High-dynamic-range magnetometry with a single electronic spin in diamond

A wide dynamic range diamond quantum sensor as an electric vehicle battery monitor

To demonstrate the application capability of the diamond quantum sensor as an electric vehicle (EV) battery monitor, we (i) investigated the measurable current in a real car noise level and (ii) compared the linearity with conventional sensors. Consequently, (i) we could measure a 20 mA current pulse even under an external magnetic field of 80 µT, which is larger than that of 50 µT around the EV battery module in a real car during driving. The 20 mA pulse measurement corresponds to the EV battery state of charge estimation accuracy of 0.2% in the standard driving pattern, which is smaller than the present level of 10%. (ii) The linearity degradation seen in the Hall sensor near the upper limit of the measurement range was not seen in the diamond sensor. Although the Hall sensor and the shunt resistor showed linearity degradation in the current range of several tens of amperes or less, the degradation was smaller for the diamond sensor. The transverse magnetic field effect in the diamond sensor on the linearity was estimated to be less than 0.01% for a several-degree misalignment of the sensor surface to the magnetic field direction and under a 340 A current. This article is part of the Theo Murphy meeting issue 'Diamond for quantum applications'.

Optimizing NV magnetometry for Magnetoneurography and Magnetomyography applications

Magnetometers based on color centers in diamond are setting new frontiers for sensing capabilities due to their combined extraordinary performances in sensitivity, bandwidth, dynamic range, and spatial resolution, with stable operability in a wide range of conditions ranging from room to low temperatures. This has allowed for its wide range of applications, from biology and chemical studies to industrial applications. Among the many, sensing of bio-magnetic fields from muscular and neurophysiology has been one of the most attractive applications for NV magnetometry due to its compact and proximal sensing capability. Although SQUID magnetometers and optically pumped magnetometers (OPM) have made huge progress in Magnetomyography (MMG) and Magnetoneurography (MNG), exploring the same with NV magnetometry is scant at best. Given the room temperature operability and gradiometric applications of the NV magnetometer, it could be highly sensitive in the pT / Hz -range even without magnetic shielding, bringing it close to industrial applications. The presented work here elaborates on the performance metrics of these magnetometers to the state-of-the-art techniques by analyzing the sensitivity, dynamic range, and bandwidth, and discusses the potential benefits of using NV magnetometers for MMG and MNG applications.

Simplified Algorithms for Adaptive Experiment Design in Parameter Estimation

Measurements to estimate parameters of a model are commonplace in the physical sciences, where the traditional approach to automation is to use a sequence of preselected settings followed by least-squares fitting of a model function to the data. This measure-then-fit approach is simple and effective and entirely appropriate for many applications but when measurement resources are limited, efficiency becomes more important. To increase efficiency, Bayesian experiment design allows measurement settings to be chosen adaptively based on accumulated data and utility, the predicted improvement in results as a function of settings. However, the calculation of utility has been judged too impractical for most applications. In this paper, we introduce computational methods and simplified algorithms that accelerate utility calculations by over an order of magnitude, with only slight degradation in measurement efficiency. The methods eliminate utility calculation as a barrier to practical application of efficient adaptive measurement.

Sequential Measurements for Quantum-Enhanced Magnetometry in Spin Chain Probes

Quantum sensors outperform their classical counterparts in their estimation precision, given the same amount of resources. So far, quantum-enhanced sensitivity has been achieved by exploiting the superposition principle. This enhancement has been obtained for particular forms of entangled states, adaptive measurement basis change, critical many-body systems, and steady state of periodically driven systems. Here, we introduce a different approach to obtain quantum-enhanced sensitivity in a many-body probe through utilizing the nature of quantum measurement and its subsequent wave function collapse without demanding prior entanglement. Our protocol consists of a sequence of local measurements, without reinitialization, performed regularly during the evolution of a many-body probe. As the number of sequences increases, the sensing precision is enhanced beyond the standard limit, reaching the Heisenberg bound asymptotically. The benefits of the protocol are multifold as it uses a product initial state and avoids complex initialization (e.g., prior entangled states or critical ground states) and allows for remote quantum sensing.

