Silicon-vacancy (SiV) centers in diamond combine near-infrared emission with solid-state robustness, but their performance hinges on isolating favorable defect charge states. We demonstrate static and dynamic control of ultra-shallow (<15 nm) SiV ensembles in type IIa diamond. By combining low-energy ion implantation with tailored oxygen and hydrogen terminations, we map regimes that maximise the fluorescent SiV- population over dark charge states. We then realize reversible SiV- to SiV0 conversion using aqueous electrolytic gating with sub-200 mV biases and low optical powers. Our results enable low-power electrical control of SiV ensembles for integrated quantum photonics and biologically compatible voltage imaging in the near-infrared.

Fluorescent nanodiamonds (FNDs) containing nitrogen-vacancy (NV) defects are useful probes for biological imaging and nanoscale sensing applications. Here, we explore the effect of chemical surface modifications and core-shell structures on the T1 relaxation times of 100 nm FNDs hosting nitrogen-vacancy ensembles. The results show that surface oxidation and silica coating of FNDs using the Stöber method can dramatically increase the spin relaxation time from T1 = 320 ± 9 μs to T1 = 1.00 ± 0.06 ms. Using FT-IR and NEXAFS measurements conducted on air oxidized particles, we find that changes to surface functional groups and sp2 carbon density may be responsible for the observed enhancements to the spin relaxation rate. Finally, we use a Monte Carlo model to numerically investigate the relationship between chemical sensitivity and shell thickness and find that a shell thickness on the order of 1 nm should provide the highest sensitivity. Our findings demonstrate that the surface of FNDs can be engineered to exhibit bulk-like T1 relaxation times, in the absence of complex quantum control sequences, which is crucial to advancing biosensing and imaging applications where surface spin noise currently limits measurement precision.

Nitrogen vacancy (NV) centers in diamond are at the heart of many emerging quantum technologies, all of which require control over the NV charge state. Hence, methods for quantification of the relative photoluminescence (PL) intensities of the NV^0 and NV^- charge state, i.e., a charge state ratio, are vital. Several approaches to quantify NV charge state ratios have been reported but are either limited to bulk-like NV diamond samples or yield qualitative results. We propose an NV charge state quantification protocol based on the determination of sample- and experimental setup-specific NV^0 and NV^- reference spectra. The approach employs blue (400-470 nm) and green (480-570 nm) excitation to infer pure NV^0 and NV^- spectra, which are then used to quantify NV charge state ratios in subsequent experiments via least squares fitting. We test our dual excitation protocol (DEP) for a bulk diamond NV sample, 20 and 100 nm nanodiamond particles and compare results with those obtained via other commonly used techniques such as zero-phonon line fitting and non-negative matrix factorization. We find that DEP can be employed across different samples and experimental setups and yields consistent and quantitative results for NV charge state ratios that are in agreement with our understanding of NV photophysics. By providing robust NV charge state quantification across sample types and measurement platforms, DEP will support the development of NV-based quantum technologies.

Remote magnetic sensing can be used to monitor the position of objects in real-time, enabling ground transport monitoring, underground infrastructure mapping and hazardous detection. However, magnetic signals are typically weak and complex, requiring sophisticated physical models to analyze them and a detailed knowledge of the system under study, factors that are frequently unavailable. In this work, we provide a solution to these limitations by demonstrating a Machine Learning (ML) method that can be trained exclusively on experimental data, without the need of any physical model, to predict the position of a magnetic target in real-time. The target can be any object with a magnetic signal above the floor noise, and in this case we use a quantum diamond magnetometer to track variations of few hundreds of nanoteslas produced by an elevator moving along a single axis. The one-dimensional movement is a simple yet challenging scenario, resembling realistic environments such as high buildings, tunnels or train circuits, and is the first step towards building broader applications. Our ML algorithm can be trained in approximately 40 min, achieving over 80 Hz, for a positional error tolerance of 30 cm, which is a precise distance compared to the 4-meter spacing between parking levels. Our results open up the possibility to apply this ML method more generally for real-time monitoring of magnetic objects, which will broaden the scope of magnetic detection applications.

