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Abstract We have developed a Yb-doped fiber amplifier (YDFA) using fusion splicing, and characterized its performance with numerical simulation, achieving a continuous output of above 10 W $10~{\mathrm{W}}$ of 1064 nm $1064~{\mathrm{nm}}$ light. The device has been conceptualized to have a configuration as simple as possible; a strategy for using fiber amplifiers in harsh environments where quick repairs and replacements may become necessary at unexpected times.

Abstract In contrast to conventional E-mode resonance accelerators, H-mode DTLs provide for compact linac sections and have been established as highly efficient resonators during the last decades. Thus, H-mode structures are widely applied for heavy-ion acceleration with medium beam energies because of their outstanding capability to provide high acceleration gradients with relatively low energy consumption. To build upon those advantages, an alternating phase focusing beam dynamics layout has been applied to provide for a resonance accelerator design without internal lenses, which allows for eased commissioning, routine operation, maintenance, and potential future upgrades. The features of such a channel are going to be demonstrated on the example of two interdigital H-mode cavities, separated by an external quadrupole triplet. This setup provides for heavy ion (mass-to-charge ratio A / z ≤ 6 $A/z\le 6$ ) acceleration from 300 keV/u to 1400 keV/u and is used as an injector part of the superconducting continuous wave accelerator HELIAC. Hence, this promising approach generally enables effective and compact routine operation for various applications, such as super heavy ion research, material science, and radio biological applications such as heavy-ion tumor therapy.

Abstract HVE-400 ion implanter is special ion implantation equipment for semiconductor materials boron and phosphorus doping. The ion source and extraction deflection system are at high voltage platform, while the corresponding control system is at ground voltage position. The control signals and measurement signals of various parameters at the high-voltage end need to be transmitted between ground voltage and high voltage through optical fibers to isolate high voltage. Upgrading is carried out due to the aging of the optical fiber transmission control and monitoring system, which cannot work stably. The transformation replaces the original distributed single-point control method with an advanced distributed centralized control method, and integrates all control and monitoring functions into an industrial control computer for digital operation and display. In the computer software, two kinds of automatic calculation of ion mass number are designed. After upgrading, the implanter high-voltage platform control and monitoring system features digitalization, centralized control, high reliability, strong anti-interference, fast communication speed, and easy operation.

Abstract This work presents GN-Vision, a novel dual γ-ray and neutron imaging system, which aims at simultaneously obtaining information about the spatial origin of γ-ray and neutron sources. The proposed device is based on two position sensitive detection planes and exploits the Compton imaging technique for the imaging of γ-rays. In addition, spatial distributions of slow- and thermal-neutron sources (

Abstract We present a stabilization technique developed to lock and dynamically tune the resonant frequency of a moderate finesse Fabry-Pérot (FP) cavity used in precision atom-cavity quantum electrodynamics (QED) experiments. Most experimental setups with active stabilization either operate at one fixed resonant frequency or use transfer cavities to achieve the ability to tune the resonant frequency of the cavity. In this work, we present a simple and cost-effective solution to actively stabilize an optical cavity while achieving a dynamic tuning range of over 100 MHz with a precision under 1 MHz. Our unique scheme uses a reference laser locked to an electro-optic modulator (EOM) shifted saturation absorption spectroscopy (SAS) signal. The cavity is locked to the PDH error signal obtained from the dip in the reflected intensity of this reference laser. Our setup provides the feature to efficiently tune the resonant frequency of the cavity by only changing the EOM drive without unlocking and re-locking either the reference laser or the cavity. We present measurements of precision control of the resonant cavity frequency and vacuum Rabi splitting (VRS) to quantify the stability achieved and hence show that this technique is suitable for a variety of cavity QED experiments.

