Lifeboat Foundation

(Nanowerk News) Advanced technologies enable the controlled release of medicine to specific cells in the body. Scientists argue these same technologies must be applied to agriculture if growers are to meet increasing global food demands.

In a new Nature Nanotechnology journal review paper (“Towards realizing nano-enabled precision delivery in plants”), scientists from UC Riverside and Carnegie Mellon University highlight some of the best-known strategies for improving agriculture with nanotechnology.

Chemists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory, Stony Brook University (SBU), and their collaborators have uncovered new details of the reversible assembly and disassembly of a platinum catalyst. The new understanding may offer clues to the catalyst’s stability and recyclability.

The work, described in a paper published in the journal Nanoscale (“Unravelling the origin of reaction-driven aggregation and fragmentation of atomically dispersed Pt catalyst on ceria support”), reveals how single platinum atoms on a cerium oxide support aggregate under reaction conditions to form active catalytic nanoparticles — and then, surprisingly, fragment once the reaction is stopped.

Fragmentation may sound shattering, but the scientists say it could be a plus.

A collaborative study by researchers at Lancaster and Radboud universities has pioneered a method to generate and control spin waves at the nanoscale, offering a new, energy-efficient approach to quantum computing.

Researchers at Lancaster University and Radboud University Nijmegen have successfully produced propagating spin waves on the nanoscale, unveiling a new method to modulate and amplify these waves.

Their discovery, published in Nature, could pave the way for the development of dissipation-free quantum information technologies. As the spin waves do not involve electric currents these chips will be free from associated losses of energy.

An Israeli startup has developed a way to make lead acid batteries last four times longer, disrupting a multi-billion-dollar industry and potentially making them the rechargeable – and recyclable – energy storage method of choice around the world.

Lead acid is the second most common battery technology worldwide and the power cells are currently used as the starter batteries in cars, trucks and motorcycles.

The batteries have a positive plate made of lead dioxide on one end, and a spongy lead negative plate on the other end, with sulfuric acid flowing between them both to conduct the electricity.

Nanoscale materials offer remarkable chemical and physical properties that transform theoretical applications, like single-molecule sensing and minimally invasive photothermal therapy, into practical realities.

The unparalleled features of nanoparticles make them promising for various research and industrial uses. However, effectively using these materials is challenging due to the absence of a rapid and consistent method to transfer a uniform monolayer of nanoparticles, a crucial step in device manufacturing.

One potential solution to this challenge lies in electrostatic assembly processes, where oppositely charged nanoparticles adhere to a surface, forming a monolayer that repels other similarly charged particles from attaching further. While effective, this process is often slow. Nature provides an innovative model to address this limitation through underwater adhesion strategies, which have evolved to circumvent similar problems.

Conductive aerogels have gained significant research interests due to their ultralight characteristics, adjustable mechanical properties, and outstanding electrical performance^1,2,3,4,5,6. These attributes make them desirable for a range of applications, spanning from pressure sensors^7,8,9,10 to electromagnetic interference shielding^11,12,13, thermal insulation^14,15,16, and wearable heaters^17,18,19. Conventional methods for the fabrication of conductive aerogels involve the preparation of aqueous mixtures of various building blocks, followed by a freeze-drying process^20,21,22,23. Key building blocks include conductive nanomaterials like carbon nanotubes, graphene, Ti₃C₂T_x MXene nanosheets^{24,25,26,27,28,29,30}, functional fillers like cellulose nanofibers (CNFs), silk nanofibrils, and chitosan^{29,31,32,33,34}, polymeric binders like gelatin^25,26, and crosslinking agents that include glutaraldehyde (GA) and metal ions^30,35,36,37. By adjusting the proportions of these building blocks, one can fine-tune the end properties of the conductive aerogels, such as electrical conductivities and compression resilience^38,39,40,41. However, the correlations between compositions, structures, and properties within conductive aerogels are complex and remain largely unexplored^{42,43,44,45,46,47}. Therefore, to produce a conductive aerogel with user-designated mechanical and electrical properties, labor-intensive and iterative optimization experiments are often required to identify the optimal set of fabrication parameters. Creating a predictive model that can automatically recommend the ideal parameter set for a conductive aerogel with programmable properties would greatly expedite the development process⁴⁸.

