Evaluation of first-principles Hubbard and Hund corrected DFT for defect formation energies in non-magnetic transition metal oxides.

Recent advances have shown that first-principles DFT+ techniques, such as DFT++ with parameters from linear response, are capable of high bandgap accuracy in transition metal oxides at a fraction of the computational cost of hybrid functionals. Extending the use of these functionals to defect calculations could save computational resources, but there is limited knowledge on whether such techniques are capable of reliably modelling defect energies. Furthermore, the use of separate and values for the same atomic species in different chemical environments, within the same system, can introduce significant errors into formation energy calculations.

Charting Regions of Cobalt's Chemical Space with Maximally Large Magnetic Anisotropy: A Computational High-Throughput Study.

Magnetic anisotropy slows down magnetic relaxation and plays a prominent role in the design of permanent magnets. Coordination compounds of Co(II) in particular exhibit large magnetic anisotropy in the presence of low-coordination environments and have been used as single-molecule magnet prototypes. However, only a limited sampling of cobalt's vast chemical space has been performed, potentially obscuring alternative chemical routes toward large magnetic anisotropy.

Interlaboratory comparison of endotoxin contamination assessment of nanomaterials.

Endotoxin contamination is a significant hurdle to the translation of nanomaterials for biomedical applications. Multiple reports now describe that more than one-third of nanomaterials fail early pre-clinical assessment due to levels of endotoxin above regulatory requirements. Additionally, most immunological studies or studies testing nanomaterials in the literature lack inclusion of this assessment, which may lead to false-positive or false-negative results if high levels of the contaminant are present.

Video frame interpolation neural network for 3D tomography across different length scales.

Three-dimensional (3D) tomography is a powerful investigative tool for many scientific domains, going from materials science, to engineering, to medicine. Many factors may limit the 3D resolution, often spatially anisotropic, compromising the precision of the information retrievable. A neural network, designed for video-frame interpolation, is employed to enhance tomographic images, achieving cubic-voxel resolution.

Room-temperature quantum nanoplasmonic coherent perfect absorption.

Light-matter superposition states obtained via strong coupling play a decisive role in quantum information processing, but the deleterious effects of material dissipation and environment-induced decoherence inevitably destroy coherent light-matter polaritons over time. Here, we propose the use of coherent perfect absorption under near-field driving to prepare and protect the polaritonic states of a single quantum emitter interacting with a plasmonic nanocavity at room temperature. Our scheme of quantum nanoplasmonic coherent perfect absorption leverages an inherent frequency specificity to selectively initialize the coupled system in a chosen plasmon-emitter dressed state, while the coherent, unidirectional and non-perturbing near-field energy transfer from a proximal plasmonic waveguide can in principle render the dressed state robust against dynamic dissipation under ambient conditions.

Predicting the One-Particle Density Matrix with Machine Learning.

Two of the most widely used electronic-structure theory methods, namely, Hartree-Fock and Kohn-Sham density functional theory, require the iterative solution of a set of Schrödinger-like equations. The speed of convergence of such a process depends on the complexity of the system under investigation, the self-consistent-field algorithm employed, and the initial guess for the density matrix. An initial density matrix close to the ground-state matrix will effectively allow one to cut out many of the self-consistent steps necessary to achieve convergence.

Pectin/sodium alginate-based active film integrated with microcrystalline cellulose and geraniol for food packaging applications.

Biopolymer-based packaging films were prepared from pectin (PEC) and sodium alginate (SA), with the incorporation of 10 % MCC and different concentrations of geraniol (GER at 2.5, 5.0, 7.

Ultrafast photoluminescence and multiscale light amplification in nanoplasmonic cavity glass.

Interactions between plasmons and exciton nanoemitters in plexcitonic systems lead to fast and intense luminescence, desirable in optoelectonic devices, ultrafast optical switches and quantum information science. While luminescence enhancement through exciton-plasmon coupling has thus far been mostly demonstrated in micro- and nanoscale structures, analogous demonstrations in bulk materials have been largely neglected. Here we present a bulk nanocomposite glass doped with cadmium telluride quantum dots (CdTe QDs) and silver nanoparticles, nAg, which act as exciton and plasmon sources, respectively.

Fine-tuning covalent organic frameworks for structure-activity correlation via adsorption and catalytic studies.

