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Phosphorus doped few layer WS2 flakes grown by chemical vapor deposition for hydrogen evolution reactions

Weighing unequal parameter importance and measurement expense in adaptive quantum sensing

A large class of experiments consists of measuring the parameters of physical models. In these experiments, the goal is to learn about these parameters as accurately and, often, quickly as possible. Adaptive experiment design works by yielding instrument control to Bayesian-based algorithms that alter instrument settings based on potential information gain about the parameters. By actively learning from data in real-time where to measure instead of determining instrument settings a priori, striking improvements in experiment efficiency are possible. Here, two new algorithms that improve upon previous implementations of adaptive experiment design are introduced. The first algorithm focuses on learning the model parameters that matter the most. The second algorithm considers the expense of a measurement and prioritizes information that can be gained at a lower cost. We demonstrate the remarkable improvement in efficiency and sensitivity that these algorithms provide for quantum sensing, specifically magnetometry, with nitrogen-vacancy centers in diamond. Most notably, we find an almost fivefold improvement in magnetic field sensitivity.

Addressing biomedical data challenges and opportunities to inform a large-scale data lifecycle for enhanced data sharing, interoperability, analysis, and collaboration across stakeholders

Abstract Biomedical discovery is fraught with challenges stemming from diverse data types and siloed analysis. In this study, we explored common biomedical data tasks and pain points that could be addressed to elevate data quality, enhance sharing, streamline analysis, and foster collaboration across stakeholders. We recruited fifteen professionals from various biomedical roles and industries to participate in sixty-minute semi-structured interviews, which involved an assessment of their challenges, needs, and tasks as well as a brainstorm exercise to validate each professional’s research process. We applied a qualitative analysis of individual interviews using an inductive-deductive thematic coding approach for emerging themes. We identified a common set of challenges related to procuring and validating data, applying new analysis techniques and navigating varied computational environments, distributing results effectively and reproducibly, and managing the flow of data across phases of the data lifecycle. Our findings emphasize the importance of secure data sharing and facilities for collaboration throughout the discovery process. Our identified pain points provide researchers with an opportunity to align workstreams and enhance research data lifecycles to conduct biomedical discovery. We conclude our study with a summary of key actionable recommendations to tackle multiomic data challenges across the stages and phases of biomedical discovery.

Estimation of channel capacity in CAT6 cable with circular waveguide modeling for future THz communication systems

Millimeter-wave and terahertz (THz) frequency bands are being explored in wired and wireless communication systems due to ongoing demands for increased data rates. Recently, it has been proposed that twisted-pair cables, already part of existing infrastructure, could be utilized for terabit-per-second data transmission by exploiting wireless THz radiation between the copper wires. THz radiation can be wirelessly transferred through the dielectric gap and the air gap in between the copper wires. The air gap and the dielectric material between the copper wires in a CAT6 (Category 6) cable can be considered a circular hollow-core waveguide, providing a suitable medium for the propagation of THz waves. Therefore, this work aims to estimate the data rate per distance by experimentally analyzing the copper circular waveguide. Furthermore, the impact of a waveguide radius is also examined. Waveguide propagation characteristics were experimentally analyzed using THz time-domain spectroscopy as well as on a simulation basis using CST (Computer Simulation Technology) Microwave Studio 2022. It was found that the radius of the waveguide has a significant effect on the transmission characteristics of the waveguide and the channel capacity for a longer range. The proposed waveguides achieved a maximum data rate in Tbps (terabits per second) for a few meters depending upon the diameter of the waveguide. This study investigates the propagation of THz waves through narrower spaces and explores the initial steps toward realizing the concept of a TDSL (Terabit Digital Subscriber Line) and future high-frequency communication systems.

On the build-up of effective hyperuniformity from large globular colloidal aggregates

A simple three-dimensional model of a fluid whose constituent particles interact via a short range attractive and long range repulsive potential is used to model the aggregation into large spherical-like clusters made up of hundreds of particles. The model can be thought of as a straightforward rendition of colloid flocculation into large spherical aggregates. We illustrate how temperature and particle density influence the cluster size distribution and affect inter- and intra-cluster dynamics. The system is shown to exhibit two well separated length and time scales, which can be tuned by the balance between repulsive and attractive forces. Interestingly, cluster aggregates at moderate/low temperatures approach a cluster glassy phase, whereas cluster particles retain a local liquid-like structure. These states present a strong suppression of density fluctuations for a significant range of relatively large wavelengths, meeting the criterion of effective disordered hyperuniform materials as far as the intercluster structure is concerned.