Due to the shortage of kidneys donated for transplantation, surgeons are forced to use the organs with an elevated risk of poor function or even failure. Although the existing methods for pre-transplant quality evaluation have been validated over decades in population cohort studies across the world, new methods are needed as long as delayed graft function or failure in a kidney transplant occurs. In this study, we explored the potential of utilizing photoacoustic (PA) imaging during normothermic machine perfusion (NMP) as a means of evaluating kidney quality. We closely monitored twenty-two porcine kidneys using 3D PA imaging during a two-hour NMP session. Based on biochemical analyses of perfusate and produced urine, the kidneys were categorized into ‘non-functional’ and ‘functional’ groups. Our primary focus was to quantify oxygenation (sO2) within the kidney cortical layer of depths 2 mm, 4 mm, and 6 mm using two-wavelength PA imaging. Next, receiver operating characteristic (ROC) analysis was performed to determine an optimal cortical layer depth and time point for the quantification of sO2 to discriminate between functional and non-functional organs. Finally, for each depth, we assessed the correlation between sO2 and creatinine clearance (CrCl), oxygen consumption (VO2), and renal blood flow (RBF).We found that hypoxia of the renal cortex is associated with poor renal function. In addition, the determination of sO2 within the 2 mm depth of the renal cortex after 30 min of NMP effectively distinguishes between functional and non-functional kidneys. The non-functional kidneys can be detected with the sensitivity and specificity of 80% and 85% respectively, using the cut-off point of sO2

In this article, a mid-infrared all-fiber light-induced thermoelastic spectroscopy (LITES) sensor based on a hollow-core anti-resonant fiber (HC-ARF) was reported for the first time. The HC-ARF was applied as a light transmission medium and gas chamber. The constructed all-fiber structure has merits of low loss, easy optical alignment, good system stability, reduced sensor size and cost. The mid-infrared transmission structure can be utilized to target the strongest gas absorption lines. The reversely-tapered SM1950 fiber and the HC-ARF were spatially butt-coupled with a V-shaped groove between the two fibers to facilitate gas entry. Carbon monoxide (CO) with an absorption line at 4291.50 cm−1 (2.33 µm) was chosen as the target gas to verify the sensing performance. The experimental results showed that the all-fiber LITES sensor based on HC-ARF had an excellent linear response to CO concentration. Allan deviation analysis indicated that the system had excellent long-term stability. A minimum detection limit (MDL) of 3.85 ppm can be obtained when the average time was 100 s

By combining optical absorption contrast and acoustic resolution, photoacoustic imaging (PAI) has broken the barrier in depth for high-resolution optical imaging. Meanwhile, Fluorescence imaging (FLI), owing to advantages of high sensitivity and high specificity with abundant fluorescence agents and proteins, has always been playing a key role in live animal studies. Based on different optical contrast mechanisms, PAI and FLI can provide important complementary information to each other. In this work, we uniquely designed a Photoacoustic-Fluorescence (PA-FL) imaging system that provides real-time dual modality imaging, in which a half-ring ultrasonic array is employed for high quality PA tomography and a specially designed optical window allows simultaneous whole-body fluorescence imaging. The performance of this dual modality system was demonstrated in live animal studies, including real-time monitoring of perfusion and metabolic processes of fluorescent dyes. Our study indicates that the PA-FL imaging system has unique potential for live small animal research.

Methane (CH4) is a greenhouse gas as well as being flammable and explosive. In this manuscript, quartz-enhanced photoacoustic spectroscopy (QEPAS) and heterodyne QEPAS (H-QEPAS) exploring a self-designed quartz tuning fork (QTF) with resonance frequency (f0) of ∼8.7 kHz was utilized to achieve sensitive CH4 detection. Compared with the standard commercial 32.768 kHz QTF, this self-designed QTF with a low f0 and large prong gap has the merits of long energy accumulation time and low optical noise. The strongest line located at 6057.08 cm−1 in the 2v3 overtone band of CH4 was chosen as the target absorption line. A diode laser with a high output power of > 30 mW was utilized as the excitation source. Acoustic micro-resonators (AmRs) were added to the sensor architecture to amplify the intensity of acoustic waves. Compared to the bare QTF, after the addition of AmRs, a signal enhancement of 149-fold and 165-fold were obtained for QEPAS and H-QEPAS systems, respectively. The corresponding minimum detection limits (MDLs) were 711 ppb and 1.06 ppm for QEPAS and H-QEPAS sensors. Furthermore, based on Allan variance analysis the MDLs can be improved to 19 ppb and 27 ppb correspondingly. Compared to the QEPAS sensor, the H-QEPAS sensor shows significantly shorter measurement timeframes, allowing for measuring the gas concentration quickly while simultaneously obtaining f0 of QTF.

