate (PET) PDs. Based on the ultrafast photo-response of the PD (8 μs), an optically transparent (> 68 %) communication system was developed. The flexible and transparent PD (TPD) can process the incident Morse codes of encrypted optical signals to text (“MXENE TPD”) information effectively. This study combines the transparency and self-reliant characteristics into a wearable MXene/bulk semiconductor-based PD, exhibiting great potential for applications in energy-efficient imaging, communication, and health monitoring systems.

Hydrogen-based fuels demand high-density storage that can operate at ambient temperatures. Pd and its alloys are the most studied metal hydrides for hydrogen fuel cell applications. This study presented an alternative Pd alloy for hydrogen storage that can store and release hydrogen at room temperature. The surface of the most commonly studied Pd (110) was modified with Au and Rh such that the hydrogen adsorption energy was 0.49 eV and the release temperature was 365 K. Both values are quite close to the optimal values for the adsorption energy and release temperature of a hydrogen fuel cell in real use. We further show that the modified Pd (110) surface has significantly stronger oxygen evolution reaction (OER) catalytic properties than the pure Pd (110) surface.

Finding a suitable material for hydrogen storage at ambient atmospheric conditions is challenging for material scientists and chemists. In this work, using a first principles based cluster expansion approach, the hydrogen storage capacity of Ti2AC (A = Al, Ti, Cr, Mn, Fe, Co, Ni, Cu, and Zn) MAX phase and its alloys were studied. We found that hydrogen is energetically stable in Ti-A layers in which the tetrahedral site consisting of one A atom and three Ti atoms is energetically more favorable for hydrogen adsorption than other sites in the Ti-A layer. Ti2CuC has the highest hydrogen adsorption energy than other Ti2AC phases. We find that 83.33% Cu doped Ti2AlxCu1-xC alloy structure is both energetically and dynamically stable and can store 3.66 wt% hydrogen at ambient atmospheric conditions, which is higher than both Ti2AlC and Ti2CuC phase. These findings indicate that the hydrogen capacity of the MAX phase can be significantly improved by doping an appropriate atom species.

Spin gapless semiconductors exhibit a finite band gap for one spin channel and a closed gap for another spin channel, and they have emerged as a new state of magnetic materials with a great potential for spintronic applications. The first experimental evidence for spin gapless semiconducting behavior was observed in an inverse Heusler compound Mn2CoAl. Here, we report a detailed investigation of the crystal structure and anomalous Hall effect in Mn2CoAl using experimental and theoretical studies. The analysis of the high-resolution synchrotron x-ray diffraction data shows antisite disorder between Mn and Al atoms within the inverse Heusler structure. The temperature-dependent resistivity shows semiconducting behavior and follows Mooij's criteria for disordered metal. The scaling behavior of the anomalous Hall resistivity suggests that the anomalous Hall effect in Mn2CoAl is primarily governed by an intrinsic mechanism due to the Berry curvature in momentum space. The experimental intrinsic anomalous Hall conductivity (AHC) is found to be ∼35 S/cm, which is considerably larger than the theoretically predicted value for ordered Mn2CoAl. Our first-principles calculations conclude that the antisite disorder between Mn and Al atoms enhances the Berry curvature and hence the value of intrinsic AHC, which is in very good agreement with the experiment.