Design of a Low-Temperature Solar Heat Concentrator for the synthesis of ZnO nanostructures

 

Diagram and image of the CPC Solar Collector and SEM image of the synthesized ZnO

It has been widely reported that heat obtained from solar radiation can be applied to the synthesis of nanomaterials. In the case of zinc oxide (ZnO), the nanomaterial of interest in this study, it has previously been synthesized using high-temperature solar heat through Physical Vapor Deposition (PVD) methods.

In this work, a group of researchers from Mexico (CNyN-UNAM, CICESE, and UABC) propose evaluating a new approach for ZnO production through the design of a compound parabolic concentrator (CPC) with a cylindrical (tubular) receiver that generates heat at low temperatures.

The authors placed the precursors, zinc nitrate Zn(NO₃)₂ and sodium hydroxide (NaOH), inside the reactor where ZnO is produced. The reactor is in turn located within the CPC. In this setup, the collector serves both as a heat generator and as a reactor for synthesis.

The synthesis temperatures ranged from 50°C to 70°C. Using solar heat, pure ZnO crystalline clusters were obtained, with sizes ranging from 40.4 nm to 55.7 nm, and a band gap of 3.27 eV, slightly lower than that obtained by other methods at 50°C. The absorbance of the synthesized ZnO was 90%, regardless of the synthesis temperature.

This study confirmed that high-quality ZnO can be feasibly produced using low-temperature solar heat. This constitutes a new "green chemistry" approach and a renewable energy source for nanomaterial synthesis.

For more details, consult: Journal of Nanotechnology

NiFe Sulfide and Ti3C2 MXene Nanocomposites for High-Performance Seawater Electrolysis

 

Clean and sustainable energy sources are essential to address energy shortage and reduce carbon emissions caused by fossil fuels. One promising solution is the production of "green" hydrogen through water electrolysis using renewable energy sources such as solar and wind power.

The use of anion exchange membranes (AEM) has gained attention because it combines the low cost and high efficiency of alkaline water electrolysis with the benefits of proton exchange membrane (PEM) electrolysis, which is compatible with renewable energy sources.

However, freshwater is a limited resource, making direct seawater electrolysis an attractive alternative for future large-scale hydrogen production.  To date, satisfactory progress has not been made in obtaining systems based on anion exchange membranes. One major challenge is the development of highly stable electrocatalysts that can withstand both oxygen evolution reaction (OER) conditions and chloride-induced corrosion.

A research team in China developed a robust nanocomposite electrocatalyst by integrating MXene (Ti3C2) with Ni-Fe sulfides ((Ni,Fe)S2@Ti3C2). Using various characterizations and theoretical (DFT) calculations, they demonstrated that the strong interaction between (Ni,Fe)S2 and Ti3C2 regulates electron distribution, activating the OER. Additionally, the formation of Ti-O-Fe bonds prevents the loss of Fe species during the process, improving long-term stability. Additionally, the material effectively retains sulfates and features Ti3C2 groups that shield against chloride corrosion.

As a result, the (Ni,Fe)S2@Ti3C2 nanocomposite achieves high OER activity (1.598 V at 2 A cm-2) and remains stable for over 1,000 hours in seawater electrolysis. Moreover, when used as an anode along with a Ni Raney cathode (a nickel-based material with a porous structure that improves hydrogen production), the system operates at industrial current density (0.5 A cm-2) with 500 hours of durability, 70% efficiency, and an energy consumption of 48.4 kWh per kg of H2.

This study provides an effective methodology to address seawater electrolysis based on AEM technology, solving the challenges of catalyst degradation and chloride corrosion. 

More information in Nature Communications

Machine Learning Algorithms for Calculating the Electronic Structure of Molecules

 

Advances in nanotechnology largely rely on computational models that help us understand how materials behave at the atomic level. These tools are essential in physics, chemistry, and materials science, as they allow researchers to uncover new mechanisms and accelerate the design of innovative materials. However, one major challenge in this field is calculating the electronic structure of molecules—a process that is often slow and requires significant computing power.

This is where machine learning (ML) comes into play. ML, a branch of artificial intelligence, enables computers to learn from data and improve their performance over time. ML has become a promising alternative for studying molecules more quickly and efficiently thanks to its ability to identify patterns and make predictions.

In recent years, scientists have combined ML with density functional theory (DFT), a widely used method in computational chemistry. However, DFT can introduce errors in the results. To address this issue, researchers at the Massachusetts Institute of Technology developed an ML-based approach incorporating a more precise method called coupled-cluster singles, doubles, and perturbative triples or CCSD(T). While CCSD(T) is known for its accuracy, it is also computationally expensive, especially for larger molecules.

The researchers used data from 70 molecules with 7,440 different atomic configurations to train their model. The results were promising: they successfully calculated molecular formation enthalpies with a high degree of accuracy (showing differences of just 0.1-0.2 Kcal/mol compared with experimental data) and simulated infrared spectra that matched real measurements in peak position and intensity.

Although this technique has not yet been applied to crystalline materials, the authors believe this will be possible in the future. If so, it could transform how new materials are designed, paving the way for more advanced technologies.

For more information see: Nature Computational Science

Mechanochemistry in Space Promoted by Nanometeoroid Bombardment on an Asteroid

 

In the universe, phenomena occur that depend on micro- and nano-sized particles that, accelerated by the interplanetary magnetic field, impact and transform celestial bodies, producing surface changes—a process known as space weathering.

In 2018-2019, Japan's Hayabusa2 spacecraft obtained in situ infrared reflectance spectra of the surface of asteroid (162173) Ryugu, which showed an absorption band at ~2.7 μm corresponding to O-H vibrations in the asteroid’s phyllosilicates.

Through a directed impact, the Hayabusa2 spacecraft created a crater approximately 1 m deep on the asteroid’s surface. The infrared reflectance spectra near the crater revealed a more intense absorption band at ~2.7 μm, suggesting that the asteroid’s surface underwent a dehydration process (dissociation of O-H bonds).

To study the dissociation mechanism of these chemical bonds, the authors of this study used simulation methods with reactive molecular dynamics. The model simulated the bombardment of the asteroid’s phyllosilicates with impactors of fixed diameters (1 or 2 nm). In the absence of the magnetic fields of the interplanetary solar wind plasma, nanometeoroid impact velocities ranged from 10 to 20 km/s, leading to the dissociation of approximately 200 O-H bonds in the phyllosilicates. When the impactor was accelerated by the interplanetary magnetic field, impact velocity increased by an order of magnitude (up to ~300 km/s), dissociating over 1000 O-H bonds even with nanometeoroids of 1 nm in diameter.

The dehydration of the asteroid’s surface minerals was attributed to the kinetic energy of the impacts, which caused local heating exceeding 1000 Kelvin at the impact site.

This discovery contributes to understanding the evolution of asteroid chemical composition and the role of nanometeoroids in the interplanetary medium.

For more information, consult The Astrophysical Journal