Reconfigurable Ferroelectric Field-Effect Transistors with Single-Walled Carbon Nanotube Channels

 

The rapid development of the internet and artificial intelligence has accelerated data generation, imposing greater demands on data processing. To process data efficiently, it is necessary to reduce device dimensions and operating voltage, thereby lowering energy consumption.

However, with current field-effect transistor (FET) technology, such as silicon complementary metal-oxide-semiconductor (CMOS) transistors, these improvements have met with physical limitations: when transistors become too small, electrical control issues arise. More specifically, size reduction is hindered by effects associated with short channel length; while lowering the voltage below 1 V is constrained by the Boltzmann limit, which depends on the constant ratio between the interaction potential and the mean free path of charge carriers.

Considering these limitations, reconfigurable transistors—capable of changing their operation after fabrication—offer a promising alternative. A special case is reconfigurable FeFETs, which can operate as either p-type or n-type transistors as needed.

A research team from Korea, the U.S., and China developed this type of devices using highly aligned single-walled carbon nanotubes (SWCNTs) as semiconductor channels and an innovative ferroelectric material (aluminum–scandium nitride). These devices exhibit ambipolar carrier characteristics with high and well-balanced ON-state currents (~270 μA μm−1 at a drain voltage of 3 V) and ON/OFF ratios greater than 105, along with wide memory windows and excellent retention capability. Furthermore, they feature ternary memory capability (able to store -1, 0, or +1 instead of just 0 and 1). This means that more compact and efficient circuits can be built compared with those based on conventional silicon.

Further information in: Nature Communications

Homoepitaxial Growth of MoS₂ in a Rhombohedral Stacking

 

Two-dimensional (2D) materials possess unique properties that make them suitable for implementation in various technological devices. Manipulating and modifying the stacking order between layers is a way to tune their properties.

Two-dimensional transition metal dichalcogenides (TMDs) are important candidates for transistor downscaling. These materials are typically stacked in an arrangement known as 2H, consisting of two monolayers rotated by 180°. Inducing an alternative artificial stacking (for example, the rhombohedral stacking known as 3R, in which three monolayers are shifted without rotation) imparts exotic properties such as ferroelectricity, superconductivity, among others. However, inducing this type of stacking is not straightforward, due to the high thermodynamic stability of the 2H stacking.

Scientists from Chinese universities have succeeded in obtaining large-scale (on the order of centimeters) molybdenum disulfide (MoS₂) with 3R stacking. Using chemical vapor deposition (CVD), they deposited a MoS₂ monolayer onto a sapphire substrate. Once the first monolayer was deposited, the nucleation process of the subsequent monolayer became crucial to achieving the desired stacking, since once formed, it cannot be rotated.

This study proposes, through density functional theory (DFT) calculations, that defects known as Mo antisites promote 3R stacking over 2H. Experimentally, the presence of such defects was demonstrated in samples with 3R stacking, while no such defects were observed in samples with 2H stacking, corroborating the proposed growth mechanism. The obtained samples were shown to exhibit ferroelectricity via piezoresponse force microscopy (PFM).

Since 3R-MoS₂ is a semiconductor with ferroelectric characteristics, it is proposed for the fabrication of ferroelectric semiconductor field-effect transistors (FeS-FETs). Moreover, the advantage of obtaining high-quality, large-area samples ensures device reproducibility.

For more information go to:

nature materials

Flexible Selenium Nanowires with Tuneable Electronic Bangaps

 

Changes in the size and geometric shape of nanoparticles allow for the manipulation of semiconductor properties without altering their chemical composition. However, a challenge remains: depending on the synthesis method, the size distribution of the nanoparticles can vary.

The use of nanotube molds to form selenium nanowires is part of a broader strategy that employs nanostructured templates to control the growth of one-dimensional nanomaterials.

Although selenium naturally crystallizes into elongated structures due to its anisotropic nature, templates such as carbon nanotubes (CNTs), anodic aluminum oxide, or other hollow nanostructures enable precise control over the nanowire’s unidirectional growth, size, orientation, and uniformity, while also protecting the material during formation. These core–shell structures, with a selenium core and a protective nanotube shell, have applications in nanoelectronics, photoconductors, and energy storage.