Machine learning (ML) is a subset of artificial intelligence (AI) that builds models for predictions or recommendations^49,50,51. AI/ML methodologies serve as an effective toolbox to unravel intricate correlations within the parameter space with multiple degrees of freedom (DOFs)^50,52,53. The AI/ML adoption in materials science research has surged, particularly in the fields with available simulation programs and high-throughput analytical tools that generate vast amounts of data in shared and open databases⁵⁴, including gene editing^55,56, battery electrolyte optimization^57,58, and catalyst discovery^59,60. However, building a prediction model for conductive aerogels encounters significant challenges, primarily due to the lack of high-quality data points. One major root cause is the lack of standardized fabrication protocols for conductive aerogels, and different research laboratories adopt various building blocks^35,40,46. Additionally, recent studies on conductive aerogels focus on optimizing a single property, such as electrical conductivity or compressive strength, and the complex correlations between these attributes are often neglected to understand^{37,42,61,62,63,64}. Moreover, as the fabrication of conductive aerogels is labor-intensive and time-consuming, the acquisition rate of training data points is highly limited, posing difficulties in constructing an accurate prediction model capable of predicting multiple characteristics.

Herein, we developed an integrated platform that combines the capabilities of collaborative robots with AI/ML predictions to accelerate the design of conductive aerogels with programmable mechanical and electrical properties (see Supplementary Fig. 1 for the robot–human teaming workflow). Based on specific property requirements, the robots/ML-integrated platform was able to automatically suggest a tailored parameter set for the fabrication of conductive aerogels, without the need for conducting iterative optimization experiments. To produce various conductive aerogels, four building blocks were selected, including MXene nanosheets, CNFs, gelatin, and GA crosslinker (see Supplementary Note 1 and Supplementary Fig. 2 for the selection rationale and model expansion strategy). Initially, an automated pipetting robot (i.e., OT-2 robot) was operated to prepare 264 mixtures with varying MXene/CNF/gelatin ratios and mixture loadings (i.e.

Researchers based at the Dept of Biology and School of Physics, Engineering and Technology have developed a remarkable new technology which is able to study single biological molecules using intrinsic twist properties to bring about essential functions in cells.

“Nano twists” that drive life

There are myriad so-called “chiral” molecules in biology, which have a fascinating property of not appearing to have the same structure were you to look at their image in a mirror — one of the best known examples being DNA, the “molecule of life”, whose chirality comes from its amazing double helix structure. This chirality, which looks in the case of extended DNA molecules like “nano twists”, results in a property which physicists describe as “symmetry breaking” which in turn can drive molecules into a range of different states. With input from sources of energy, these molecules can then jump between different states as part of their normal function, and it is this state jumping which essentially drives all processes in living cells — so chirality is an enormously fundamental feature which in effect effect steers key cellular processes.

Prof. Sergey Prosandeev and Prof. Bellaiche (who proposed with other co-workers the polar vortex ordering theoretically 20 years ago), joined this collaboration and further proved that the vortex distribution results obtained from experiments are consistent with theoretical calculations.

By controlling the number and orientation of these polarization distributions, it is expected that this can be utilized in a next-generation high-density memory device that can store more than 10,000 times the amount of information in the same-sized device compared to existing ones.

Dr. Yang, who led the research, explained the significance of the results, “This result suggests that controlling the size and shape of ferroelectrics alone, without needing to tune the substrate or surrounding environmental effects such as epitaxial strain, can manipulate ferroelectric vortices or other topological orderings at the nano-scale. Further research could then be applied to the development of next-generation ultra-high-density memory.”

Imaging the hot turbulence of aircraft propulsion systems may now be possible with sturdy sheets of composite materials that twist light beams, according to research led by the University of Michigan and Air Force Research Laboratory.