With the rise of the Internet of Things and Industry 4.0, piezoelectrics, or materials that generate an electric charge when a strain is applied to them, are becoming extremely useful as compact and energy-efficient force sensors. Accordingly, piezotronics has emerged as a new technological frontier with applications in structural health monitoring in civil engineering and human-machine interface devices.

Piezotronic force sensors are typically governed by either a strain-induced “Schottky barrier height (SBH) modulation” or by a “piezo-gating effect” that redistributes the charge carriers in an induced piezoelectric field. However, while SBH-based devices have been well-explored, piezo-gating-based devices remain relatively less understood. This has limited the fabrication of piezo-gated transistors, the basic building block of all electronics. Additionally, the piezo-gating effect is often confused with the “piezoresistive effect” a co-existing phenomenon with a similar response. To harness the full potential of the piezo-gating impact, we, therefore, need to understand it better.

In a new study published in Nano Energy, researchers from National Cheng Kung University (NCKU), Taiwan now report, for the first time, a “dual-mode” piezo-gated thin-film transistor (PGTFT) along with an analytical model explaining its working mechanism. The PGTFT exhibits an unprecedented operation between two modes, namely depletion and accumulation, and a record gauge factor (ratio of relative change in current to mechanical strain) of 2780, indicating its extreme sensitivity.

“PGTFTs relying solely on the piezo-gating effect are essential for developing advanced piezotronic devices. But, most PGTFTs reported so far show indistinct piezo-gating effect through SBH modulation induced by piezoelectric fields, and can detect only one-dimensional strain,” says Prof. Chuan-Pu Liu, the corresponding author of the study.

In their work, the researchers used zinc oxide (ZnO) to fabricate the thin-film transistors owing to the versatile piezoelectric and semiconductor properties of ZnO. The charge carrier concentrations in the ZnO thin films were varied in a controlled manner by changing the gas used during their preparation. The thin films were then fully characterized and used to prepare two distinct PGTFT configurations.

The team tested the current-voltage characteristics of the PGTFTs by subjecting them to strain and analyzed the results both analytically and using numerical simulations. Additionally, they explored the effect of changing carrier concentrations on the operation modes of the PGTFTs to gauge the influence of the piezo-gating effect.

The team found that increased strains reduced the current in the top PGTFT electrode but increased it in the bottom electrode. This happened due to the electrons moving from the top to the bottom in response to the force, creating a depletion at the top and an accumulation of electrons at the bottom. This, in turn, affected the output current and revealed the co-existence of the piezo-gating effect and piezoresistive effect, with the piezo-gating effect being dominant.

Additionally, the team showed, experimentally and analytically, that the gauge factor is highly sensitive to the carrier concentration, showing a 44% enhancement in their design.

“Our proposed analytical model explains the workings of the PGTFT perfectly, showing agreement with experiment as well as simulations. These findings will pave the way for the development and application of multi-dimension strain-sensing PGTFTs,” says Prof. Liu. This could lead to novel human-machine interfaces that are compact, cost-effective, and less power-hungry.

If science and nature were to have a baby, it would surely be the zeolite. This special rock, with its porous structure that traps water inside, also traps atoms and molecules that can cause chemical reactions. That’s why zeolites are important as catalysts, or substances that speed up chemical reactions without harming themselves. Zeolites work their magic in the drug and energy industries and a slew of others. Petrochemicals break large hydrocarbon molecules into gasoline and further into all kinds of petroleum byproducts. Applications like fluid catalytic cracking and hydrocracking rely heavily on zeolites. 

So important is the use of zeolites that decades ago scientists began making them (synthetic ones) in the lab with the total number of crystal structures exceeding 250.  

Now, an undisputed bedrock in the global zeolite research community, Jeffrey Rimer, Abraham E. Dukler Professor of chemical and biomolecular engineering at the University of Houston, has published a review summarizing methods over the past decade that have been used to prepare state-of-the-art zeolites with nano-sized dimensions and hierarchical structures.  

The findings emphasize that smaller is better and structure is critical. 

“These features are critical to their performance in a wide range of industrial applications. Notably, the small pores of zeolites impose diffusion limitations for processes involving catalysis or separations where small molecules must access pores without obstruction from the accumulation of residual materials like coke, which is a carbonaceous deposit that blocks pores,” reports Rimer. “This calls for new methods to prepare zeolites with smaller sizes and higher surface area, which is a challenging task because few zeolites can be prepared with sizes less than 100 nanometers.”  

The review article summarizes advanced methods to accomplish this goal, including work from Rimer’s own group on finned zeolites, which he invented. Zeolites with fins are an entirely new class of porous catalysts using unique nano-sized features to speed up the chemistry by allowing molecules to skip the hurdles that limit the reaction. 

Rimer also examines how the emergence of data analytics and machine learning are aiding zeolite design and provides future perspectives in this growing area of research. That helps make up the “new methods” that Rimer suggests as imperative, resulting in major advantages of infusing computational and big data analyses to transition zeolite synthesis away from trial-and-error methodologies. 

Besides, speeding up the process of crystallizing zeolites, and speeding up the reactions of the zeolites themselves, will result in many socioeconomic advantages, according to Rimer. 

“Improved zeolite design includes the development of improved catalysts for energy applications (including advancements in alternative energy), new technologies for regulating emissions that impact the environment, and separations to improve industrial processes with impact on petroleum refining, production of chemicals, and water purification,” he said. 

