The platform based on mixed-dimensional van der Waals heterostructures is promising for compact, energy-efficient analog and digital electronics on a single substrate. Hurdles include an incomplete understanding of charge behavior at atomically thin junctions, and technical difficulties in fabricating scalable, defect-free interfaces. This study overcomes those barriers via a two-step growth strategy and detailed transport measurements, revealing a nanometer-scale depletion region and gate-tunable diode characteristics. Individual Te and MoS${}_2$ regions can function as high-performance $p-$ and $n-$type FETs, respectively, enabling complete CMOS logic operations on the same chip.

The authors propose engineering non-Hermitian optical couplers so that external radiation enters the system through such a unidirectional coupler, but cannot escape. Unidirectionality is achieved by combining periodic modulation of the refraction index (the Hermitian part) with the gain or loss (non-Hermitian part) of the coupler. This results in an interesting physical effect, violating the usual action-reaction laws, and also leads to practical consequences, such as enhanced absorption of the trapped light. Enhanced absorption is demonstrated by measuring a greater temperature increase under unidirectional coupling, compared to a reference with symmetric coupling.

Physical learning machines promise to overcome the von Neumann bottleneck by implementing highly energy-efficient in-situ adaptation. This adaptation requires parameter updates that are local in space and time, while being robust to the inherent noise in physical substrates. This study embraces physical noise generated by stochastic magnetic tunnel junctions as a mechanism for learning via a combination with a recent local noise-based learning rule. The authors demonstrate that learning based on physical noise is a viable strategy, scalable to larger systems and a variety of physical substrates.

Soft ionic circuitry promises to create soft control systems and active materials that can sense, assess information, and respond to their environment. This complex behavior is enabled by charged polymers that act as ionic semiconductors, but their widespread use is inhibited by a lack of suitable design tools. The authors develop a lumped-element model that incorporates key effects and enables the design and analysis of large-scale ionic systems. Their tool illuminates the performance and limits of existing devices, and principles for designing a fully ionic soft-robot control system. This model will enable the field of ionics to move from building single devices to whole systems.

Linear inductors are integral components of superconducting circuits, but making them simultaneously compact, linear, and low-loss is challenging. The authors overcome this challenge using thin films of superconducting granular aluminum (grAl). By using an ex situ bandage technique, they integrate the grAl inductors with tantalum capacitor pads to make resonators with quality factors exceeding 3.5 million. These inductors are a valuable addition to the circuit QED toolkit and will find applications in circuits that are limited by the nonidealities of Josephson junction arrays or geometric inductances.

Josephson parametric amplifiers are essential components for quantum microwave measurements, but their high pump power requirement and unwanted pump leakage into the signal circuitry pose significant challenges for scalable implementation. This study presents a framework for integrating on-chip microwave filters with the amplifiers, improving power efficiency while suppressing pump leakage. The authors further investigate the amplifier’s robustness to thermal noise from the pump line. These results offer practical strategies for reducing the thermal load and component overhead in large-scale quantum processor readout systems.

Quantum annealing is a promising approach to solving a diversity of classical optimization problems across different fields, but real-world problems are often represented by densely connected graphs, which cannot be directly implemented in hardware in a scalable way. This work overcomes this limitation by presenting a very sparse architecture that results in effective dense connectivities. This result will have an impact on the engineering challenge of building large-scale quantum annealing devices that can solve practical optimization problems in several industry sectors, such as logistics, energy, or finance.

Physical reservoir computing holds promise for energy-efficient, real-time information processing, but its development is hindered by limited understanding of the nonlinear dynamics in physical substrates like magnons. The authors use time-resolved Brillouin light scattering microscopy to evaluate a magnon-scattering reservoir in a single magnetic vortex disk, and find that its ability to perform memory and nonlinear transformation tasks is independent of the readout scheme, provided that the output space captures enough nonlinear dynamics. This suggests that the intrinsic magnon interactions are key to unlocking high-performance magnetic reservoirs for future neuromorphic applications.

Nitrogen-vacancy (N-$V$) centers in diamond are widely used in quantum information science, but existing methods to fabricate N-$V$ centers rely on damaging the diamond lattice, and usually lead to poor optical coherence. The authors propose a nondestructive method, where high-purity diamonds are annealed under high pressure and high temperature, to generate N-$V$ centers with excellent optical, spin, and charge properties. These results provide new insights into the diffusion dynamics of defects under extreme conditions, and indicate that even the ultrapure diamond contains enough nitrogen and vacancies to form N-$V$ centers.