We present an all-fiber-based laser gas analyzer (LGA) employing quartz-enhanced photoacoustic spectroscopy (QEPAS) and a side-polished fiber (SPF). The LGA comprises a custom quartz tuning fork (QTF) with 0.8 mm prong spacing, two acoustic micro-resonators (mR) located on either side of the prong spacing, and a single-mode fiber containing a 17 mm polished section passing through both mRs and QTF. The SPF polished face is positioned to enable the evanescent wave (EW) to create a photoacoustic wave and excite the fundamental flexural mode of the QTF. Sensor performance was demonstrated using methane in nitrogen gas mixtures, with CH4 mixing ratios ranging from 75 ppmv to 1% (by volume), measured with an accumulation time of 300 ms, and a minimum detection limit of 34 ppmv subsequently determined. The EW-QEPAS sensor is ideal for miniaturization, as it does not contain any free-space optics and is suitable for gas sensing in harsh environments and where mobility is required.

We introduce a physics-based computational reconstruction framework for non-invasive photoacoustic tomography through a thick aberrating layer. Our wave-based approach leverages an analytic formulation of diffraction to beamform a photoacoustic image, when the aberrating layer profile is known. When the profile of the aberrating layer is unknown, the same analytical formulation serves as the basis for an automatic-differentiation regularized optimization algorithm that simultaneously reconstructs both the profile of the aberrating layer and the optically absorbing targets. Results from numerical studies and proof-of-concept experiments show promise for fast beamforming that takes into account diffraction effects occurring in the propagation through thick, highly-aberrating layers.

Atmospheric aerosols play a pivotal role in the earth-atmospheric system. Analyzing their optical properties, specifically absorption and scattering coefficients, is essential for comprehending the impact of aerosols on climate. When different optical properties of aerosols are individually measured using multiple devices, cumulative errors in the detection results inevitably occur. To address this challenge, based on photoacoustic spectroscopy (PAS) and integrating sphere (IS) scattering enhancement, a compact gas cell (PASIS-Cell) was developed. The PASIS-Cell comprises a dual-T-type photoacoustic cell (DTPAC) and an IS. IS is coupled with DTPAC through a transparent quartz tube, thereby enhancing the scattering signal without compromising the acoustic characteristics of DTPAC. Concurrently, DTPAC can realize high-performance photoacoustic detection of absorption signal. Experimental results demonstrate that PASIS-Cell can simultaneously invert atmospheric aerosol absorption and scattering coefficients, with a minimum detection limit of less than 1 Mm−1, showcasing its potential in the analysis of aerosol optical properties.

Mechanical properties of brain tissues are from principal features from different points of view; diagnosis, the performance of the brain and neurological disorders. Particularly viscoelastic properties of the brain tissues are determinative. In this study based on a proposed accurate and non-invasive method, we have measured the viscoelastic properties of prefrontal cortex and cerebellum, two important brain regions involved in motor learning and pathophysiology of autism spectrum disorder (ASD). In this regard, using photoacoustic systems, viscoelastic properties of tissues from the cerebellum and prefrontal cortex of normal and prenatal VPA (Valproic acid)-exposed (i.e. autistic-like) offspring rats are measured. Results of our study show that the cerebellums of normal tissues are stiffer than the tissue obtained from autistic-like rats, while the viscoelasticity of the prefrontal cortex of normal tissues is higher than that of autistic ones. The proposed method for the measurement of viscoelastic properties of the brain tissue has the potential not only for the fundamental studies but as a diagnosis technique.