Effects of organic salts of virucidal and antiviral compounds from Nelumbo nucifera and Kaempferia parviflora against SARS-CoV-2

Nonequilibrium ac quantum transport in nanoscale transistors

This paper presents the small-signal (ac) nonequilibrium Green function (NEGF) simulation approach. By utilizing the solution of the steady-state (dc) NEGF solutions, the ac responses of the electrostatic potential and the electron density can be calculated. For the self-consistent solution considering the long range Coulomb interaction, the Poisson equation is coupled with the NEGF equations for both ac and dc cases. Especially, for the ac case, the NEGF and Poisson equations are fully coupled and solved in a single system matrix. In order to take into account the mode interaction fully, the real-space approach is presented. For the application of the ac quantum transport, a silicon based highly scaled nanosheet metal–oxide–semiconductor field-effect transistor is simulated under the ballistic transport approximation at room temperature. The simulation results at a low frequency are verified against the quasi-static results. We present the ac intrinsic performance of the device at the terahertz range. At the high-frequency range, the plasma instability from the ungated silicon region is investigated.

Large-scale sparse wave function circuit simulator for applications with the variational quantum eigensolver

The standard paradigm for state preparation on quantum computers for the simulation of physical systems in the near term has been widely explored with different algorithmic methods. One such approach is the optimization of parameterized circuits, but this becomes increasingly challenging with circuit size. As a consequence, the utility of large-scale circuit optimization is relatively unknown. In this work we demonstrate that purely classical resources can be used to optimize quantum circuits in an approximate but robust manner such that we can bridge the resources that we have from high performance computing and see a direct transition to quantum advantage. We show this through the sparse wave function circuit solvers, which we detail here, and demonstrate a region of efficient classic simulation. With such tools, we can avoid the many problems that plague circuit optimization for circuits with hundreds of qubits using only practical and reasonable classical computing resources. These tools allow us to probe the true benefit of variational optimization approaches on quantum computers, thus opening the window to what can be expected with near term hardware for physical systems. We demonstrate this with a unitary coupled cluster ansatz on various molecules up to 64 qubits with tens of thousands of variational parameters.

Early warning study of field station process safety based on VMD-CNN-LSTM-self-attention for natural gas load prediction

Optical sensing of nanoparticles employing porous silicon thin films

With the increasing consumption of nanomaterials in a variety of applications, our environment becomes more and more exposed to different kinds of (possibly toxic) nanomaterials having variable sizes and shapes, raising up the requirement to sense and monitor the presence of nanomaterials. Here, we propose and demonstrate a porous-silicon based optical sensing platform, capable of sensing nanoparticles of a given distribution of sizes and shapes, but independent of their chemical, mechanical, or electrical properties. A white light optical interference technique has been utilized to transduce nanoparticles trapped in the porous matrix into an optical signal. We have found an unusual optical sensing response that substantially increases the sensing bandwidth of the porous-silicon based optical sensor, which follows a Hill-equation type behavior that is characterized by a logarithmic response at low nanoparticle's concentration and saturation at high concentrations. These universal characteristics of the sensors are explained by the anomalous and limited diffusion of the nanoparticles via a quasi-1D geometry of the pore's matrix. Very low concentration of nanoparticles, of the order of few μg/ml, has been measured by this sensing technique.

Temperature and pressure effects on the surface structure of liquid gallium

Liquid gallium exhibits a unique metallic-covalent coexistence. Leveraging the volume constant pressure molecular dynamics method and a well-trained neural network potential, we study the evolution of liquid Ga surface structures under varying temperatures and pressures. Our study presents a schematic P–T phase diagram of the liquid surface. We observe symmetric static structure factor main peaks in the outermost layers of the liquid Ga surface compared with asymmetric ones for inner layers, indicating a simple liquid behavior and a lack of Ga2 dimers at the surface. We calculate the surface energy and the surface tension, which reveal non-monotonic changes. All these results provide a further insight into understanding the physics of the strange metal gallium.