In applications utilizing Covalent Organic Frameworks (COFs) for adsorption, the interplay between crystallinity (vis-à-vis surface area) and active sites still remains ambiguous. To address this, the present study introduces three isoreticular COFs-COP-N18 (covalent organic polymer with short-range order), COF-N18 (COF having long-range order), and COF-N27 (semicrystalline COF with pyridyl heteroatoms)-to explore this duality. Through systematic variations in structural order, pore volume, and pore-wall nitrogen content, we aim to establish a structure-activity relationship (SAR) for these COFs via adsorption and catalysis, using CO and I as probes.

Self-Consistent Field Approach for the Variational Quantum Eigensolver: Orbital Optimization Goes Adaptive.

We present a self-consistent field (SCF) approach within the adaptive derivative-assembled problem-tailored ansatz variational quantum eigensolver (ADAPT-VQE) framework for efficient quantum simulations of chemical systems on near-term quantum computers. To this end, our ADAPT-VQE-SCF approach combines the idea of generating an ansatz with a small number of parameters, resulting in shallow-depth quantum circuits with a direct minimization of an energy expression that is correct to second order with respect to changes in the molecular orbital basis. Our numerical analysis, including calculations for the transition-metal complex ferrocene [Fe (CH)], indicates that convergence in the self-consistent orbital optimization loop can be reached without a considerable increase in the number of two-qubit gates in the quantum circuit by comparison to a VQE optimization in the initial molecular orbital basis.

Machine-Learning-Assisted Construction of Ternary Convex Hull Diagrams.

In the search for novel intermetallic ternary alloys, much of the effort goes into performing a large number of calculations covering a wide range of compositions and structures. These are essential to building a reliable convex hull diagram. While density functional theory (DFT) provides accurate predictions for many systems, its computational overheads set a throughput limit on the number of hypothetical phases that can be probed.

Electrochemically Switchable Multimode Strong Coupling in Plasmonic Nanocavities.

The strong-coupling interaction between quantum emitters and cavities provides the archetypical platform for fundamental quantum electrodynamics. Here we show that methylene blue (MB) molecules interact coherently with subwavelength plasmonic nanocavity modes at room temperature. Experimental results show that the strong coupling can be switched on and off reversibly when MB molecules undergo redox reactions which transform them to leuco-methylene blue molecules.

Spin-Vibronic Dynamics in Open-Shell Systems beyond the Spin Hamiltonian Formalism.

Vibronic coupling has a dramatic influence over a large number of molecular processes, ranging from photochemistry to spin relaxation and electronic transport. The simulation of vibronic coupling with multireference wave function methods has been largely applied to organic compounds, and only early efforts are available for open-shell systems such as transition metal and lanthanide complexes. In this work, we derive a numerical strategy to differentiate the molecular electronic Hamiltonian in the context of multireference ab initio methods and inclusive of spin-orbit coupling effects.

Biodistribution and histological analysis of iron oxide-dextran nanoparticles in wistar rats.

Iron oxide nanoparticles (IONP) are showing promise in many biomedical applications. One of these- magnetic hyperthermia- utilizes externally applied alternating magnetic fields and tumor-residing magnetic nanoparticles to generate localized therapeutic temperature elevations. Magnetic hyperthermia is approved in Europe to treat glioblastoma and is undergoing clinical assessment in the United States to treat prostate cancer.

Nanoscale Gap-Plasmon-Enhanced Superconducting Photon Detectors at Single-Photon Level.

With a growing demand for detecting light at the single-photon level in various fields, researchers are focused on optimizing the performance of superconducting single-photon detectors (SSPDs) by using multiple approaches. However, input light coupling for visible light has remained a challenge in the development of efficient SSPDs. To overcome these limitations, we developed a novel system that integrates NbN superconducting microwire photon detectors (SMPDs) with gap-plasmon resonators to improve the photon detection efficiency to 98% while preserving all detector performance features, such as polarization insensitivity.

Multiple Carbon Morphologies Derived from Polyion Complex-Based Double Hydrophilic Block Copolymers as Templates and Phenol as a Carbon Precursor.