The endometrium microvessel system, responsible for supplying oxygen and nutrients to the embryo, holds significant importance in evaluating endometrial receptivity (ER). Visualizing this system directly can significantly enhance ER evaluation. Currently, clinical methods like Narrow-band hysteroscopy and Color Doppler ultrasound are commonly used for uterine blood vessel examination, but they have limitations in depth or resolution. Endoscopic Photoacoustic Imaging (PAE) has proven effective in visualizing microvessels in the digestive tract, while its adaptation to uterine imaging faces challenges due to the uterus's unique physiological characteristics. This paper for the first time that uses high-resolution PAE in vivo to capture a comprehensive network of endometrial microvessels non-invasively. Followed by continuous observation and quantitative analysis in the endometrial injury model, we further corroborated that PAE detection of endometrial microvessels stands as a valuable indicator for evaluating ER. The PAE system showcases its promising potential for integration into reproductive health assessments.

We report on a photoacoustic sensor system based on a differential photoacoustic cell to detect the concentration of CO impurities in hydrogen. A DFB-QCL laser with a central wavelength of 4.61 µm was employed as an exciting source with an optical power of 21 mW. Different concentrations of CO gas mixed with pure hydrogen were injected into the photoacoustic cell to test the linear response of the photoacoustic signal to the CO concentration. The stability of the long-term operation was verified by Allan-Werle deviation analysis. The minimum detection limit (MDL, SNR=1) results 8 ppb at 1 s and reaches a sub-ppb level at 100 s of integration time. Dynamic response of the system is linear and has been tested up to the concentration of 6 ppm. Saturation conditions are expected to be reached for CO concentration larger than 100 ppm.

Abstract The wide variety and ever-growing applications of plasma processes in research and industry require an equally growing diversity and accessibility of suitable plasma diagnostics. The plasma parameters and the tailoring thereof strongly influence the outcome of thin film deposition, plasma etching, or surface treatments, to name only a few. To further enhance the determination of different fluxes of species, their energies, and behaviour influencing a surface process, a custom-built combination of two commonly used diagnostics was developed. With a retarding field energy analyzer, one can obtain the ion energy distribution in a plasma by measuring the current at the collector depending on the applied voltage at the scan grid. A passive thermal probe determines the energy flux density coming from a process plasma by measuring the temperature change of a dummy substrate. In this study, we present a retarding field energy analyzer where a passive thermal probe substitutes the collector. By doing so, we can determine the energy distribution of the charged ions, their energy flux density at a certain potential, and the power deposited onto a substrate. Another advantage is that the thermal probe can even measure the power deposited by incoming (fast) neutrals and of the background gas when the grids keep away the ions. Hence, combining these two powerful diagnostics yields information neither can deliver on their own. The probe has been tested in three different plasma environments: ion beam source, magnetron sputtering and radio frequency discharge plasma.

Abstract Recently, progress in technology for accelerator-based neutron sources has increased attention regarding boron neutron capture therapy (BNCT). BNCT is a type of radiotherapy that combines neutrons and boron drugs and is expected to be used in the treatment of refractory and recurrent cancers. Owing to the need for high-intensity neutrons in treatment, compact accelerator-based neutron sources applicable to BNCT are being developed worldwide. These current projects utilize cyclotrons, linear accelerators, and electrostatic accelerators as accelerators for BNCT devices. Beryllium and lithium are the main target materials for neutron generation. The accelerators for BNCT device are required to accelerate charged particles with an average current ranging from a few milliamperes to a few tens of milliamperes in order to generate neutrons of sufficient intensity for the treatment. Moreover, the target systems require technologies and mechanisms that can withstand the large heat load produced by high-power beam irradiation and prevent blistering. This review outlines and explains the accelerator neutron sources for BNCT and the requirements for the components of each device, such as the accelerator, target material, and beam shaping assembly. In addition, various development projects for accelerator-based BNCT devices worldwide are introduced.

Abstract Flexible printed cables and circuitry based on copper-polyimide materials are widely used in experiments looking for rare events due to their unique electrical and mechanical characteristics. However, past studies have found copper-polyimide flexible cables to contain 400-4700 pg 238U/g, 16-3700 pg 232Th/g, and 170-2100 ng natK/g, which can be a significant source of radioactive background for many current and next-generation ultralow background detectors. This study presents a comprehensive investigation into the fabrication process of copper-polyimide flexible cables and the development of custom low radioactivity cables for use in rare-event physics applications. A methodical step-by-step approach was developed and informed by ultrasensitive assay to determine the radiopurity in the starting materials and identify the contaminating production steps in the cable fabrication process. Radiopure material alternatives were identified, and cleaner production processes and treatments were developed to significantly reduce the imparted contamination. Through the newly developed radiopure fabrication process, fully-functioning cables were produced with radiocontaminant concentrations of 20-31 pg 238U/g, 12-13 pg 232Th/g, and 40-550 ng natK/g, which is significantly cleaner than cables from previous work and sufficiently radiopure for current and next-generation detectors. This approach, employing witness samples to investigate each step of the fabrication process, can hopefully serve as a template for investigating radiocontaminants in other material production processes.