Transitioning to sustainable energy and enhanced environmental quality in Somalia through renewable energy, globalisation and trade openness

Electron cyclotron resonance (ECR) plasmas: A topical review through representative results obtained over the last 60 years

The present review is devoted to the electron cyclotron resonance (ECR) plasmas. Considering that the electromagnetic wave absorption using the ECR concept has been employed since the 1960s, it becomes obvious that the coverage of the field of the ECR plasma physics, engineering, applications, and prospectives in its entirety would be a utopia in the context of a single report. Thus, the backbone of this work is a meaningful categorization of the wide applications of the ECR plasmas (Secs. III, V, and VI), by citing representative publications. The applications mainly refer to surface processes (etching, deposition, nano-construction, functionalization, cleaning, etc.), biotechnology, thrusters, and ion sources. The text also focuses on the details of different ECR setup designs, as they are tailored for specific projects. At the same time, physical parameters and the pros and cons of the ECR discharges are evaluated. This approach leads to a brief but telling compilation of the state of the art of the ECR-driven plasmas over the last 60 years (mainly 1960–2023) as well as of their prospective aspects. An introductory discussion on the ECR plasma history (Sec. I) and on the fundamental principles of the ECR heating, multipolar confinement, technical aspects, practical setups, and features of ECR plasmas (Sec. II) is given at the early beginning of this work, facilitating, thus, the consideration of the topics that follow. Special attention is paid to the distributed or modular ECR plasmas (Sec. IV) since they may mirror the road map for engineering the future ECR plasma systems. The review is throughout supported by future-proof classic and up-to-date bibliographies to encourage further reading and to fill any information gap that inevitably appears in the present work. It is underlined that the main claims or conclusions of most of the cited works are here reproduced intentionally. In other words, it is the pretension of the present article to become a quick, but pithy, guide on the ECR plasmas and on the results achieved over the last 60 years, for potential readers of different disciplines and various backgrounds. Finally, Sec. VII recaps the present perspective on the ECR plasmas, and it points to the ECR plasma prospectives.

The time-fractional Schrödinger equation in the context of non-Markovian dynamics with dissipation

In this paper, we examine the time-fractional Schrödinger equation from the perspective of non-Markovian dynamics in dissipative systems. First, we determine the range of the fractional derivative’s order by examining the memory properties of the time-fractional Schrödinger equation. Next, we employ the Jaynes–Cummings model to identify the appropriate mathematical form of the imaginary unit. Finally, we use the refined equation to study quantum teleportation under amplitude damping noise. It was found that the time-fractional Schrödinger equation without fractional operations on the imaginary unit i might be more suitable for describing non-Markovian dynamics in dissipative systems. Our research may provide a new perspective on the time-fractional Schrödinger equation, contributing to a deeper understanding and further development of time-fractional quantum mechanics.

Flower fertilization optimization algorithm with application to adaptive controllers

Abstract This article presents the Flower Fertilization Optimization Algorithm (FFO), a novel bio-inspired optimization technique inspired by the natural fertilization process of flowering plants. The FFO emulates the behavior of pollen grains navigating through the search space to fertilize ovules, effectively balancing exploration and exploitation mechanisms. The developed FFO is theoretically introduced through the article and rigorously evaluated on a diverse set of 32 benchmark optimization problems, encompassing unimodal, multimodal, and fixed-dimension functions. The algorithm consistently outperformed 14 state-of-the-art metaheuristic algorithms, demonstrating superior accuracy, convergence speed, and robustness across all test cases. Also, exploitation, exploration, and parameter sensitivity analyses were performed to have a comprehensive understanding of the new algorithm. Additionally, FFO was applied to optimize the parameters of a Proportional-Integral-Derivative (PID) controller for magnetic train positioning—a complex and nonlinear control challenge. The FFO efficiently fine-tuned the PID gains, enhancing system stability, precise positioning, and improved response times. The successful implementation underscores the algorithm’s versatility and effectiveness in handling real-world engineering problems. The positive outcomes from extensive benchmarking and practical application show the FFO’s potential as a powerful optimization tool. In applying multi-objective PID controller parameter optimization, FFO demonstrated superior performance with a sum of mean errors of 190.563, outperforming particle swarm optimization (250.075) and dynamic differential annealed optimization (219.629). These results indicate FFO’s ability to achieve precise and reliable PID tuning for control systems. Furthermore, FFO achieved competitive results on large-scale optimization problems, demonstrating its scalability and robustness.