This study demonstrates the multiple carbon morphology forming abilities of two dissimilar polyion complex (PIC)-based double hydrophilic block copolymers (DHBC) along with three different phenol concentrations when subjecting the blend in aqueous media via a hydrothermal-assisted carbonization strategy. The morphological transition from worm-like to spherical along with granular is found for the blend of oppositely charged poly(ethylene glycol) (PEG)-conjugated poly(amino acid) block copolymers, PEG-poly(l-lysine) (PEG-PLys) and PEG-poly(glutamic acid) (PEG-PGlu), along with three different concentrations of phenol. In contrast, after mixing the combination of PEG-PLys and PEG-poly(aspartic acid) (PEG-PAsp) separately with three different phenol contents, elliptical to irregular to spherical structural transition occurred.

Stiffness and Atomic-Scale Friction in Superlubricant MoS Bilayers.

Molecular dynamics simulations, performed with chemically accurate machine-learning force fields, are used to demonstrate that layer stiffness has profound effects on the superlubricant state of two-dimensional van der Waals heterostructures. We engineer bilayers of different rigidity but identical interlayer sliding energy surface and show that a 2-fold increase in the intralayer stiffness reduces the friction by a factor of ∼6. Two sliding regimes as a function of the sliding velocity are found.

Testing the Effects of Magnetic Hyperthermia in 2D Cell Culture.

Magnetic hyperthermia is an innovative thermal therapy for the treatment of solid malignancies. This treatment approach utilizes magnetic nanoparticles that are stimulated by alternating magnetic fields to induce temperature elevations in tumor tissue, resulting in cell death. Magnetic hyperthermia is clinically approved for treating glioblastoma in Europe and is undergoing clinical evaluation for prostate cancer in the United States.

A Method for the In Vitro Cytotoxicity Assessment of Anti-cancer Compounds and Materials Using High Content Screening Analysis.

To date, there is a large bottleneck associated with cancer drug design and development: a lack of appropriate methodologies for screening their potential toxicity. This issue not only causes a high attrition rate for these compounds but also slows down the drug discovery process in general. To overcome this problem, robust, accurate, and reproducible methodologies for assessing anti-cancer compounds are essential.

A Method for Culturing 3D Tumoroids of Lung Adenocarcinoma Cells at the Air-Liquid Interface.

Three-dimensional (3D) tumor spheroids and tumoroids are among the most exploited cell culture methods in the lung cancer field, finding applications in the investigation of tumor growth and proliferation, invasion, and drug screening. However, 3D tumor spheroids and tumoroids cannot fully mimic the architecture of the human lung adenocarcinoma tissue and, in particular, the direct contact of the lung adenocarcinoma cells with the air, as they lack polarity. Our method allows to overcome this limitation by enabling to grow tumoroids of lung adenocarcinoma cells and healthy lung fibroblasts at the Air-Liquid Interface (ALI).

Three-Dimensional Spheroids for Cancer Research.

In vitro cell culture is one of the most widely used tools used today for increasing our understanding of various things such as protein production, mechanisms of drug action, tissue engineering, and overall cellular biology. For the past decades, however, cancer researchers have relied heavily on conventional two-dimensional (2D) monolayer culture techniques to test a variety of aspects of cancer research ranging from the cytotoxic effects of antitumor drugs to the toxicity of diagnostic dyes and contact tracers. However, many promising cancer therapies have either weak or no efficacy in real-life conditions, therefore delaying or stopping altogether their translating to the clinic.

ZnSe and ZnTe as tunnel barriers for Fe-based spin valves.

Owing to their use in the optoelectronic industry, we investigate whether ZnSe and ZnTe can be utilised as tunnel barrier materials in magnetic spin valves. We perform electronic structure and linear response transport calculations based on self-interaction-corrected density functional theory for both Fe/ZnSe/Fe and Fe/ZnTe/Fe junctions. In the Fe/ZnSe/Fe junction the transport is tunneling-like and a symmetry-filtering mechanism is at play, implying that only the majority spin electrons with symmetry are transmitted with large probability, resulting in a potentially large tunneling magnetoresistance (TMR) ratio.

Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations.

Having served as a playground for fundamental studies on the physics of d and f electrons for almost a century, magnetic molecules are now becoming increasingly important for technological applications, such as magnetic resonance, data storage, spintronics and quantum information. All of these applications require the preservation and control of spins in time, an ability hampered by the interaction with the environment, namely with other spins, conduction electrons, molecular vibrations and electromagnetic fields. Thus, the design of a novel magnetic molecule with tailored properties is a formidable task, which does not only concern its electronic structures but also calls for a deep understanding of the interaction among all the degrees of freedom at play.