High-precision robust monitoring of charge/discharge current over a wide dynamic range for electric vehicle batteries using diamond quantum sensors

Accurate prediction of the remaining driving range of electric vehicles is difficult because the state-of-the-art sensors for measuring battery current are not accurate enough to estimate the state of charge. This is because the battery current of EVs can reach a maximum of several hundred amperes while the average current is only approximately 10 A, and ordinary sensors do not have an accuracy of several tens of milliamperes while maintaining a dynamic range of several hundred amperes. Therefore, the state of charge has to be estimated with an ambiguity of approximately 10%, which makes the battery usage inefficient. This study resolves this limitation by developing a diamond quantum sensor with an inherently wide dynamic range and high sensitivity for measuring the battery current. The design uses the differential detection of two sensors to eliminate in-vehicle common-mode environmental noise, and a mixed analog-digital control to trace the magnetic resonance microwave frequencies of the quantum sensor without deviation over a wide dynamic range. The prototype battery monitor was fabricated and tested. The battery module current was measured up to 130 A covering WLTC driving pattern, and the accuracy of the current sensor to estimate battery state of charge was analyzed to be 10 mA, which will lead to 0.2% CO₂ reduction emitted in the 2030 WW transportation field. Moreover, an operating temperature range of - 40 to + 85 °C and a maximum current dynamic range of ± 1000 A were confirmed.

Quantum-assisted distortion-free audio signal sensing

Quantum sensors are known for their high sensitivity in sensing applications. However, this sensitivity often comes with severe restrictions on other parameters which are also important. Examples are that in measurements of arbitrary signals, limitation in linear dynamic range could introduce distortions in magnitude and phase of the signal. High frequency resolution is another important feature for reconstructing unknown signals. Here, we demonstrate a distortion-free quantum sensing protocol that combines a quantum phase-sensitive detection with heterodyne readout. We present theoretical and experimental investigations using nitrogen-vacancy centers in diamond, showing the capability of reconstructing audio frequency signals with an extended linear dynamic range and high frequency resolution. Melody and speech based signals are used for demonstrating the features. The methods could broaden the horizon for quantum sensors towards applications, e.g. telecommunication in challenging environment, where low-distortion measurements are required at multiple frequency bands within a limited volume.

High sensitivity in quantum sensing comes often at the expense of other figures of merit, usually resulting in distortion. Here, the authors propose a protocol with good sensitivity, readout linearity and high frequency resolution, and benchmark it through signal measurements at audio bands with NV centers.

Ultra-high dynamic range quantum measurement retaining its sensitivity

Quantum sensors are highly sensitive since they capitalise on fragile quantum properties such as coherence, while enabling ultra-high spatial resolution. For sensing, the crux is to minimise the measurement uncertainty in a chosen range within a given time. However, basic quantum sensing protocols cannot simultaneously achieve both a high sensitivity and a large range. Here, we demonstrate a non-adaptive algorithm for increasing this range, in principle without limit, for alternating-current field sensing, while being able to get arbitrarily close to the best possible sensitivity. Therefore, it outperforms the standard measurement concept in both sensitivity and range. Also, we explore this algorithm thoroughly by simulation, and discuss the T⁻² scaling that this algorithm approaches in the coherent regime, as opposed to the T^−1/2 of the standard measurement. The same algorithm can be applied to any modulo-limited sensor.

Usually, quantum sensing protocols impose a trade-off between sensitivity and maximum range. Here, the authors demonstrate a non-adaptive algorithm for quantum sensors to measure AC fields with a large range for which the loss in sensitivity is negligible.

Sequential Bayesian experiment design for adaptive Ramsey sequence measurements

The Ramsey sequence is a canonical example of a quantum phase measurement for a spin qubit. In Ramsey measurements, the measurement efficiency can be optimized through careful selection of settings for the phase accumulation time setting, τ. This paper implements a sequential Bayesian experiment design protocol in low-fidelity Ramsey measurements, and its performance is compared to a previously reported adaptive heuristic protocol, a quantum phase estimation algorithm, and random setting choices. A workflow allowing measurements and design calculations to run concurrently largely eliminates computation time from measurement overhead. When precession frequency is the lone parameter to estimate, the Bayesian design is faster by factors of roughly 2 and 4 and 5 relative to the adaptive heuristic, random τ choices and the quantum phase estimation algorithm respectively. When four parameters are to be determined, Bayesian experiment design and random τ choices can converge to roughy equivalent sensitivity, but the Bayesian method converges 4 times faster.