The two-dimensional border-collision normal form is a four-parameter family of piecewise-linear maps generalizing the Lozi family and relevant to diverse applications. It was recently shown to exhibit a chaotic attractor throughout an open region of parameter space, but only for parameter combinations where the map is invertible and orientation-preserving. In this paper we formally identify analogous regions for the orientation-reversing and non-invertible cases, the latter being particularly relevant to control systems. This is achieved by constructing a trapping region in phase space and an invariant expanding cone in tangent space, and provides a more complete picture of robust chaos by showing its presence is disassociated from the global topological properties of the map. We also show some boundaries of the regions are optimal in that they correspond to bifurcations where the chaotic attractor is destroyed.

Diamond-embedded optical fibers with negatively charged nitrogen-vacancy (NV)centers have great potential for remote and distributed magnetic field sensing. However, themagnetic field sensitivity of the currently proposed fiber configuration is limited. This work usesa numerical approach to investigate the effect of structured diamonds on enhancing the excitationand collection efficiency in an optical fiber through a hybrid modelling approach. The resultsrevealed that a 690-times enhancement is achievable with a pillar-shaped diamond embedded ina fiber (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

This study explores the optimisation of a diamond pillar geometry with NV centres near the tip. Modelling incoherent fluorescence emission from NV ensembles, we achieve fivefold backward directional emission over forward. (C) 2024 The Author(s)

Here we show that gradient force optical tweezers can be used to mediate the self-assembly of nanodiamonds into superstructures, which can serve as optically trapped nanoscale quantum probes with superior magnetic resonance sensing capabilities. Enhanced fluorescence rates from nitrogen-vacancy NV- defect centers enable rapid acquisition of optically detected magnetic resonance (ODMR), and shape-induced forces can improve both positioning accuracy and orientation control. The use of confocal imaging can isolate the signal from individual nanodiamonds within the assembly, thereby retaining the desirable properties of a single crystal probe. The improvements afforded by the use nanodiamond assemblies has the potential to resolve dynamic changes through, for example, real-time monitoring of the ODMR contrast.

A hybrid numerical approach is presented to design diamond pillars to enhance the excitation and collection of incoherent NV- photoluminescence for magnetic field sensing. The designed geometry has 690 times higher signal strength than average. (c) 2024 The Author(s)

The essential role of ferritin in iron homeostasis makes its study highly important for fundamental biochemistry research and clinical analysis of iron status, while the magnetic properties of its core mean that it holds interest for understanding magnetism in nanoscale condensed matter systems. Here we employ an emerging magnetic sensing technique using nitrogen-vacancy fluorescence defects in single crystal diamond and nanodiamonds, to quantify the magnetic properties of the iron core of ferritin as it is loaded. We observe anomalous magnetic behavior that can be explained using a theoretical model detailing a morphological change to the iron core occurring at relatively low iron loads. This model provides an L^(0.35±0.06) scaling of the uncompensated Fe spins, in agreement with previous theoretical predictions. The low detection limit (ferritin 2% loaded at a concentration of 7.5 ± 0.4 μg/mL) also makes this a promising method for precision applications where low analyte concentrations are unavoidable, such as in biological research or even clinical analysis.

The development of fluorescent molecular sensors for imaging voltage changes in biological systems has revolutionized neuroscience, providing a tool to capture neuronal activity over large areas with sub-neuron resolution both in vitro and in vivo [1–3]. However, the poor photostability of molecular voltage sensors limits recording times to a few minutes [1–3], posing problems for longitudinal studies of network evolution and disease processes. Here, we present an alternate non-invasive platform for sensitive high resolution voltage imaging using fluorescent, charge-sensitive defects in a transparent diamond substrate [6]. Using these charge state sensors, we establish an all-optical diamond voltage imaging microscope (DVIM) capable of sub-millisecond voltage imaging with sub-millivolt sensitivity. Our work open new pathways for the study of 2D neuronal network cultures as well as 3D brain organoids.

