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Producing photons one at a time on demand at room temperature is a key requirement for the rollout of a quantum internet—and the practical quantum computers that would undergird that network. The photons can be used as quantum bits (qubits), the quantum equivalent of classical computing’s 0s and 1s. Labs around the world have devised various ways to generate single photons, but they can involve complex engineering techniques such as doped carbon nanotubes or costly cryogenically-cooled conditions. On the other hand, less complicated techniques such as using traditional light sources do not provide the necessary level of control over single-photon emissions required for quantum networks and computers.

Now, researchers from Tokyo University of Science (TUS) and the Okinawa Institute of Science and Technology have collaborated to develop a prototype room temperature single-photon light source using standard materials and methods. The team described the fabrication of the prototype and its results in a recent issue of the journal Physical Review Applied.

“Our single-photon light source … increases the potential to create quantum networks—a quantum internet—that are cost-effective and accessible.” —Kaoru Sanaka, Tokyo University of Science.

Background: The Promise of Prime Editing

Prime editing is a promising technology for changing genomic deoxyribonucleic acid (DNA) that has the potential to be used to cure genetic diseases in individuals. Prime editors are proteins that can replace a specific deoxyribonucleic acid sequence with another. PE systems necessitate three distinct nucleic acid hybridizations and are not dependent on double-strand deoxyribonucleic acid breaks or donor deoxyribonucleic acid templates.

Researchers must devise efficient and safe techniques to deliver prime editors in tissues in the in vivo settings to fulfill PE’s objective. While viral delivery techniques such as adenoviruses and adeno-associated viruses (AAVs) can transport PE in vivo, non-viral delivery techniques like lipid nanoparticles can sidestep these concerns by packaging PEs as temporarily expressing messenger ribonucleic acids.

Before delving into the prospects of the Fifth Industrial Revolution, let’s reflect on the legacy of its predecessor. The Fourth Industrial Revolution, characterised by the fusion of digital, physical, and biological systems, has already transformed the way we live and work. It brought us AI, blockchain, the Internet of Things, and more. However, it also raised concerns about automation’s impact on employment and privacy, leaving us with a mixed legacy.

The promise of the Fifth Industrial Revolution.

The Fifth Industrial Revolution represents a quantum leap forward. At its core, it combines AI, advanced biotechnology, nanotechnology, and quantum computing to usher in a new era of possibilities. One of its most compelling promises is the extension of human life. With breakthroughs in genetic engineering, regenerative medicine, and AI-driven healthcare, we are inching closer to not just treating diseases but preventing them altogether. It’s a vision where aging is not an inevitability, but a challenge to overcome.

New Compounds for Organometallic Chemistry – Sandwich Complexes in the Form of Rings Are Kept Together by Their Own Energy.

Sandwich compounds are special chemical compounds used as basic building blocks in organometallic chemistry. So far, their structure has always been linear. Recently, researchers of Karlsruhe Institute of Technology (KIT) and the University of Marburg were the first to make stacked sandwich complexes form a nano-sized ring. Physical and other properties of these cyclocene structures will now be further investigated.

Evolution of Sandwich Complexes.

A study led by the University of Oxford has used the power of machine learning to overcome a key challenge affecting quantum devices. For the first time, the findings reveal a way to close the “reality gap”: the difference between predicted and observed behavior from quantum devices. The results have been published in Physical Review X.

Quantum computing could supercharge a wealth of applications, from climate modeling and financial forecasting to drug discovery and artificial intelligence. But this will require effective ways to scale and combine individual (also called qubits). A major barrier against this is inherent variability, where even apparently identical units exhibit different behaviors.

Functional variability is presumed to be caused by nanoscale imperfections in the materials from which quantum devices are made. Since there is no way to measure these directly, this internal disorder cannot be captured in simulations, leading to the gap in predicted and observed outcomes.

The integration of mechanical memory in the form of springs has for hundreds of years proven to be a key enabling technology for mechanical devices (such as clocks), achieving advanced functionality through complex autonomous movements. Currently, the integration of springs in silicon-based microtechnology has opened the world of planar mass-producible mechatronic devices from which we all benefit, via air-bag sensors for example.

For a of minimally and even non-invasive biomedical applications however, that can safely interact mechanically with cells must be achieved at much smaller scales (10 microns) and with much softer forces (pico Newton scale, i.e., lifting weights less than one millionth of a mg) and in customized three-dimensional shapes.

Researchers at the Chemnitz University of Technology, the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences and the Leibniz IFW Dresden, in a recent publication in Nature Nanotechnology, have demonstrated that controllable springs can be integrated at arbitrary chosen locations within soft three-dimensional structures using confocal photolithographic manufacturing (with nanoscale precision) of a novel magnetically active material in the form of a photoresist impregnated with customizable densities of magnetic nanoparticles.

