A recent study published in ACS Publications introduces a novel approach to predicting relative binding free energy (RBFE) through the identification of quasi-bound states. Traditionally, RBFE calculations are computationally intensive, posing challenges for large-scale drug discovery and molecular design. This new method leverages intermediate, metastable configurations known as quasi-bound states to streamline prediction processes and improve accuracy.

Researchers have shown that quasi-bound states—structures that are neither fully bound nor completely unbound—play a critical role in characterizing the thermodynamic landscape of molecular interactions. By focusing on these transient conformations, the study reveals a strong correlation between the stability of the quasi-bound state and the relative binding free energy of two ligands. This insight opens new avenues for approximating RBFE without relying solely on full-scale molecular dynamics simulations.

Using enhanced sampling techniques and statistical mechanics, the team demonstrated that identifying and analyzing quasi-bound states offers a more computationally efficient alternative. The approach accurately estimates RBFE differences in a variety of protein-ligand systems, validating the method against experimental benchmarks and high-fidelity simulation results.

This development holds significant implications for rational drug design, enabling faster screening of potential therapeutic compounds while maintaining predictive power. By incorporating quasi-bound state analysis into computational pipelines, researchers and pharmaceutical developers can expedite the early stages of drug development with fewer computational resources.

The findings mark a step forward in the ongoing effort to refine molecular modeling techniques for biomedical and pharmaceutical applications.

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A recent study published in Nature explores how the choice of density functional in computational models can significantly influence predictions of antipolar distortions in complex oxides—a finding that has broad implications for the design and understanding of functional materials.

Density Functional Theory (DFT) is a cornerstone of modern materials science, widely used to investigate the electronic structure of solids. At its core is the use of approximations known as exchange-correlation functionals, which are essential for calculating material properties. However, not all functionals perform uniformly across different material classes or physical phenomena.

In this study, researchers evaluated the sensitivity of antipolar displacements—subtle, symmetry-breaking shifts in atomic positions that can influence dielectric, piezoelectric, and structural properties—to the choice of density functional. Focusing on layered perovskite oxides, the team systematically tested a range of widely used functionals, including local density approximation (LDA), generalized gradient approximation (GGA), and hybrid functionals.

The findings revealed an unexpected and pronounced dependence of antipolar distortions on the specific functional employed. For example, while LDA and GGA functionals predicted relatively subdued antipolar behavior, certain hybrid functionals produced significantly larger distortions, even altering the qualitative nature of the ground state structure.

This result highlights a critical consideration for researchers working in materials design: predictions of structural instabilities and functional properties can vary not just quantitatively, but qualitatively, depending on the computational methods chosen. Such sensitivity could impact the theoretical screening of materials for applications in ferroelectrics, multiferroics, and high-temperature superconductivity, where precise control of atomic-scale structures plays a pivotal role.

The authors suggest that future computational studies incorporate careful benchmarking against experimental data and consider multiple functionals to ensure robust predictions. As materials discovery becomes increasingly reliant on high-throughput computation, understanding and mitigating these methodological dependencies will be key to accelerating innovation in electronic, energy, and quantum materials.

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Volektra, an innovative technology company specializing in sustainable energy solutions, has successfully secured a new round of funding to accelerate commercialization of its Virtual Magnet Motor (VMM). Designed for application across mobility, industrial, and defense sectors, the patented motor technology represents a breakthrough in energy efficiency and power density.

The Virtual Magnet Motor operates without reliance on rare-earth materials, using proprietary software and hardware systems to create a controlled magnetic flux. This approach enables significant improvements in torque, efficiency, and scalability, positioning the VMM as a competitive alternative to conventional electric motors and internal combustion engines.

With this fresh infusion of capital, Volektra plans to expand prototyping, pilot deployments, and partnerships with key players in automotive, logistics, and defense industries. The company is also investing in manufacturing capabilities and engineering talent to support its go-to-market strategy.

