RESUMO
The prevalence of orthopedic implants is increasing with an aging population. These patients are vulnerable to risks from periprosthetic infections and instrument failures. Here, we present a dual-functional smart polymer foil coating compatible with commercial orthopedic implants to address both septic and aseptic failures. Its outer surface features optimum bioinspired mechano-bactericidal nanostructures, capable of killing a wide spectrum of attached pathogens through a physical process to reduce the risk of bacterial infection, without directly releasing any chemicals or harming mammalian cells. On its inner surface in contact with the implant, an array of strain gauges with multiplexing transistors, built on single-crystalline silicon nanomembranes, is incorporated to map the strain experienced by the implant with high sensitivity and spatial resolution, providing information about bone-implant biomechanics for early diagnosis to minimize the probability of catastrophic instrument failures. Their multimodal functionalities, performance, biocompatibility, and stability are authenticated in sheep posterolateral fusion model and rodent implant infection model.
Assuntos
Anti-Infecciosos , Nanoestruturas , Animais , Ovinos , Anti-Infecciosos/farmacologia , Anti-Infecciosos/química , Antibacterianos/farmacologia , Antibacterianos/química , Próteses e Implantes/efeitos adversos , Osso e Ossos , Nanoestruturas/química , MamíferosRESUMO
Analog arithmetic operations are the most fundamental mathematical operations used in image and signal processing as well as artificial intelligence (AI). In-memory computing (IMC) offers a high performance and energy-efficient computing paradigm. To date, in-memory analog arithmetic operations with emerging nonvolatile devices are usually implemented using discrete components, which limits the scalability and blocks large scale integration. Here, a prototypical implementation of in-memory analog arithmetic operations (summation, subtraction and multiplication) is experimentally demonstrated, based on in-memory electrical current sensing units using spin-orbit torque (SOT) devices. The proposed structures for analog arithmetic operations are smaller than the state-of-the-art complementary metal oxide semiconductor (CMOS) counterparts by several orders of magnitude. Moreover, data to be processed and computing results can be locally stored, or the analog computing can be done in the nonvolatile SOT devices, which are exploited to experimentally implement the image edge detection and signal amplitude modulation with a simple structure. Furthermore, an artificial neural network (ANN) with SOT devices based synapses is constructed to realize pattern recognition with high accuracy of ≈95%.
RESUMO
Many living organisms track light sources and halt their movement when alignment is achieved. This phenomenon, known as phototropism, occurs, for example, when plants self-orient to face the sun throughout the day. Although many artificial smart materials exhibit non-directional, nastic behaviour in response to an external stimulus, no synthetic material can intrinsically detect and accurately track the direction of the stimulus, that is, exhibit tropistic behaviour. Here we report an artificial phototropic system based on nanostructured stimuli-responsive polymers that can aim and align to the incident light direction in the three-dimensions over a broad temperature range. Such adaptive reconfiguration is realized through a built-in feedback loop rooted in the photothermal and mechanical properties of the material. This system is termed a sunflower-like biomimetic omnidirectional tracker (SunBOT). We show that an array of SunBOTs can, in principle, be used in solar vapour generation devices, as it achieves up to a 400% solar energy-harvesting enhancement over non-tropistic materials at oblique illumination angles. The principle behind our SunBOTs is universal and can be extended to many responsive materials and a broad range of stimuli.