Articles in 2024

Rui Li, Gabriel della Maggiora and co-authors present a deep learning approach for attenuating diffraction and optical imperfections in light microscopy images. By incorporating the underlying physics of light propagation in microscopy into the loss function and designing a conditional diffusion model, they obtained improved performance compared to the state-of-the-art.

Zhen Tian, Hongzhuan Xuan, and colleagues show an optical fiber sensor for measuring concentration changes of protein kinase B, also known as AKT, extracted from human Lovo cells. Their biosensor allows studying anti-cancer mechanisms in the human body.

Vapour trails (contrails) from aircraft make a substantial contribution to aviation’s climate impact. Here we execute a per-flight contrail avoidance feasibility test through altitude adjustments based on contrail formation predictions. The avoidance regime resulted in a 64% reduction in satellite-visible contrails at a 2% increase in fuel burn per adjusted flight.

Yandao Huang and colleagues introduce a non-contact system that integrates fiber optic sensors with AI to achieve accurate, medical-grade ballistocardiography signal detection. This system allows for continuous nocturnal blood pressure monitoring, aiding in early screening and managing hypertension and other cardiovascular diseases.

When mapping brain activity with optogenetic techniques, patterned illumination is critical for targeted stimulation. Here, implantable silicon neural probes forming a single steerable beam are developed and in vivo demonstrations reported the device’s potential for deep brain optogenetic stimulation

Maximilian Gießler and colleagues present a framework for detecting and distinguishing near-falls related to trips and slips using a wearable sensor. Their system accounts for individual gait characteristics, thereby minimising false detection.

Wenhai Chu and co-authors discuss continuous and discontinuous approaches for atmospheric water harvesting. They identify the steps for expanding the operability range and efficiency of the existing techniques and propose mass transfer mechanics using sorbent materials.

Accurate and fast prediction of dynamical systems such as rocket combustion instabilities, is critical to the safety of aerospace missions. Michael Qian Vergnolle and colleagues report a bio-inspired deep learning model called TimeWaves which accurately and efficiently predicts long-term pressure oscillations of a liquid propellant rocket combustion instability.

Ellie Fini and co-authors investigate innovative and often overlooked methods for managing sewage sludge. Their work emphasizes how these alternative approaches can effectively reduce environmental hazards, such as heavy metal contamination and carbon emissions, while also fostering the development of value-added products.

Kenji Shimazoe and co-authors present an indirect fine-pitch X-ray photon-counting detector by combining silicon photomultiplier arrays and fast scintillation crystals. The detector is capable of detecting the photons and differentiating them by the energy level.

Kenji Kakiage and colleagues report an ultra-lightweight Li-S pouch cell with a gravimetric energy density of 761 Wh/kg. They use sulfurized polyacrylonitrile as a cathode active material, combining ten technologies for rechargeable batteries.

Meitham Amereh and colleagues report a hybrid discrete-continuum model to predict the cancerous growth, invasion, and treatment response of glioblastoma tumours. Their in-silico model uses metabolic data from a biomimetic two-dimensional in-vitro cancer model to predict three-dimensional behaviour of in-vitro human glioblastoma.

Zhe Meng and co-authors demonstrate the feasibility of synergetic pyrolysis of lithium-ion battery cathode materials with PET plastic for recovering Li and transition metals. They demonstrate a high recovery ratio and energy efficiency.

Jonathan Tran and colleagues use aerodynamics-guided machine learning for the shape optimization of electric cars. Their approach saves computational time for high complexity engineering tasks, e.g., computational fluid dynamics-based design optimization.

Operational data of lithium-ion batteries from battery electric vehicles can be logged and used to model lithium-ion battery aging, i.e., the state of health. Here, we discuss future State of Health definitions, the use of data from battery production beyond production, the logging & aggregation of operational data and challenges of the State of Health in automotive applications. Our suggestions could improve data transfer efficiency and data storage costs.

It is not currently possible for an infrared camera to see through a hot window. Now Ciril Samuel Prasad and colleagues report a metasurface-coated window which suppresses thermal emission towards an IR camera while being sufficiently transparent for thermal imaging.

Rolf Behling and colleagues propose a new X-ray source concept to improve the resolution of X-ray computed tomography and non-destructive testing and the efficacy of radiation cancer therapy by replacing the rotary anode with a fast stream of microparticles in the electron beam.

Dr Piet Claus and colleagues report a method to extract tissue samples from a human-sized pig heart used for studying discrete arrhythmogenic sites. They determine locations for marking and sectioning by using a 3D printed model that is derived from MRI images, allowing them to correlate structural imaging with prior information obtained in vivo.

Manuylovich and colleagues propose the use of stochastic resonances in neural networks as dynamic nonlinear nodes. They demonstrate the possibility of reducing the number of neurons for a given prediction accuracy and observe that the performance of such neural networks can be more robust against the impact of noise in the training data compared to the conventional networks.