Geometric phase magnetometry using a solid-state spin

A key challenge of magnetometry lies in the simultaneous optimization of magnetic field sensitivity and maximum field range. In interferometry-based magnetometry, a quantum two-level system acquires a dynamic phase in response to an applied magnetic field. However, due to the 2π periodicity of the phase, increasing the coherent interrogation time to improve sensitivity reduces field range. Here we introduce a route towards both large magnetic field range and high sensitivity via measurements of the geometric phase acquired by a quantum two-level system. We experimentally demonstrate geometric-phase magnetometry using the electronic spin associated with the nitrogen vacancy (NV) color center in diamond. Our approach enables unwrapping of the 2π phase ambiguity, enhancing field range by 400 times. We also find additional sensitivity improvement in the nonadiabatic regime, and study how geometric-phase decoherence depends on adiabaticity. Our results show that the geometric phase can be a versatile tool for quantum sensing applications.

When performing interferometry-based magnetometry, there is generally a trade-off between sensitivity and range. Here, instead, the authors demonstrate a geometric-phase-based protocol which allows a 400-fold enhancement in static magnetic field range with a single NV-centre without reducing sensitivity.

Experimental optical phase measurement approaching the exact Heisenberg limit

The use of quantum resources can provide measurement precision beyond the shot-noise limit (SNL). The task of ab initio optical phase measurement—the estimation of a completely unknown phase—has been experimentally demonstrated with precision beyond the SNL, and even scaling like the ultimate bound, the Heisenberg limit (HL), but with an overhead factor. However, existing approaches have not been able—even in principle—to achieve the best possible precision, saturating the HL exactly. Here we demonstrate a scheme to achieve true HL phase measurement, using a combination of three techniques: entanglement, multiple samplings of the phase shift, and adaptive measurement. Our experimental demonstration of the scheme uses two photonic qubits, one double passed, so that, for a successful coincidence detection, the number of photon-passes is N = 3. We achieve a precision that is within 4% of the HL. This scheme can be extended to higher N and other physical systems.

Measurements of an unknown optical phase have not yet been performed with the ultimate precision, i.e. saturating the Heisenberg limit. Here, Daryanoosh et al. demonstrate this with a precision within 4% of the Heisenberg limit by combining photonic entanglement and multiple passes.

Nanoscale Spin Manipulation with Pulsed Magnetic Gradient Fields from a Hard Disc Drive Writer

The individual and coherent control of solid-state based electron spins is important covering fields from quantum information processing and quantum metrology to material research and medical imaging. Especially for the control of individual spins in nanoscale networks, the generation of strong, fast, and localized magnetic fields is crucial. Highly engineered devices that demonstrate most of the desired features are found in nanometer size magnetic writers of hard disk drives (HDD). Currently, however, their nanoscale operation in particular comes at the cost of excessive magnetic noise. Here, we present HDD writers as a tool for the efficient manipulation of single as well as multiple spins. We show that their tunable gradients of up to 100 μT/nm can be used to spectrally address individual spins on the nanoscale. Their gigahertz bandwidth allows one to switch control fields within nanoseconds, faster than characteristic time scales such as Rabi and Larmor periods, spin-spin couplings, or optical transitions, thus extending the set of feasible spin manipulations. We used the fields to drive spin transitions through nonadiabatic fast passages or to enable the optical readout of spin states in strong misaligned fields. Building on these techniques, we further apply the large magnetic field gradients for microwave selective addressing of single spins and show its use for the nanoscale optical colocalization of two emitters.

Dynamical sensitivity control of a single-spin quantum sensor

The Nitrogen-Vacancy (NV) defect in diamond is a unique quantum system that offers precision sensing of nanoscale physical quantities at room temperature beyond the current state-of-the-art. The benchmark parameters for nanoscale magnetometry applications are sensitivity, spectral resolution, and dynamic range. Under realistic conditions the NV sensors controlled by conventional sensing schemes suffer from limitations of these parameters. Here we experimentally show a new method called dynamical sensitivity control (DYSCO) that boost the benchmark parameters and thus extends the practical applicability of the NV spin for nanoscale sensing. In contrast to conventional dynamical decoupling schemes, where π pulse trains toggle the spin precession abruptly, the DYSCO method allows for a smooth, analog modulation of the quantum probe’s sensitivity. Our method decouples frequency selectivity and spectral resolution unconstrained over the bandwidth (1.85 MHz–392 Hz in our experiments). Using DYSCO we demonstrate high-accuracy NV magnetometry without |2π| ambiguities, an enhancement of the dynamic range by a factor of 4 · 10³, and interrogation times exceeding 2 ms in off-the-shelf diamond. In a broader perspective the DYSCO method provides a handle on the inherent dynamics of quantum systems offering decisive advantages for NV centre based applications notably in quantum information and single molecule NMR/MRI.