Application of ultrafast x-ray lasers in studying the material structure under shock compression

For more than a century, x rays have been an essential tool in physics, chemistry, biology, materials science, and other subjects, considerably expanding our understanding of the fundamental structure of materials. X rays and electrons are among the most useful tools in the scientific toolbox for understanding the properties and functions of materials and molecules because of their capacity to penetrate matter and differentiate the structural changes at the atomic level. This information has a wide range of applications, including the development of innovative materials for electronics and clean energy technologies, as well as more effective pharmaceuticals with fewer side effects. A major new field in x-ray science has been opened by recent developments in ultrafast x-ray sources operating in the femtosecond (fs) to atto-second regimes. These advancements make possible element-specific probing of dynamics of charge particles and electronic configurations of electronic motions at fundamental timescales, sensitive probing of structural dynamics in materials at the atomic and electronic level at fundamental timescales, and efficient new methods for examining the coupling between atomic and electronic structural dynamics to investigate the material properties and functions. The most significant advancement has been the latest discovery of x-ray free-electron lasers (XFELs), of which there are now many new facilities either operational or under development worldwide. In addition, the development of high-order harmonic extreme ultraviolet sources based on lasers that operate in the atto-second regime as well as the tabletop and synchrotron-based laser-plasma x-ray sources that operate in the fs regime complement the achievements of XFEL. The current article provides a comprehensive discussion and future perspectives on the application of ultrafast XFELs to study the structure of matter under shock compression.

Polariton spectra under the collective coupling regime. II. 2D non-linear spectra

In our previous work [Mondal et al., J. Chem. Phys. 162, 014114 (2025)], we developed several efficient computational approaches to simulate exciton–polariton dynamics described by the Holstein–Tavis–Cummings (HTC) Hamiltonian under the collective coupling regime. Here, we incorporated these strategies into the previously developed Lindblad-partially linearized density matrix (L-PLDM) approach for simulating 2D electronic spectroscopy (2DES) of exciton–polariton under the collective coupling regime. In particular, we apply the efficient quantum dynamics propagation scheme developed in Paper I to both the forward and the backward propagations in the PLDM and develop an efficient importance sampling scheme and graphics processing unit vectorization scheme that allow us to reduce the computational costs from O(K2)O(T3) to O(K)O(T0) for the 2DES simulation, where K is the number of states and T is the number of time steps of propagation. We further simulated the 2DES for an HTC Hamiltonian under the collective coupling regime and analyzed the signal from both rephasing and non-rephasing contributions of the ground state bleaching, excited state emission, and stimulated emission pathways.

Modeling bulk diffusion of hydrogen in X70 pipeline steel

Perspective: Are glasses really frozen?

A glass is obtained by cooling a liquid fast enough to avoid crystallization. It is a solid with elastic constants and density similar to those of a crystal with the same composition. It is customarily assumed that the structure of a glass is frozen, and atoms are largely locked into a random, but specific, structure; while a small number of loosely bound atoms may be mobile, most atoms are frozen at room temperature and below. However, recent simulation studies on metallic glasses present a rather different picture. A very significant fraction (∼20%) of atoms are not frozen and locally mobile, even down to T = 0 partly because of quantum effect. Here, we describe these observations and discuss their implications on the nature of the glass structure and the origin of the glass transition.

Exploring atom-pairwise and many-body dispersion corrections for the BEEF-vdW functional

The Bayesian error estimation functional (BEEF-vdW) is widely used in surface science and catalysis, because it provides a balanced description of molecular, surface, and solid state systems, along with reliable error estimates. However, the nonlocal van-der-Waals density functional (vdW-DF2) employed in BEEF-vdW can be computationally costly and displays relatively low accuracy for molecular systems. Therefore, this work explores whether atom-pairwise and many-body dispersion treatments represent viable alternatives to using the vdW-DF2 functional with BEEF-vdW. To this end, we investigate the performance of commonly used atom-pairwise corrections [i.e., the Tkatchenko–Scheffler (TS) and the exchange-hole dipole moment (XDM) approaches] and many-body dispersion (MBD) treatments for molecular, surface, and solid-state systems. The results indicate that atom-pairwise methods such as TS and particularly XDM provide a good balance of cost and accuracy across all systems.