Background: Accurate assessment of Rheumatoid Arthritis (RA) activity remains a challenge. Multimodal photoacoustic/ultrasound (PA/US) joint imaging emerges as a novel imaging modality capable of depicting microvascularization and oxygenation levels in inflamed joints associated with RA. However, the scarcity of large-scale studies limits the exploration of correlating joint oxygenation status with disease activity. Objective: This study aimed to explore the correlation between multimodal PA/US imaging scores and RA disease activity, assessing its clinical applicability in managing RA. Methods: In this study, we recruited 111 patients diagnosed with RA and conducted examinations of seven small joints on their clinically dominant side using a PA/US imaging system. The PA and power Doppler ultrasound (PDUS) signals were semi-quantitatively assessed using a 0–3 grading system. The cumulative scores for PA and PDUS across these seven joints (PA-sum and PDUS-sum) were calculated. Relative oxygen saturation (So2) values of inflamed joints on the clinically dominant side were measured, and categorized into four distinct PA+So2 patterns. The correlation between PA/US imaging scores and disease activity indices was systematically evaluated. Results: Analysis of 777 small joints in 111 patients revealed that the PA-sum scores exhibited a strong positive correlation with standard clinical scores for RA, including DAS28 [ESR] (ρ = 0.682), DAS28 [CRP] (ρ = 0.683), CDAI (ρ = 0.738), and SDAI (ρ = 0.739), all with p < 0.001. These correlations were superior to those of the PDUS-sum scores (DAS28 [ESR] ρ = 0.559, DAS28 [CRP] ρ = 0.555, CDAI ρ = 0.575, SDAI ρ = 0.581, p < 0.001). Significantly, in patients with higher PA-sum scores, notable differences were observed in the erythrocyte sedimentation rate (ESR) (p < 0.01) and swollen joint count 28 (SJC28) (p < 0.01) between hypoxia and intermediate groups. Notably, RA patients in the hypoxia group exhibited higher clinical scores in certain clinical indices. Conclusion: Multi-modal PA/US imaging introduces potential advancements in RA assessment, especially regarding So2 evaluations in synovial tissues and associated PA scores. However, further studies are warranted, particularly with more substantial sample sizes and in multi-center settings. Summary: This study utilized multi-modal PA/US imaging to analyze Rheumatoid Arthritis (RA) patients' synovial tissues and affected joints. When juxtaposed with traditional PDUS imaging, the PA approach demonstrated enhanced sensitivity, especially concerning detecting small vessels in thickened synovium and inflamed tendon sheaths. Furthermore, correlations between the derived PA scores, PA+So2 patterns, and standard clinical RA scores were observed. These findings suggest that multi-modal PA/US imaging could be a valuable tool in the comprehensive assessment of RA, offering insights not only into disease activity but also into the oxygenation status of synovial tissues. However, as promising as these results are, further investigations, especially in larger and diverse patient populations, are imperative. Key points: ⸸ Multi-modal PA/US Imaging in RA: This novel technique was used to assess the So2 values in synovial tissues and determine PA scores of affected RA joints.⸸ Correlation significantly with Clinical RA Scores: Correlations significantly were noted between PA scores, PA+So2 patterns, and standard clinical RA metrics, hinting at the potential clinical applicability of the technique.