Nanoscale Imaging of Current Density with a Single-Spin Magnetometer

Charge transport in nanostructures and thin films is fundamental to many phenomena and processes in science and technology, ranging from quantum effects and electronic correlations in mesoscopic physics, to integrated charge- or spin-based electronic circuits, to photoactive layers in energy research. Direct visualization of the charge flow in such structures is challenging due to their nanometer size and the itinerant nature of currents. In this work, we demonstrate noninvasive magnetic imaging of current density in two-dimensional conductor networks including metallic nanowires and carbon nanotubes. Our sensor is the electronic spin of a diamond nitrogen-vacancy center attached to a scanning tip and operated under ambient conditions. Using a differential measurement technique, we detect DC currents down to a few μA with a current density noise floor of ∼2 × 10⁴ A/cm². Reconstructed images have a spatial resolution of typically 50 nm, with a best-effort value of 22 nm. Current density imaging offers a new route for studying electronic transport and conductance variations in two-dimensional materials and devices, with many exciting applications in condensed matter physics and materials science.

Enhancing quantum sensing sensitivity by a quantum memory

In quantum sensing, precision is typically limited by the maximum time interval over which phase can be accumulated. Memories have been used to enhance this time interval beyond the coherence lifetime and thus gain precision. Here, we demonstrate that by using a quantum memory an increased sensitivity can also be achieved. To this end, we use entanglement in a hybrid spin system comprising a sensing and a memory qubit associated with a single nitrogen-vacancy centre in diamond. With the memory we retain the full quantum state even after coherence decay of the sensor, which enables coherent interaction with distinct weakly coupled nuclear spin qubits. We benchmark the performance of our hybrid quantum system against use of the sensing qubit alone by gradually increasing the entanglement of sensor and memory. We further apply this quantum sensor-memory pair for high-resolution NMR spectroscopy of single ¹³C nuclear spins.

In quantum sensing, memories have been used to enhance measurement precision. Here, the authors demonstrate the use of a memory to increase sensitivity of single ¹³C nuclear spins spectroscopy by storing the full sensor state and entangling memory and sensor.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Identification of Nanoparticle Prototypes and Archetypes

High-throughput (HT) computational characterization of nanomaterials is poised to accelerate novel material breakthroughs. The number of possible nanomaterials is increasing exponentially along with their complexity, and so statistical and information technology will play a fundamental role in rationalizing nanomaterials HT data. We demonstrate that multivariate statistical analysis of heterogeneous ensembles can identify the truly significant nanoparticles and their most relevant properties. Virtual samples of diamond nanoparticles and graphene nanoflakes are characterized using clustering and archetypal analysis, where we find that saturated particles are defined by their geometry, while nonsaturated nanoparticles are defined by their carbon chemistry. At the complex hull of the nanostructure spaces, a combination of complex archetypes can efficiency describe a large number of members of the ensembles, whereas the regular shapes that are typically assumed to be representative can only describe a small set of the most regular morphologies. This approach provides a route toward the characterization of computationally intractable virtual nanomaterial spaces, which can aid nanomaterials discovery in the foreseen big data scenario.

A nitrogen-vacancy spin based molecular structure microscope using multiplexed projection reconstruction

Methods and techniques to measure and image beyond the state-of-the-art have always been influential in propelling basic science and technology. Because current technologies are venturing into nanoscopic and molecular-scale fabrication, atomic-scale measurement techniques are inevitable. One such emerging sensing method uses the spins associated with nitrogen-vacancy (NV) defects in diamond. The uniqueness of this NV sensor is its atomic size and ability to perform precision sensing under ambient conditions conveniently using light and microwaves (MW). These advantages have unique applications in nanoscale sensing and imaging of magnetic fields from nuclear spins in single biomolecules. During the last few years, several encouraging results have emerged towards the realization of an NV spin-based molecular structure microscope. Here, we present a projection-reconstruction method that retrieves the three-dimensional structure of a single molecule from the nuclear spin noise signatures. We validate this method using numerical simulations and reconstruct the structure of a molecular phantom β-cyclodextrin, revealing the characteristic toroidal shape.