An evocative new image captured by the Gemini North telescope in Hawai‘i reveals a pair of interacting spiral galaxies — NGC 4568 and NGC 4567 — as they begin to clash and merge. These galaxies are entangled by their mutual gravitational field and will eventually combine to form a single elliptical galaxy in around 500 million years. Also visible in the image are the glowing remains of a supernova that was detected in 2020. 

Gemini North, one of the twin telescopes of the International Gemini Observatory, operated by NSF’s NOIRLab, has observed the initial stages of a cosmic collision approximately 60 million light-years away in the direction of the constellation Virgo. The two stately spiral galaxies, NGC 4568 (bottom) and NGC 4567 (top) are poised to undergo one of the most spectacular events in the Universe, a galactic merger. At present, the centers of these galaxies are still 20,000 light-years apart (about the distance from Earth to the center of the Milky Way) and each galaxy still retains its original, pinwheel shape. Those placid conditions, however, will change.

As NGC 4568 and NGC 4567 draw together and coalesce, their dueling gravitational forces will trigger bursts of intense star formation and wildly distort their once-majestic structures. Over millions of years, the galaxies will repeatedly swing past each other in ever-tightening loops, drawing out long streamers of stars and gas until their structures are so thoroughly mixed that a single, essentially spherical, galaxy emerges from the chaos. By that point, much of the gas and dust (the fuel for star formation) in this system will have been used up or blown away.

This merger is also a preview of what will happen when the Milky Way and its closest large galactic neighbor the Andromeda Galaxy collide in about 5 billion years. 

A bright region in the center of one of NGC 4568’s sweeping spiral arms is the fading afterglow of a supernova — known as SN 2020fqv — that was detected in 2020. The new Gemini image was produced from data taken in 2020. 

By combining decades of observations and supercomputer modeling, astronomers now have compelling evidence that merging spiral galaxies like these go on to become elliptical galaxies. Likely, NGC 4568 and NGC 4567 will eventually resemble their more-mature neighbor Messier 89, an elliptical galaxy that also resides in the Virgo Cluster. With its dearth of star-forming gas, Messier 89 now exhibits minimal star formation and is made up primarily of older, low-mass stars and ancient globular clusters.

Advanced technology on the Gemini North telescope, including the Gemini Multi-Object Spectrograph North (GMOS-N) and the dry air above the summit of Maunakea, allowed astronomers to capture this spectacular image. 

The image was obtained by NOIRLab’s Communication, Education & Engagement team, as part of the NOIRLab Legacy Imaging Program.

Sequence modeling algorithms could eventually lead to new ways to fight diseases caused by genetic mutations

Newly developed artificial intelligence (AI) programs accurately predicted the role of DNA’s regulatory elements and three-dimensional (3D) structure based solely on its raw sequence, according to two recent studies. These tools could eventually shed new light on how genetic mutations lead to disease and could lead to a new understanding of how genetic sequence influences the spatial organization and function of chromosomal DNA in the nucleus, said study author Jian Zhou, Ph.D., Assistant Professor in the Lyda Hill Department of Bioinformatics at UTSW.

“Taken together, these two programs provide a more complete picture of how changes in DNA sequence, even in noncoding regions, can have dramatic effects on its spatial organization and function,” said Dr. Zhou, a member of the Harold C. Simmons Comprehensive Cancer Center, a Lupe Murchison Foundation Scholar in Medical Research, and a Cancer Prevention and Research Institute of Texas (CPRIT) Scholar.

Only about 1% of human DNA encodes instructions for making proteins. Research in recent decades has shown that much of the remaining noncoding genetic material holds regulatory elements – such as promoters, enhancers, silencers, and insulators – that control how the coding DNA is expressed. How sequence controls the functions of most of these regulatory elements is not well understood, Dr. Zhou explained.

To better understand these regulatory components, he and colleagues at Princeton University and the Flatiron Institute developed a deep learning model they named Sei, which accurately sorts these snippets of noncoding DNA into 40 “sequence classes” or jobs – for example, as an enhancer for stem cell or brain cell gene activity. These 40 sequence classes, developed using nearly 22,000 data sets from previous studies studying genome regulation, cover more than 97% of the human genome. Moreover, Sei can score any sequence by its predicted activity in each of the 40 sequence classes and predict how mutations impact such activities.

By applying Sei to human genetics data, the researchers were able to characterize the regulatory architecture of 47 traits and diseases recorded in the UK Biobank database and explain how mutations in regulatory elements cause specific pathologies. Such capabilities can help gain a more systematic understanding of how genomic sequence changes are linked to diseases and other traits. The findings were published this month.

In May, Dr. Zhou reported the development of a different tool, called Orca, which predicts the 3D architecture of DNA in chromosomes based on its sequence. Using existing data sets of DNA sequences and structural data derived from previous studies that revealed the molecule’s folds, twists, and turns, Dr. Zhou trained the model to make connections and evaluated the model’s ability to predict structure at various length scales. 

The findings showed that Orca predicted DNA structures both small and large based on their sequences with high accuracy, including for sequences carrying mutations associated with various health conditions including a form of leukemia and limb malformations. Orca also enabled the researchers to generate new hypotheses about how DNA sequence controls its local and large-scale 3D structure.

Dr. Zhou said that he and his colleagues plan to use Sei and Orca, which are both publicly available on web servers and as open-source code, to further explore the role of genetic mutations in causing the molecular and physical manifestations of diseases – research that could eventually lead to new ways to treat these conditions.