Molecular Sustainable Solutions, a spin-off from the Universitat Jaume I of Castelló (UJI), secures €186,000 investment from BeAble Capital, a leading Science Equity fund specializing in disruptive scientific technologies. The disinfection and sterilization methods developed by Molecular Sustainable Solutions —more powerful and sustainable than current ones— are capable of tackling particularly resistant and dangerous microorganisms, such as the fungus Candida auris, popularly known as “the killer fungus.”

With this investment, Molecular Sustainable Solutions will be able to accelerate the maturation of its technology and move towards rapid market entry, strengthening its position as a benchmark in innovative solutions for public health and sustainability. The company, based at Espaitec, the UJI Science and Technology Park, thus becomes the first spin-off from the public university in Castelló to receive funding from a venture capital firm.

Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic compounds introduced in food due to cooking methods such as smoking, grilling, and frying. Recently, researchers from Seoul National University of Science and Technology have leveraged a new method called QuEChERS-GC-MS to extract and detect PAHs in common food items, finding the highest levels in soybean oil, followed by duck meat and canola oil.

A zigzag stitch enables fabric to stretch until the thread is straight. University of Tartu researchers report in Advanced Materials that thread packing can encode fabric stretchability, leading the way to tailoring wearables at industrial scale.

In the Universe, thermonuclear fusion is a common reaction: it is the source of energy for stars. On Earth producing energy using this process is difficult due to problems with controlling the plasma emitting significant amounts of energy. Of critical importance here is the knowledge of the current state of the plasma and the power released in nuclear reactions. In the ITER reactor this knowledge will be gathered by a sophisticated neutron flux diagnostic system.

Inspired by molecular motors in biological systems, researchers at Doshisha University develop the world’s first symmetric ratchet motor in which a perfectly circular disk spins in one direction when placed on vibrating particles. While conventional rachets rely on asymmetry, this motor emerges from spontaneous symmetry breaking. This discovery highlights a new principle in physics of extracting order from noise, setting the stage for innovative energy-harvesting devices that work on ambient vibrations.

Optical synapses have an ability to perceive and remember visual information, making them expected to provide more intelligent and efficient visual solutions for humans. As a new type of artificial visual sensory devices, photoelectric memristors can fully simulate synaptic performance and have great prospects in the development of biological vision. However, due to the urgent problems of nonlinear conductance and high-energy consumption, its further application in high-precision control scenarios and integration is hindered. In this work, we report an optoelectronic memristor with a structure of TiN/CeO₂/ZnO/ITO/Mica, which can achieve minimal energy consumption (187 pJ) at a single pulse (0.5 V, 5 ms). Under the stimulation of continuous pulses, linearity can be achieved up to 99.6%. In addition, the device has a variety of synaptic functions under the combined action of photoelectric, which can be used for advanced vision. By utilizing its typical long-term memory characteristics, we achieved image recognition and long-term memory in a 3 × 3 synaptic array and further achieved female facial feature extraction behavior with an activation rate of over 92%. Moreover, we also use the linear response characteristic of the device to design and implement the night meeting behavior of autonomous vehicles based on the hardware platform. This work highlights the potential of photoelectric memristors for advancing neuromorphic vision systems, offering a new direction for bionic eyes and visual automation technology.