Nanodiamonds and silicon quantum dots: ultrastable and biocompatible luminescent nanoprobes for long-term bioimaging

Ultra-stability and low-toxicity of silicon quantum dots and fluorescent nanodiamonds for long-termin vitroandin vivobioimaging are demonstrated.

Efficient estimation of resonant coupling between quantum systems

We present an efficient method for the characterization of two coupled discrete quantum systems, one of which can be controlled and measured. For two systems with transition frequencies ωq, ωr, and coupling strength g we show how to obtain estimates of g and ωr whose error decreases exponentially in the number of measurement shots rather than as a power law expected in simple approaches. Our algorithm can thereby identify g and ωr simultaneously with high precision in a few hundred measurement shots. This is achieved by adapting measurement settings upon data as it is collected. We also introduce a method to eliminate erroneous estimates with small overhead. Our algorithm is robust against the presence of relaxation and typical noise. Our results are applicable to many candidate technologies for quantum computation, in particular, for the characterization of spurious two-level systems in superconducting qubits or stripline resonators.

Suppressing qubit dephasing using real-time Hamiltonian estimation

Unwanted interaction between a quantum system and its fluctuating environment leads to decoherence and is the primary obstacle to establishing a scalable quantum information processing architecture. Strategies such as environmental and materials engineering, quantum error correction and dynamical decoupling can mitigate decoherence, but generally increase experimental complexity. Here we improve coherence in a qubit using real-time Hamiltonian parameter estimation. Using a rapidly converging Bayesian approach, we precisely measure the splitting in a singlet-triplet spin qubit faster than the surrounding nuclear bath fluctuates. We continuously adjust qubit control parameters based on this information, thereby improving the inhomogenously broadened coherence time (T2*) from tens of nanoseconds to >2 μs. Because the technique demonstrated here is compatible with arbitrary qubit operations, it is a natural complement to quantum error correction and can be used to improve the performance of a wide variety of qubits in both meteorological and quantum information processing applications.

Scalable fabrication of high purity diamond nanocrystals with long-spin-coherence nitrogen vacancy centers

The combination of long spin coherence time and nanoscale size has made nitrogen vacancy (NV) centers in nanodiamonds the subject of much interest for quantum information and sensing applications. However, currently available high-pressure high-temperature (HPHT) nanodiamonds have a high concentration of paramagnetic impurities that limit their spin coherence time to the order of microseconds, less than 1% of that observed in bulk diamond. In this work, we use a porous metal mask and a reactive ion etching process to fabricate nanocrystals from high-purity chemical vapor deposition (CVD) diamond. We show that NV centers in these CVD nanodiamonds exhibit record-long spin coherence times in excess of 200 μs, enabling magnetic field sensitivities of 290 nT Hz(-1/2) with the spatial resolution characteristic of a 50 nm diameter probe.

Fast optical cooling of nanomechanical cantilever with the dynamical Zeeman effect

We propose an efficient optical electromagnetically induced transparency (EIT) cooling scheme for a cantilever with a nitrogen-vacancy center attached in a non-uniform magnetic field using dynamical Zeeman effect. In our scheme, the Zeeman effect combined with the quantum interference effect enhances the desired cooling transition and suppresses the undesired heating transitions. As a result, the cantilever can be cooled down to nearly the vibrational ground state under realistic experimental conditions within a short time. This efficient optical EIT cooling scheme can be reduced to the typical EIT cooling scheme under special conditions.

High-dynamic-range imaging of nanoscale magnetic fields using optimal control of a single qubit

We present a novel spectroscopy protocol based on optimal control of a single quantum system. It enables measurements with quantum-limited sensitivity (η(ω)[proportionality](1/√[T(2)(*)]), T(2)(*) denoting the system's coherence time) but has an orders of magnitude larger dynamic range than pulsed spectroscopy methods previously employed for this task. We employ this protocol to image nanoscale magnetic fields with a single scanning nitrogen-vacancy center in diamond. Here, our scheme enables quantitative imaging of a strongly inhomogeneous field in a single scan without closed-loop control, which has previously been necessary to achieve this goal.

Understanding ultrafine nanodiamond formation using nanostructured explosives

The detonation process is able to build new materials with a bottom-up approach. Diamond, the hardest material on earth, can be synthesized in this way. This unconventional synthesis route is possible due to the presence of carbon inside the high-explosive molecules: firing high-explosive mixtures with a negative oxygen balance in a non-oxidative environment leads to the formation of nanodiamond particles. Trinitrotoluene (TNT) and hexogen (RDX) are the explosives primarily used to synthesize nanodiamonds. Here we show that the use of nanostructured explosive charges leads to the formation of smaller detonation nanodiamonds, and it also provides new understanding of nanodiamond formation-mechanisms. The discontinuity of the explosive at the nanoscale level plays the key role in modifying the diamond particle size, and therefore varying the size with microstructured charges is impossible.