Chemical functionalization of diamond surfaces by hydrogen is an important method for controlling the charge state of near-surface fluorescent color centers, an essential process in fabricating devices such as diamond field-effect transistors and chemical sensors, and a required first step for realizing families of more complex terminations through subsequent chemical processing. In all these cases, termination is typically achieved using hydrogen plasma sources which can etch or damage the diamond as well as deposited materials or embedded colour centers. This work explores alternative methods for lower-damage hydrogenation of diamond surfaces, specifically the annealing of diamond samples in high-purity, non-explosive mixtures of nitrogen and hydrogen gas, and the exposure of samples to microwave hydrogen plasmas in the absence of intentional stage heating. The effectiveness of these methods are characterized by x-ray photoelectron spectroscopy, and comparison of the results to density-functional modelling of the surface hydrogenation energetics implicates surface oxygen ligands as the primary factor limiting the termination quality of annealed samples. Finally, photoluminescence spectroscopy is used to verify that both the annealing and reduced sample temperature plasma methods are non-destructive to near-surface ensembles of nitrogen-vacancy centers, in stark contrast to plasma treatments which use heated sample stages.

Fluorescent nanodiamonds (FNDs) containing nitrogen-vacancy (NV) centers can be used as nanoscale sensors for temperature and electromagnetic fields and find increasing application in many areas of science and technology from biology to quantum metrology. Decreasing the separation between the NV centers and their sensing target often enhances the measurement sensitivity. FND shape strongly affects this distance from NV centers to the particle surface and therefore properties such as brightness and fluorescence spectrum, and can limit sensor applications. Here, we demonstrate that FNDs made from high-pressure high-temperature (HPHT) diamond have predominantly disk-like shapes. Using single-particle atomic force microscopy in combination with ensemble X-ray and light scattering techniques, we show that a typical FND in the 50-150 nm size range has an aspect ratio of three i.e. is three times thinner (e.g. in z) than it is wide (e.g. in the x-y plane). This high aspect ratio of FNDs is important for many quantum sensing measurements as it will enable enhanced sensitivities compared to spherical or other isotropic particle geometries. We investigate FND shape, fluorescence properties, T1 spin relaxation time and T1 fluorescence contrast as functions of particle size and discuss the implications of FND particle shape on quantum sensing applications.

Dense, near-surface (within 10 nm) ensembles of nitrogen-vacancy (NV) centres in diamond are rapidly moving into prominence as the workhorse of a variety of envisaged applications, ranging from the imaging of fast-fluctuating magnetic signals to the facilitation of nuclear hyperpolarisation. Unlike their bulk counterparts, near-surface ensembles suffer from charge stability issues and reduced NV formation efficiency due to the diamond surface's role as a vacancy sink during annealing and an electron sink afterwards. To this end, work is ongoing to determine the best methods for producing high-quality ensembles in this regime. Here we examine the prospects for creating such ensembles cost-effectively by implanting nitrogen-rich type Ib diamond with electron donors, aiming to exploit the high bulk nitrogen density to combat surface-induced band bending in the process. This approach has previously been successful at creating deeper ensembles, however we find that in the near-surface regime there are fewer benefits over nitrogen implantation into pure diamond substrates. Our results suggest that control over diamond surface termination during annealing is key to successfully creating high-yield near-surface NV ensembles generally, and implantation into type Ib diamond may be worth revisiting once that has been accomplished.

In this paper, a probabilistic method for map matching localisation based on magnetometery measurement and total magnetic intensity maps is described. We show that the method is able to effectively address the challenge issues associated with map matching using geophysical maps and provides a mechanism of handling map measurement ambiguity and a way of evaluating the underlying quality. Furthermore, the effectiveness of the magnetometery map matching localisation is demonstrated using the simulation of removing position drift of an inertial navigation system, that arises in INS over a long duration, by the magnetometery aiding in the absence GNSS positioning. Simulation results using online maps verified the robustness and effectiveness of the proposed algorithm, particularly, the aiding precision will be getting better if a high sensitivity magnetometer is used.

