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Category: chemistry – Page 65

After its “birth” in the Big Bang, the universe consisted mainly of hydrogen and a few helium atoms. These are the lightest elements in the periodic table. More-or-less all elements heavier than helium were produced in the 13.8 billion years between the Big Bang and the present day.

Stars have produced many of these heavier elements through the process of nuclear fusion. However, this only makes elements as heavy as iron. The creation of any heavier elements would consume energy instead of releasing it.

In order to explain the presence of these heavier elements today, it’s necessary to find phenomena that can produce them. One type of event that fits the bill is a gamma-ray burst (GRB)—the most powerful class of explosion in the universe. These can erupt with a quintillion (10 followed by 18 zeros) times the luminosity of our sun, and are thought to be caused by several types of event.

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Organic electrochemical artificial neurons (OANs) are the latest entry of building blocks, with a few different approaches for circuit realization. OANs possess the remarkable capability to realistically mimic biological phenomena by responding to key biological information carriers, including alkaline ions, noise in the electrolyte, and biological conditions. An organic artificial neuron with a cascade-like topology made of OECT inverters has shown basic (regular) firing behavior and firing frequency that is responsive to the concentration of ionic species (Na+, K+) of the host liquid electrolyte33. An organic artificial neuron consisting of a non-linear building block that displays S-shape negative differential resistance (S-NDR) has also been recently demonstrated34. Due to the realization of the non-linear circuit theory with OECTs and the sharp threshold for oscillations, this artificial neuron displays biorealistic firing properties and neuronal excitability that can be found in the biological domain such as input voltage-induced regular and irregular firing, ion and neurotransmitter-induced excitability and ion-specific oscillations. Biohybrid devices comprising artificial neurons and biological membranes have also shown to operate synergistically, with membrane impedance state modulating the firing properties of the biohybrid in situ. More recently, a circuit leveraging the non-linear properties of antiambipolar OMIECs, which exhibit negative differential transconductance, has been realized35. These neurons show biorealistic properties such as various firing modes and responsivity to biologically relevant ions and neurotransmitters. With this neuron, ex-situ electrical stimulation has been shown in a living biological model. Therefore, the class of OANs perfectly complements the broad range of features already demonstrated by solid-state spiking circuits (Supplementary Table 1), offering opportunities for both hybrid interfacing between these technologies and new developments in neuromorphic bioelectronics.

Despite the promising recent realizations of organic artificial neurons, all approaches still remain in the qualitative demonstration domain and a rigorous investigation of circuit operation is still missing. Indeed, quantitative models exist only for inorganic, solid-state artificial neurons without the inclusion of physical soft-matter parameters and the biological wetware (i.e., aqueous electrolytes, alkaline ions, biomembranes)36,37. This gap in knowledge significantly impedes the simulation of larger-scale functional circuits, and therefore the design and development of integrated organic neuromorphic electronics, biohybrids, OAN-based neural networks, and intelligent bioelectronics.

In this work, we unravel the operation of organic artificial neurons that display non-linear phenomena such as S-shape negative differential resistance (S-NDR). By combining experiments, numerical simulations of non-linear iontronic circuits, and newly developed analytical expressions, we investigate, reproduce, rationalize, and design the wide biorealistic repertoire of organic electrochemical artificial neurons including their firing properties, neuronal excitability, wetware operation, and biohybrid formation. The OAN operation is efficiently rationalized to include how neuronal dynamics are probed by biochemical stimuli in the electrolyte medium. The OAN behavior is also extended on the biohybrid formation, with a solid rationale of the in situ interaction of OANs with biomembranes. Non-linear simulations of OANs are rooted in a physics-based framework, considering ion type, ion concentration, organic mixed ionic–electronic parameters, and biomembrane properties. The derived analytical expressions establish a direct link between OAN spiking features and its physical parameters and therefore provide a mapping between neuronal behavior and materials/device parameters. The proposed approach open opportunities for the design and engineering of advanced biorealistic OAN systems, establishing essential knowledge and tools for the development of neuromorphic bioelectronics, in-liquid neural networks, biohybrids, and biorobotics.

