The magnetic sensing at nanoscale level is a promising and interesting research topic of nanoscience. Indeed, magnetic imaging is a powerful tool for probing biological, chemical and physical systems. The study of small spin cluster, like magnetic molecules and nanoparticles, single electron, cold atom clouds, is one of the most stimulating challenges of applied and basic research of the next years. In particular, the magnetic nanoparticle investigation plays a fundamental role for the modern material science and its relative technological applications like ferrofluids, magnetic refrigeration and biomedical applications, including drug delivery, hyper-thermia cancer treatment and magnetic resonance imaging contrast-agent. Actually, one of the most ambitious goals of the high sensitivity magnetometry is the detection of elementary magnetic moment or spin. In this framework, several efforts have been devoted to the development of a high sensitivity magnetic nanosensor pushing sensing capability to the individual spin level. Among the different magnetic sensors, Superconducting QUantum Interference Devices (SQUIDs) exhibit an ultra high sensitivity and are widely employed in numerous applications. Basically, a SQUID consists of a superconducting ring (sensitive area) interrupted by two Josephson junctions. In the recent years, it has been proved that the magnetic response of nano-objects can be effectively measured by using a SQUID with a very small sensitive area (nanoSQUID). In fact, the sensor noise, expressed in terms of the elementary magnetic moment (spin or Bohr magneton), is linearly dependent on the SQUID loop side length. For this reason, SQUIDs have been progressively miniaturized in order to improve the sensitivity up to few spin per unit of bandwidth. With respect to other techniques, nanoSQUIDs offer the advantage of direct measurement of magnetization changes in small spin systems. In this

This study hypothesizes that the brain shows hyper connectedness as amyotrophic lateral sclerosis (ALS) progresses. 54 patients (classified as “early stage” or “advanced stage”) and 25 controls underwent magnetoencephalography and MRI recordings. The activity of the brain areas was reconstructed, and the synchronization between them was estimated in the classical frequency bands using the phase lag index. Brain topological metrics such as the leaf fraction (number of nodes with degree of 1), the degree divergence (a measure of the scale-freeness) and the degree correlation (a measure of disassortativity) were estimated. Betweenness centrality was used to estimate the centrality of the brain areas.In all frequency bands, it was evident that, the more advanced the disease, the more connected, scale-free and disassortative the brain networks. No differences were evident in specific brain areas. Such modified brain topology is sub-optimal as compared to controls. Within this framework, our study shows that brain networks become more connected according to disease staging in ALS patients.

An integrated magnetic nanosensor based on a niobium dc SQUID (superconducting quantum interference device) for nanoscale applications is presented. The sensor, having a washer shape with a hole of 200 nm and two Josephson-Dayem nanobridges of 80 nm × 100 nm, consists of a Nb(30 nm)/Al(30 nm) bilayer patterned by electron beam lithography (EBL) and shaped by lift-off and reactive ion etch (RIE) processes. The presence of the niobium coils, integrated on-chip and tightly coupled to the SQUID, allows us to easily excite the sensor in order to get the voltage-flux characteristics and to flux bias the SQUID at its optimal point. The measurements were performed at liquid helium temperature. A voltage swing of 75 µV and a maximum voltage-flux transfer coefficient (responsivity) as high as 1 mV/Φ(0) were directly measured from the voltage-flux characteristic. The noise measurements were performed in open loop mode, biasing the SQUID with a dc magnetic flux at its maximum responsivity point and using direct-coupled low-noise readout electronics. A white magnetic flux noise spectral density as low as 2.5 μΦ(0) Hz(-1/2) was achieved, corresponding to a magnetization or spin sensitivity in units of the Bohr magneton of 100 spin Hz(-1/2). Possible applications of this nanosensor can be envisaged in magnetic detection of nanoparticles and small clusters of atoms and molecules, in the measurement of nanoobject magnetization, and in quantum computing.

A high sensitive nano superconducting quantum interference device (nanoSQUID) operating as a magnetic flux to critical current transducer with a suitable feedback circuit is employed to measure the magnetization of ferrimagnetic iron oxide nanoparticles. An improved SQUID responsivity has been obtained by using a loop inductance asymmetry. Iron oxide nanoparticles having a mean diameter of 8 nm have been excited by applying a polarizing field in the plane of the nanoSQUID loop. The field dependence of the nanoparticle magnetization at T = 4.2 K shows magnetic hysteresis. Magnetic relaxation measurements are reported and compared with those obtained by using a commercial measurement system

We investigate the properties of Josephson junction networks with inhomogeneous architecture. The networks are shaped as "square comb" planar lattices on which Josephson junctions link superconducting islands arranged in the plane to generate the pertinent topology. Compared to the behavior of reference linear arrays, the temperature dependencies of the Josephson currents of the branches of the network exhibit relevant differences. The observed phenomena evidence new and surprising behavior of superconducting Josephson arrays as well as remarkable similarities with bosonic junction arrays.