Search for: All records

Integrated photonic microresonators have become an essential resource for generating photonic qubits for quantum information processing, entanglement distribution and networking, and quantum communications. The pair-generation rate is enhanced by reducing the microresonator radius, but this comes at the cost of increasing the frequency-mode spacing and reducing the quantum information spectral density. Here, we circumvent this rate-density trade-off in an $\mathrm{Al}\mathrm{Ga}\mathrm{As}$-on-insulator photonic device by multiplexing an array of 20 small-radius microresonators, each producing a 650-GHz-spaced comb of time-energy entangled-photon pairs. The resonators can be independently tuned via integrated thermo-optic heaters, enabling control of the mode spacing from degeneracy up to a full free spectral range. We demonstrate simultaneous pumping of five resonators with up to $50$-GHz relative comb offsets, where each resonator produces pairs exhibiting time-energy entanglement visibilities up to $95\mathrm{\%}$, coincidence-to-accidental ratios exceeding $5000$, and an on-chip pair rate up to $2.6{\mathrm{G}\mathrm{Hz}/\mathrm{mW}}^2$per comb line—an improvement over prior work by more than a factor of 40. As a demonstration, we generate frequency-bin qubits in a maximally entangled two-qubit Bell state with fidelity exceeding $87\mathrm{\%}$( $90\mathrm{\%}$with background correction) and detected frequency-bin entanglement rates up to 7 kHz (an approximately $70$MHz on-chip pair rate) using a pump power of approximately $250\text{μ}\mathrm{W}$. Multiplexing small-radius microresonators combines the key capabilities required for programmable and dense photonic qubit encoding while retaining high pair-generation rates, heralded single-photon purity, and entanglement fidelity. Published by the American Physical Society2025 

Active systems of self-propelled agents, e.g., birds, fish, and bacteria, can organize their collective motion into myriad autonomous behaviors. Ubiquitous in nature and across length scales, such phenomena are also amenable to artificial settings, e.g., where brainless self-propelled robots orchestrate their movements into spatial-temporal patterns via the application of external cues or when confined within flexible boundaries. Like their natural counterparts, these approaches typically require many units to initiate collective motion, so controlling the ensuing dynamics is challenging. Here, we demonstrate a simple mechanism that leverages nonlinear elasticity to tame near-diffusive motile particles in forming structures capable of directed motion and other emergent behaviors. Our elasto-active system comprises two centimeter-sized self-propelled microbots connected with elastic beams. These microbots exert forces that suffice to buckle the beam and set the structure in motion. We first rationalize the physics of the interaction between the beam and the microbots. Then we use reduced-order models to predict the interactions of our elasto-active structures with boundaries, e.g., walls and constrictions, and demonstrate how they can exhibit remarkable emergent behaviors such as maze navigation. These findings demonstrate that allowing and understanding changes in body morphology can enhance the capabilities of active matter systems and enable the design of robotic materials capable of space exploration, adaptation, and complex interactions with their surrounding environment. 

Material extrusion (MEX) additive manufacturing has successfully fabricated assembly-free structures composed of different materials processed in the same manufacturing cycle. Materials with different mechanical properties can be employed for the fabrication of bio-inspired structures (i.e., stiff materials connected to soft materials), which are appealing for many fields, such as bio-medical and soft robotics. In the present paper, process parameters and 3D printing strategies are presented to improve the interfacial adhesion between carbon fiber-reinforced nylon (CFPA) and thermoplastic polyurethane (TPU), which are extruded in the same manufacturing cycle using a multi-material MEX setup. To achieve our goal, a double cantilever beam (DCB) test was used to evaluate the mode I fracture toughness. The results show that the application of a heating gun (assembled near the nozzle) provides a statistically significant increase in mean fracture toughness energy from 12.3 kJ/m2 to 33.4 kJ/m2. The underlying mechanism driving this finding was further investigated by quantifying porosity at the multi-material interface using an X-ray computed tomography (CT) system, in addition to quantifying thermal history. The results show that using both bead ironing and the hot air gun during the printing process leads to a reduction of 24% in the average void volume fraction. The findings from the DCB test and X-ray CT analysis agree well with the polymer healing theory, in which an increased thermal history led to an increased fracture toughness at the multi-material interface. Moreover, this study considers the thermal history of each printed layer to correlate the measured debonding energy with results obtained using the reptation theory. 

Fusion-based Material Extrusion (MEX) Additive Manufacturing (AM) processes have been extensively used for the fabrication of smart structures with embedded sensors, proving to have several benefits such as reduction in cost, manufacturing time, and assembly. A major issue negatively affecting 3D printed sensors is related to their poor electrical conductivity, as well as inconsistent electrical performance, which leads to electrical power losses amongst other issues. In the present paper, a set of process parameters (ironing, printing temperature, and infill overlap) has been analyzed by performing a Design of Experiment (DoE) factorial plan to minimize the electrical resistance. The best process parameters configuration involves a remarkable reduction of electrical resistance of 47.9%, as well as an improvement of mechanical properties of 31.9% (ultimate tensile strength), 25.8% (elongation at break) and 28.14% (flexural stress). The microstructure of the obtained results has also been analyzed by employing a high-resolution, X-ray Computed Tomography (X-Ray CT) system showing a reduction of intralayer voids of 19.5%. This work demonstrates a clear correlation between process parameters and the corresponding electrical properties, mechanical properties, and internal microstructure. In the present research, it has been shown that i) it is possible to significantly improve the overall 3D printed sensors performance by process parameter selection, and ii) small changes in the microstructure lead to remarkable improvements in electrical and mechanical performance.