Fluorescent nanodiamonds (FNDs) have been exploited as sensitive quantum probes for nanoscale chemical and biological sensing applications, with the majority of demonstrations to date relying on the detection of single FNDs containing either single nitrogen vacancies or nitrogen-vacancy ensembles. This places significant limits on the measurement time, throughput and statistical significance of a measured result as there is usually marked inhomogeneity within FND samples. Here, we have developed a measurement platform that can report the T1 spin relaxation time from a large ensemble of FNDs in solution. We first describe a refined sensing protocol for this modality and then use it to identify the optimal FND size for the detection of paramagnetic targets. Our approach is simple to set up, robust and can be used for rapid material characterization for a variety of in-situ quantum sensing applications.

Quantum diamond microscopy is an emerging versatile technique for studying the magnetic properties of materials. It has been applied extensively in condensed matter physics and materials science and has blossomed into a unique platform for the magnetic study of biological systems. To date, biological demonstrations of quantum diamond microscopy have been performed under ambient conditions. Here, we extend this magnetic microscopy platform to cryogenic temperatures to study magnetic anisotropy and the blocking temperature from an individual iron organelle found within the inner ear of pigeons. Our work confirms that the interface between thin histological tissue sections and diamond can be maintained under cryogenic temperatures. Our magnetic images provide evidence of magnetic anisotropy from a single iron organelle with sub-cellular resolution using this correlative optical imaging method. This approach may be extended to a broad range of systems where magnetic materials play structural and functional roles in biological systems.

Ferritin is the primary storage protein in our body and is of significant interest in biochemistry, nanotechnology, and condensed matter physics. More specifically within this sphere of interest are the magnetic properties of the iron core of ferritin, which have been utilized as a contrast agent in applications such as magnetic resonance imaging. This magnetism depends on both the number of iron atoms present, L, and the nature of the magnetic ordering of their electron spins. In this work, we create a series of ferritin samples containing homogeneous iron loads and apply diamond-based quantum spin relaxometry to systematically study their room temperature magnetic properties. We observe anomalous magnetic behavior that can be explained using a theoretical model detailing a morphological change to the iron core occurring at relatively low iron loads. This model provides an L0.35±0.06 scaling of the uncompensated Fe spins, in agreement with previous theoretical predictions. The necessary inclusion of this morphological change within the model is also supported by electron microscopy studies of ferritin with low iron content. This provides evidence for a magnetic consequence of this morphological change and positions diamond-based quantum spin relaxometry as an effective, noninvasive tool for probing the magnetic properties of metalloproteins. The low detection limit (ferritin 2% loaded at a concentration of 7.5 ± 0.4 μg/mL) also makes this a promising method for precision applications where low analyte concentrations are unavoidable, such as in biological research or even clinical analysis.

Magnetic imaging with nitrogen-vacancy centers in diamond, also known as quantum diamond microscopy, has emerged as a useful technique for the spatial mapping of charge currents in solid-state devices. In this work, we investigate an application to photovoltaic (PV) devices, where the currents are induced by light. We develop a widefield nitrogen-vacancy microscope that allows independent stimulus and measurement of the PV device, and test our system on a range of prototype crystalline silicon PV devices. We first demonstrate micrometer-scale vector magnetic field imaging of custom PV devices illuminated by a focused laser spot, revealing the internal current paths in both short-circuit and open-circuit conditions. We then demonstrate time-resolved imaging of photocurrents in an interdigitated back-contact solar cell, detecting current build-up and subsequent decay near the illumination point with microsecond resolution. This work presents a versatile and accessible analysis platform that may find distinct application in research on emerging PV technologies.