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Memristive and nanoionic devices have recently emerged as leading candidates for neuromorphic computing architectures. While top-down fabrication based on conventional bulk materials has enabled many early neuromorphic devices and circuits, bottom-up approaches based on low-dimensional nanomaterials have shown novel device functionality that often better mimics a biological neuron. In addition, the chemical, structural and compositional tunability of low-dimensional nanomaterials coupled with the permutational flexibility enabled by van der Waals heterostructures offers significant opportunities for artificial neural networks. In this Review, we present a critical survey of emerging neuromorphic devices and architectures enabled by quantum dots, metal nanoparticles, polymers, nanotubes, nanowires, two-dimensional layered materials and van der Waals heterojunctions with a particular emphasis on bio-inspired device responses that are uniquely enabled by low-dimensional topology, quantum confinement and interfaces. We also provide a forward-looking perspective on the opportunities and challenges of neuromorphic nanoelectronic materials in comparison with more mature technologies based on traditional bulk electronic materials.

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Hydrogen offers significant potential as both a chemical and energy carrier for decarbonizing society. Unlike traditional fuels, using hydrogen does not produce carbon dioxide. However, most hydrogen currently produced derives from methane, a fossil fuel, through a process called methane reforming, which unfortunately emits a considerable amount of carbon dioxide. Consequently, developing scalable alternatives for producing green hydrogen is essential.

Water electrolysis offers a path to generate green hydrogen which can be powered by renewables and clean electricity. This process needs cathode and anode catalysts to accelerate the otherwise inefficient reactions of water splitting and recombination into hydrogen and oxygen, respectively. From its early discovery in the late 18th century, the water electrolysis has matured into different technologies. One of the most promising implementations of water electrolysis is the proton-exchange-membrane (PEM), which can produce green hydrogen by combining high rates and high energy efficiency.

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A novel technique with potential applications for fields such as droplet chemistry and photochemistry has been demonstrated by an Osaka Metropolitan University-led research group.

The findings were published in Advanced Optical Materials (“Förster Resonance Energy Transfer Control by Means of an Optical Force”).

Professor Yasuyuki Tsuboi of the Graduate School of Science and the team investigated Förster resonance energy transfer (FRET), a phenomenon seen in photosynthesis and other natural processes where a donor molecule in an excited state transfers energy to an acceptor molecule.

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Menthol detection predates the sensation of cold, indicating separate activation mechanisms that can be distinguished. This differentiation opens possibilities for novel pain treatments that avoid unwanted thermal side effects.

Millions of people around the globe suffer from chronic pain, and many existing treatments depend on opioids, which have significant addiction and overdose risks. Developing non-addictive pain relief options could transform how pain is managed. Recent research focusing on a human protein that controls cold sensations are paving the way for new pain medications. These innovative drugs aim to manage pain without altering body temperature or posing addiction risks.

A new study published in Science Advances on June 21, led by Wade Van Horn, professor in Arizona State University’s School of Molecular Sciences and Biodesign Center for Personalized Diagnostics, has uncovered new insights into the main human cold and menthol sensor TRPM8 (transient receptor potential melastatin 8). Using techniques from many fields like biochemistry and biophysics, their study revealed that it was a chemical sensor before it became a cold temperature sensor.

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Scientists in Japan say they have reversed the signs of Alzheimer’s disease in lab mice by restoring the healthy function of synapses, critical parts of neurons that shoot chemical messages to other neurons.

The secret was developing a synthetic peptide, a small package of amino acids — a mini-protein, if you will — and injecting it up the nostrils of the mice, in an experiment they detailed in a study published in the journal Brain Research.

Needless to say, mice are very different from humans. But if the treatment successfully survives the gauntlet of clinical studies with human participants, it could potentially lead to a new treatment for Alzheimer’s disease, a tragic degenerative condition that burdens tens of millions of people around the world.

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A series of advances in materials and design have enabled manufacturers to work at scales smaller than a billionth of a size to create devices and objects of nanoscopic dimensions. This is nanotechnology, which, although relatively new, produces materials and technologies already used in mass production.

The European Commission defines nano as any material that is at least 50% composed of particles between one and one hundred nanometers in size (i.e. one billionth of a meter, or one-millionth of a millimeter). Nanomaterials differ from conventional materials because of their unique properties such as higher electrical conductivity and mechanical strength, sensor technologies, and biomedical applications, and because they can create coatings that make surfaces more hydrophobic or self-cleaning.

The widespread use of nanotechnology is relatively new. Since 2000, nanomaterials have been used industrially as new research and experimental designs have made their effectiveness in different sectors clear. For example, in the health field, nanotechnology helps to reduce diagnostic errors and to develop nanobots (microscale robots) to repair and replace intercellular structures, or repair DNA molecules; in the chemical sector, it facilitates coating devices with nanoparticles to improve their smoothness and heat resistance; in manufacturing, materials developed with nanotechnology enhance the performance of the final product by improving heat resistance, strength, durability, and electrical conductivity.

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