According to Volektra, the VMM’s advantages include reduced operational costs, lower environmental impact, and enhanced performance under demanding conditions. These attributes make it well-suited for integration into electric vehicles, unmanned systems, industrial automation, and mission-critical defense platforms.

Investors in this round include leading venture capital firms and strategic partners focused on clean energy and advanced mobility technologies. The funding reflects growing confidence in the VMM’s commercial potential and Volektra’s ability to disrupt traditional motor systems with a more efficient, sustainable alternative.

As global industries seek to meet stricter emissions standards and reduce dependence on costly rare-earth elements, Volektra’s Virtual Magnet Motor offers a timely and transformative solution.

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Advancements in wave energy conversion technologies have led to the development of more efficient and robust systems for harnessing renewable ocean energy. One such breakthrough is detailed in a recent study titled “Modeling, analysis and control of an inertial wave energy converter and hydraulic power take-off unit,” published in Nature. The study focuses on a novel inertial wave energy converter (WEC) integrated with a hydraulically driven power take-off (PTO) system, showcasing promising results in performance optimization and dynamic control.

The kinetic energy of ocean waves presents a significant, yet underutilized, source of renewable energy. Converting this energy into usable electricity efficiently and reliably is a primary challenge for researchers and engineers in the field. This study addresses that challenge by introducing a comprehensive dynamic model of an advanced WEC system that leverages inertial motion and hydraulic mechanisms.

The WEC employs a buoyant floating structure coupled with a pendulum-based inertial mass. As ocean waves cause oscillatory movement, the relative motion between the buoy and the pendulum is transferred to a hydraulic PTO system. This PTO then converts mechanical energy into fluid pressure, which is ultimately transformed into electricity via a hydraulic motor and generator system.

To optimize performance, the researchers developed a control strategy rooted in nonlinear system modeling. This includes capturing the effects of wave excitation and radiation forces, damping mechanisms, and the highly dynamic interaction between the converter and the hydraulic PTO. The proposed control algorithms are designed to maximize energy extraction over a wide range of sea states while ensuring system stability and structural integrity.

Simulation results validate the effectiveness of the control scheme, demonstrating improved energy capture compared to traditional passive systems. Furthermore, the modular design of the hydraulic PTO allows for scalable deployment, making it suitable for a variety of marine energy applications.

The study contributes significantly to the growing field of ocean energy by offering a viable solution for increasing energy yield and reliability in WEC systems. Moreover, the integration of advanced control techniques with robust mechanical design highlights a path forward for commercialization and real-world deployment of wave energy technologies.

Title: Advances and Challenges in Calculating Solid–Liquid Interfacial Free Energy through Computer Simulations
Source: ACS Publications

The accurate determination of solid–liquid interfacial free energy is critical for understanding and predicting a wide range of material behaviors, from crystal growth and melting to solidification processes. This thermodynamic property governs how materials transition between solid and liquid phases and influences the morphology and dynamics of solidification fronts.

Recent developments in computational methods have enabled scientists to estimate interfacial free energy with unprecedented precision. Techniques such as molecular dynamics (MD), Monte Carlo simulations, and enhanced sampling methods have played a key role in these advances. These simulations allow researchers to model atomic-level interactions and track how nucleation and growth occur under different thermodynamic conditions.

Despite these advances, accurately calculating interfacial free energy remains a significant challenge. Key difficulties include the need for high computational resources, the selection of appropriate order parameters, the management of finite-size effects, and the accurate modeling of long-range interactions. Additionally, results often depend on the choice of interfacial orientation and material properties, making standardization complex.

Current research is focused on overcoming these obstacles through improved algorithms, machine learning approaches, and better integration of experimental data. As our understanding deepens, computational simulations are expected to play an increasingly important role in the design and discovery of new materials with tailored interfacial properties.

For a more comprehensive overview, you can read the full article on ACS Publications.