British researchers discovered distinct structural phases of selenium when confined within carbon and boron nitride nanotubes, observing remarkable structural plasticity in nanowires with diameters ranging from 0.4 to 3.0 nm. The experiment used one sample of boron nitride nanotube (BNNT) and four carbon nanotube (CNT) samples of different diameters, all under identical experimental conditions. Selenium was sublimed to fill the nanotubes, forming Se@CNT and Se@BNNT structures, in order to study exclusively the effect of nanotube diameter on the resulting selenium structure.

They found that the bandgap width of these nanowires, between 2.2 and 2.5 eV, depends non-monotonically on the diameter of the nanotube. This is due to conformational distortions in the selenium chains counteracting quantum confinement effects at sub-nanometric scales.

The authors developed a one-dimensional phase diagram that predicts the atomic structure of selenium as a function of the nanotube diameter, regardless of the host nanotube’s chemical composition. This demonstrates that confinement within nanotubes enables precise tuning of the structure and electronic properties of selenium. The materials were characterized using advanced electron microscopy and electron energy loss spectroscopy (EELS) to determine the bandgaps.

These nanoscale discoveries pave the way for the development of advanced, miniaturized, tunable, and flexible electronic components, such as transistors, optical sensors, and photovoltaic systems.

For further details, go to: Advanced Materials

Bipolar Cells of the Eye Treated with Plasmonic Gold Nanorods and Activated with Infrared Laser to Restore Vision

 

Age-related macular degeneration (AMD) and retinitis pigmentosa are major causes of vision loss. Worldwide, AMD affects approximately 200 million people, and retinitis pigmentosa 1.5 million people.

In both conditions, there is a reduction in the sensitivity to light of retinal photoreceptors; however, certain retinal neurons such as bipolar and ganglion cells remain functional. This has sparked interest in research aimed at restoring vision.

A study conducted by researchers at Brown University in the United States points to a new type of visual prosthesis system that combines the use of plasmonic gold nanorods with a small laser device integrated into eyeglasses. 

The researchers injected gold nanorods into the vitreous humor of mice eyes, where the particles incorporated into the retina and into bipolar and ganglion cells. A scanning laser with wavelengths in the near-infrared region of the visible spectrum and a beam size of 20 microns was then used to focus infrared light onto the nanoparticles, generating a small amount of heat that activated the bipolar and ganglion cells. This activation pattern mimicked the natural visual signals processed by the brain through photoreceptor pulses.

Laser stimulation led to increased activity in the visual cortex of the mice indicating that previously absent visual signals were being transmitted and processed by the brain. 

The study found no signs of toxicity or inflammation over several months.

This finding suggests the potential application of a similar technology in humans. The use of near-infrared light, rather than visible light, is non-invasive and does not interfere with residual vision that the patient may still retain. Although further testing is needed before clinical application, the findings point to a less invasive option for vision restoration.

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ACS Nano

Functional groups regulate ion concentration and pH in nanopores

 

To understand the chemical reactions occurring inside the nanopores of nanostructured materials—whether synthetic or natural, such as those found in membranes or ion channels in biological systems—it is essential to determine the ion concentration within them. For this purpose, nanopores are functionalized with specific chemical groups.

Until now, it had not been possible to determine how functional groups influence ion concentration inside nanopores.

In this study, a group of researchers from the United States reported the development of a core–shell-type plasmonic nanosensor, consisting of a gold nanorod coated with mesoporous silica functionalized with phenyl and methyl groups. This nanosensor can measure the local concentration of protons, anions (such as phosphates, nitrates, sulfates, and arsenates), as well as cations (such as mercury, lead, and copper) in functionalized nanopores. The measurements were performed using Surface-Enhanced Raman Spectroscopy (SERS), applied in situ.