The work demonstrates control over key properties leading to better performance.

MIT researchers and colleagues have demonstrated a way to precisely control the size, composition, and other properties of nanoparticles key to the reactions involved in a variety of clean energy and environmental technologies. They did so by leveraging ion irradiation, a technique in which beams of charged particles bombard a material.

They went on to show that nanoparticles created this way have superior performance over their conventionally made counterparts.

The technique of inhaling nanoparticle sensors followed by a urine test may offer the potential for faster and early detection of lung cancer.

Scientists from the Massachusetts Institute of Technology (MIT) have introduced this cutting-edge medical technology, presenting a simplified approach to diagnosing lung cancer.

Additionally, this innovation holds particular promise for low-and middle-income countries where the accessibility of computed tomography (CT) scanners is limited.

It is well-reported that solution-processed nanosheets tend to restack during deposition57. We determined the degree and nature of this restacking by measuring the nanosheet length and thickness in the ink (lNS, tNS) using AFM, as well as the aggregated nanosheet dimensions in the network (lNet, tNet) post-deposition. The restacked nanosheet length and thickness were measured from network cross-sections using the Ridge Detection plugin in FIJI50,58 (Fig. 2e, inset, and Supplementary Note 9). We define the aggregation factors in nanosheet length, χl, and thickness, χt, as \({\chi }_{{{{{\rm{l}}}}}}={l}_{{{{{\rm{Net}}}}}}/{l}_{{{{{\rm{NS}}}}}}\) and \({\chi }_{{{{{\rm{t}}}}}}={t}_{{{{{\rm{Net}}}}}}/{t}_{{{{{\rm{NS}}}}}}\) respectively. Values of χl ≈ 1.5 and χt ≈ 5.6 were found for the printed LPE graphene network in Fig. 2e. This is in agreement with a value of χt ≈ 5 reported for vacuum filtered WS2 networks59, and suggests that nanosheets primarily aggregate through vertical restacking with maximised basal plane overlap.

By isolating discrete nanoplatelets and noting their orientation (Fig. 2f, inset, and Supplementary Note 10)60, the distribution of angles, φ, between each nanoplatelet’s normal vector and the out-of-plane (y) direction was calculated. The data in Fig. 2f was fit with a Cauchy-Lorentz distribution centred on φC ≈ −0.6˚, which suggests the nanosheets are primarily aligned in the plane of the film. The full width at half maximum (FWHM) of the distribution provides an estimate of the degree of alignment about φc in the network61. The FWHM of (29 ± 1)˚ for the spray cast network in Fig. 2f is comparable to a value of 21˚ for an inkjet-printed graphene film measured using AFM. In addition, we measured the Hermans orientation factor62, \(S=\left(3\left\langle {\cos }^{2}\varphi \right\rangle-1\right)/2\), to be 0.61 ± 0.07 for the network, which is consistent with partial in-plane alignment. A value of S = 1 would imply the nanosheets are perfectly aligned in the plane of the film, while S = 0 for randomly oriented nanosheets. This is in broad agreement with a value of S = 0.79 for a vacuum filtered Ti3C2Tx nanosheet network measured using wide-angle X-ray scattering (WAXS)32.

The physical properties of 2D networks are known to scale with nanosheet size63,64. Here, we use FIB-SEM-NT to systematically study the morphology of printed LPE graphene networks for various nanosheet lengths, lNS. Size-selected inks were produced using liquid cascade centrifugation65, characterised by AFM (Fig. 3a) and spray-coated into networks. Reconstructed 3D volumes for networks of two different nanosheet sizes in Fig. 3b show noticeable changes in network morphology as lNS is decreased from 1,087 to 298 nm. Analysis reveals a clear decrease in network porosity from 51% to 39% with decreasing lNS (Fig. 3c), with a corresponding reduction in the characteristic pore size, ζ \(=\sqrt{A}\), in Fig. 3D. The pore circularity data similarly exhibits a dependence on lNS (Fig. 3e), where networks of smaller nanosheets have more circular and compact pore cross-sections. This implies that printed networks comprised of smaller nanosheets are more densely packed, which has been linked to improved charge transfer in graphene films66. Alternatively, networks of larger nanosheets are more open and porous, facilitating enhanced electrolyte infiltration and mass transport. Taken together, the data in Fig. 3c-e suggests that changing the nanosheet size offers a simple means to tailor the network porosity for a target application. FIB-SEM-NT can be used to inform this by measuring pore sizes that span from a few nanometres to microns.