A scanning superconducting quantum interference device with single electron spin sensitivity

Superconducting quantum interference devices (SQUIDs) can be used to detect weak magnetic fields and have traditionally been the most sensitive magnetometers available. However, because of their relatively large effective size (on the order of 1 µm), the devices have so far been unable to achieve the level of sensitivity required to detect the field generated by the spin magnetic moment (μB) of a single electron. Here we show that nanoscale SQUIDs with diameters as small as 46 nm can be fabricated on the apex of a sharp tip. The nano-SQUIDs have an extremely low flux noise of 50 nΦ0 Hz(-1/2) and a spin sensitivity of down to 0.38 μB Hz(-1/2), which is almost two orders of magnitude better than previous devices. They can also operate over a wide range of magnetic fields, providing a sensitivity of 0.6 μB Hz(-1/2) at 1 T. The unique geometry of our nano-SQUIDs makes them well suited to scanning probe microscopy, and we use the devices to image vortices in a type II superconductor, spaced 120 nm apart, and to record magnetic fields due to alternating currents down to 50 nT.

Super-resolving single nitrogen vacancy centers within single nanodiamonds using a localization microscope

In this paper, we show super-resolving single nitrogen vacancy (NV) centers with a sub-20 nanometer resolution in a wide-field localization microscope based on the discovery of photoluminescence blinking in high-pressure high-temperature nanodiamonds (NDs). The photon statistics reveals that NDs containing not only single but also multiple NV centers show photoluminescence blinking. The combination of an atomic force microscope and an optical localization microscope built on the blinking feature enables the optically resolved two NV centers within single NDs for the first time. Our method establishes new avenues for studying nanoscale photon dynamics associated with single NV centers within NDs together with ND-based ultra-sensitive bioimaging devices.

Robust absolute magnetometry with organic thin-film devices

Magnetic field sensors based on organic thin-film materials have attracted considerable interest in recent years as they can be manufactured at very low cost and on flexible substrates. However, the technological relevance of such magnetoresistive sensors is limited owing to their narrow magnetic field ranges (∼30 mT) and the continuous calibration required to compensate temperature fluctuations and material degradation. Conversely, magnetic resonance (MR)-based sensors, which utilize fundamental physical relationships for extremely precise measurements of fields, are usually large and expensive. Here we demonstrate an organic magnetic resonance-based magnetometer, employing spin-dependent electronic transitions in an organic diode, which combines the low-cost thin-film fabrication and integration properties of organic electronics with the precision of a MR-based sensor. We show that the device never requires calibration, operates over large temperature and magnetic field ranges, is robust against materials degradation and allows for absolute sensitivities of <50 nT Hz^−1/2.

Magnetometers based on organic magnetoresistance are limited by narrow sensitivity ranges, degradation and temperature fluctuations. Baker et al. demonstrate a magnetic resonance-based organic thin film magnetometer, which overcomes these drawbacks by exploiting the metrological nature of magnetic resonance.

High-dynamic-range magnetometry with a single nuclear spin in diamond

Sensors based on the nitrogen-vacancy defect in diamond are being developed to measure weak magnetic and electric fields at the nanoscale. However, such sensors rely on measurements of a shift in the Lamor frequency of the defect, so an accumulation of quantum phase causes the measurement signal to exhibit a periodic modulation. This means that the measurement time is either restricted to half of one oscillation period, which limits accuracy, or that the magnetic field range must be known in advance. Moreover, the precision increases only slowly (as T(-0.5)) with measurement time T (ref. 3). Here, we implement a quantum phase estimation algorithm on a single nuclear spin in diamond to combine both high sensitivity and high dynamic range. By achieving a scaling of the precision with time to T(-0.85), we improve the sensitivity by a factor of 7.4 for an accessible field range of 16 mT, or, alternatively, we improve the dynamic range by a factor of 130 for a sensitivity of 2.5 µT Hz(-1/2). Quantum phase estimation algorithms have also recently been implemented using a single electron spin in a nitrogen-vacancy centre. These methods are applicable to a variety of field detection schemes, and do not require quantum entanglement.