The obtained values were compared with those of bulk silica. Moreover, results indicated that ion concentrations differ in pristine and hydrophobic nanopores compared with those functionalized with phenyl and methyl radicals. In the latter, an increase in anion concentration and a concurrent decrease in cation concentration were reported. Additionally, the pH within the nanopores was found to depend on the composition of the solution. In some cases, the pH inside the nanopores decreased by as much as 2.5 units compared to the bulk value.

These findings provide insight into ion–nanopore chemical interactions and enable precise and selective control of contaminants, with direct applications in water chemistry for membrane-based desalination processes, CO₂ storage, and catalysis in porous materials.

More information at: ACS Applied Materials and Interfaces

Ab initio structural solutions from nanocrystal powder diffraction using diffusion models

 

Over the past century, the development of materials science has increasingly relied on the precise determination of atomic arrangements—that is, the crystal structure and its properties. To this end, X-ray diffraction (XRD) is commonly applied, with the sine qua non being the availability of a single crystal or monocrystal. However, this is not always feasible, especially with atomic clusters of nanometric size (smaller than 1000 Å), known as the nanostructure problem. In such cases, powder X-ray diffraction (PXRD) patterns are degraded due to peak broadening, intensity loss, and Bragg peak overlap.

Researchers from the United States and Germany have proposed a procedure that uses a generative machine learning model* based on diffusion processes, trained on 45,229 known structures. The model, called PXRDnet, conditioned solely on the compound's chemical formula, can solve simulated nanocrystals up to 10 Å in 200 materials with various symmetries and complexities, including all seven crystal systems.

PXRDnet correctly identifies structural candidates in 4 out of 5 cases, with an average error of just 7% in the Rietveld refinement factor R. Moreover, it is capable of resolving structures from noisy experimentally obtained diffraction patterns.

The authors argue that this data-driven, theoretically bootstrapped approach opens new avenues for determining previously unsolved nanomaterial structures. However, the model has limitations: it requires prior knowledge of the chemical formula and is restricted to structures with fewer than 20 atoms per unit cell.

*The term “generative” refers to a class of statistical models as opposed to discriminative models. Generative models can generate new data instances, while discriminative models distinguish between different types of data instances.

The work was published by Nature Materials

Synthesis of 2-Dimensional Metals via van der Waals (vdW) Compression

Since the discovery of graphene in 2004, two-dimensional (2D) materials have attracted considerable attention from the scientific community. To date, a wide variety of 2D materials are known, such as MXenes and transition metal dichalcogenides, as well as monolayers composed of a single type of atom from elements such as carbon (C), silicon (Si), germanium (Ge), and phosphorus (P). Most of these materials grow in three dimensions, forming structures stabilized by van der Waals (vdW) forces, which makes it relatively easy to exfoliate atomically thin layers.

However, this is not the case for metals, which grow three-dimensionally through strong chemical bonding. Until recently, it was believed that obtaining an atomically thin metal layer was practically impossible, as such structures would also be thermodynamically unstable.

Recently, a group of researchers in China succeeded in producing two-dimensional metals with thicknesses on the order of angstroms using a technique known as van der Waals compression. To carry out this process, they first grew a monolayer of molybdenum disulfide (MoS₂) on a sapphire substrate. This bilayer serves as a base or bottom anvil. A small amount of metal was then placed on the MoS₂ monolayer and heated until it formed a molten droplet. A second MoS₂/sapphire layer was placed on top, with the MoS₂ in direct contact with the molten metal. A pressure of 200 MPa was applied and maintained until both anvils returned to room temperature. The 2D metal was then obtained via a cleaving process that separated the MoS₂/2D-metal/MoS₂ sandwich from the sapphire substrates.

Using this simple and effective technique, two-dimensional metals have been synthesized from bismuth (Bi), tin (Sn), lead (Pb), indium (In), and gallium (Ga). Transport properties measured via Raman spectroscopy on 2D bismuth revealed enhanced electrical conductivity, improved field-effect performance, and increased conductivity due to a nonlinear Hall effect.

This paves the way to a new line of research focused on exploring metals, alloys, and non-layered materials at the 2D scale, along with the investigation of their properties and potential implementation in various technological devices.

For further information go to: NATURE