X-ray absorption spectroscopy (XAS) and electron-energy-loss spectroscopy (EELS) are crucial for material characterization. XAS excels in signal-to-noise ratio and energy range, while EELS offers atomic-scale spatial resolution but struggles with higher ionization energies. This study introduces an EELS spectrometer that achieves high spatial resolution and probes higher ionization energies through optical adjustments. This advancement enhances material analysis at submicrometer scales and provides new insights into element-specific bond lengths and oxidation states, potentially impacting fields such as nanotechnology and materials science.

Gigahertz-frequency surface phonons exhibit a large density of states, which can strongly couple to two-dimensional (2D) electronic, magnetic, and excitonic materials on a piezoelectric crystal, facilitating the study of phonon-assisted quantum engineering. Precise imaging of these phonons is crucial for studying their interaction with various carriers or quasiparticles in 2D materials. This study offers a technique for microfocused Brillouin light scattering for high-fidelity, spatiotemporally resolved imaging of the spatial distribution and time evolution of 1D and 2D surface phonons. This approach is a significant tool for designing and characterizing on-chip phononic devices.

Broadband microwave absorbers play a vital role in many applications. This study proposes a metamaterial microwave absorber that combines the anomalous Brewster effect with impedance-gradient matching. The authors explore the broadband response, high absorption, and optical transparency of this structure through electromagnetic simulations and microwave experiments. Additionally, deep-learning techniques are employed to optimize its parameters, leading to further broadening of the operational bandwidth. Such optically transparent microwave absorbers promise wide applications, such as special windows for electromagnetic shielding and stealth.

Isolated attosecond γ-ray pulses carrying transverse orbital angular momentum (TOAM) are pivotal for research in nuclear physics and quantum electrodynamics, but their production is challenging. This study uses a single spatiotemporal-optical-vortex laser to select and accelerate a 300-attosecond electron slice with TOAM, which collides with a reflected laser front to trigger nonlinear Compton scattering, producing a collimated, ultrabrilliant isolated γ-ray pulse. Such isolated pulses with TOAM will enable time-resolved nuclear detection, angular-momentum-sensitive photonuclear reactions, and multiple analyses in nuclear physics.

Flow focusing can be used to produce monodisperse microbubbles, for e.g. biomedical applications. However, industrial scale-up requires a parallelization of channels, which results in a decrease of monodispersity. This study showcases that ultrasound actuation can be used to fine-tune both bubble size and production rate. These findings present a fresh and cost-effective strategy for increasing monodispersity in a parallelized microfluidic system.

p-n junctions are utilized in almost all semiconductor devices. Here the authors present room-temperature electrical spin injection, transport, and detection via band-to-band tunneling in p-n-junction germanium devices. Their approach offers good insight for operating a spin-based tunnel field-effect transistor at room temperature (rather than at low temperature, as in the past), and the prospect of room-temperature semiconductor spintronics is quite exciting.

The controllable hybridization between right- and left-handed magnon modes is an important topic for utilizing the chiral degree of freedom in magnonics. It is commonly believed that the hybridization between different chiral magnon modes is a standard feature in the canted magnetic phase. This study discovers the presence of a magic ratio in canted ferrimagnets where the hybridization is extremely suppressed in both linear and nonlinear regimes. Combined with level-synchronization predictions, these results not only deepen the understanding of magnon mode hybridization in ferrimagnets, but also enrich the control methods for chiral magnons.

The platform based on mixed-dimensional van der Waals heterostructures is promising for compact, energy-efficient analog and digital electronics on a single substrate. Hurdles include an incomplete understanding of charge behavior at atomically thin junctions, and technical difficulties in fabricating scalable, defect-free interfaces. This study overcomes those barriers via a two-step growth strategy and detailed transport measurements, revealing a nanometer-scale depletion region and gate-tunable diode characteristics. Individual Te and MoS${}_2$ regions can function as high-performance $p-$ and $n-$type FETs, respectively, enabling complete CMOS logic operations on the same chip.

The authors propose engineering non-Hermitian optical couplers so that external radiation enters the system through such a unidirectional coupler, but cannot escape. Unidirectionality is achieved by combining periodic modulation of the refraction index (the Hermitian part) with the gain or loss (non-Hermitian part) of the coupler. This results in an interesting physical effect, violating the usual action-reaction laws, and also leads to practical consequences, such as enhanced absorption of the trapped light. Enhanced absorption is demonstrated by measuring a greater temperature increase under unidirectional coupling, compared to a reference with symmetric coupling.

Physical learning machines promise to overcome the von Neumann bottleneck by implementing highly energy-efficient in-situ adaptation. This adaptation requires parameter updates that are local in space and time, while being robust to the inherent noise in physical substrates. This study embraces physical noise generated by stochastic magnetic tunnel junctions as a mechanism for learning via a combination with a recent local noise-based learning rule. The authors demonstrate that learning based on physical noise is a viable strategy, scalable to larger systems and a variety of physical substrates.

Soft ionic circuitry promises to create soft control systems and active materials that can sense, assess information, and respond to their environment. This complex behavior is enabled by charged polymers that act as ionic semiconductors, but their widespread use is inhibited by a lack of suitable design tools. The authors develop a lumped-element model that incorporates key effects and enables the design and analysis of large-scale ionic systems. Their tool illuminates the performance and limits of existing devices, and principles for designing a fully ionic soft-robot control system. This model will enable the field of ionics to move from building single devices to whole systems.

In the ever-evolving landscape of computational science, tensor networks have emerged as a versatile toolset to simulate both quantum and classical many-body systems. This study investigates their applicability to complex optimization problems, where quantum annealing devices have generated significant interest. A challenge in applying tensor networks here is the high connectivity of the devices, which this work effectively leverages by utilizing sparse structures in construction, plus hardware acceleration. The authors quantify the limitations of their deterministic approach, and find that in certain scenarios it might outperform quantum annealers or randomized classical solvers.

Linear inductors are integral components of superconducting circuits, but making them simultaneously compact, linear, and low-loss is challenging. The authors overcome this challenge using thin films of superconducting granular aluminum (grAl). By using an ex situ bandage technique, they integrate the grAl inductors with tantalum capacitor pads to make resonators with quality factors exceeding 3.5 million. These inductors are a valuable addition to the circuit QED toolkit and will find applications in circuits that are limited by the nonidealities of Josephson junction arrays or geometric inductances.

Josephson parametric amplifiers are essential components for quantum microwave measurements, but their high pump power requirement and unwanted pump leakage into the signal circuitry pose significant challenges for scalable implementation. This study presents a framework for integrating on-chip microwave filters with the amplifiers, improving power efficiency while suppressing pump leakage. The authors further investigate the amplifier’s robustness to thermal noise from the pump line. These results offer practical strategies for reducing the thermal load and component overhead in large-scale quantum processor readout systems.

Quantum annealing is a promising approach to solving a diversity of classical optimization problems across different fields, but real-world problems are often represented by densely connected graphs, which cannot be directly implemented in hardware in a scalable way. This work overcomes this limitation by presenting a very sparse architecture that results in effective dense connectivities. This result will have an impact on the engineering challenge of building large-scale quantum annealing devices that can solve practical optimization problems in several industry sectors, such as logistics, energy, or finance.

Physical reservoir computing holds promise for energy-efficient, real-time information processing, but its development is hindered by limited understanding of the nonlinear dynamics in physical substrates like magnons. The authors use time-resolved Brillouin light scattering microscopy to evaluate a magnon-scattering reservoir in a single magnetic vortex disk, and find that its ability to perform memory and nonlinear transformation tasks is independent of the readout scheme, provided that the output space captures enough nonlinear dynamics. This suggests that the intrinsic magnon interactions are key to unlocking high-performance magnetic reservoirs for future neuromorphic applications.

Nitrogen-vacancy (N-$V$) centers in diamond are widely used in quantum information science, but existing methods to fabricate N-$V$ centers rely on damaging the diamond lattice, and usually lead to poor optical coherence. The authors propose a nondestructive method, where high-purity diamonds are annealed under high pressure and high temperature, to generate N-$V$ centers with excellent optical, spin, and charge properties. These results provide new insights into the diffusion dynamics of defects under extreme conditions, and indicate that even the ultrapure diamond contains enough nitrogen and vacancies to form N-$V$ centers.

X-ray absorption spectroscopy (XAS) and electron-energy-loss spectroscopy (EELS) are crucial for material characterization. XAS excels in signal-to-noise ratio and energy range, while EELS offers atomic-scale spatial resolution but struggles with higher ionization energies. This study introduces an EELS spectrometer that achieves high spatial resolution and probes higher ionization energies through optical adjustments. This advancement enhances material analysis at submicrometer scales and provides new insights into element-specific bond lengths and oxidation states, potentially impacting fields such as nanotechnology and materials science.