Strain-induced variation of the refractive index is the main mechanism of strain detection in photoacoustic experiments. However, weak strain-optic coupling in many materials limits the application of photoacoustics as an imaging tool. A straightforward deposition of a transparent thin film as a top layer has previously been shown to provide signal enhancement due to elastic boundary effects. In this paper, we study photoacoustic signal formation in metal covered by thin transparent films of different thicknesses and demonstrate that in addition to boundary effects, the photoacoustic response is affected by optical effects caused by the presence of the top layer. The interplay of optical effects leads to a complex temporal signal shape that strongly depends on the thickness of the thin film.

This study highlights the potential of scanning optoacoustic angiography (OA) in identifying alterations of superficial vasculature in patients with post-thrombotic syndrome (PTS) of the foot, a venous stress disorder associated with significant morbidity developing from long-term effects of deep venous thrombosis. The traditional angiography methods available in the clinics are not capable of reliably assessing the state of peripheral veins that provide blood outflow from the skin, a key hallmark of personalized risks of PTS formation after venous thrombosis. Our findings indicate that OA can detect an increase in blood volume, diameter, and tortuosity of superficial blood vessels. The inability to spatially separate vascular plexuses of the dermis and subcutaneous adipose tissue serves as a crucial criterion for distinguishing PTS from normal vasculature. Furthermore, our study demonstrates the ability of scanning optoacoustic angiography to detect blood filling decrease in an elevated limb position versus increase in a lowered position.

Microscopic defects in flip chips, originating from manufacturing, significantly affect performance and longevity. Post-fabrication sampling methods ensure product functionality but lack in-line defect monitoring to enhance chip yield and lifespan in real-time. This study introduces a photoacoustic remote sensing (PARS) system for in-line imaging and defect recognition during flip-chip fabrication. We first propose a real-time PARS imaging method based on continuous acquisition combined with parallel processing image reconstruction to achieve real-time imaging during the scanning of flip-chip samples, reducing reconstruction time from an average of approximately 1134 ms to 38 ms. Subsequently, we propose improved YOLOv7 with space-to-depth block (IYOLOv7-SPD), an enhanced deep learning defect recognition method, for accurate in-line recognition and localization of microscopic defects during the PARS real-time imaging process. The experimental results validate the viability of the proposed system for enhancing the lifespan and yield of flip-chip products in chip manufacturing facilities.

Psoriasis is a chronic inflammatory skin disease, characterized by thick scaly plaques. It imposes a notable disease burden with varying levels of severity affecting the quality of life significantly. Current disease severity assessment relies on semi-objective visual inspection based on the Psoriasis Area and Severity index (PASI) score that might not be sensitive to sub-clinical changes. Histology of psoriasis skin lesions necessitate invasive skin biopsies. This indicates an unmet need for a non-invasive, objective and quantitative approach to assess disease severity serially. Herein, we employ multispectral Raster-Scanning Optoacoustic Mesoscopy (ms-RSOM) derived structural and microvascular functional imaging metrics to examine the lesional and non-lesional skin in psoriasis subjects across different severities and also evaluate the treatment outcome in a subject with topical steroids and biologics, such as adalimumab. ms-RSOM derived structural metrics like epidermal thickness and total blood volume (TBV) and microvascular functional information such as oxygen saturation (sO2) are evaluated by spectrally resolving the endogenous chromophores like melanin, oxy-, and deoxy-hemoglobin. Initial findings reveal an elevated sO2 and TBV with severity in lesional and non-lesional psoriasis skin, thus representing increasing inflammation. An increase in epidermal thickness is also noted with the degree of severity, corresponding to the inflammation and increased abnormal cell growth. As a marker to evaluate the treatment response, we observed a decrease in epidermal thickness, sO2, and TBV in a psoriasis patient post-treatment, which is consistent with the decrease in the PASI score from 4.1 to 1.9. We envision that ms-RSOM has a huge potential to be translated into routine clinical setting for the diagnosis of severity and assessment of treatment monitoring in psoriasis subjects.

Traditional methods under sparse view for reconstruction of photoacoustic tomography (PAT) often result in significant artifacts. Here, a novel image to image transformation method based on unsupervised learning artifact disentanglement network (ADN), named PAT-ADN, was proposed to address the issue. This network is equipped with specialized encoders and decoders that are responsible for encoding and decoding the artifacts and content components of unpaired images, respectively. The performance of the proposed PAT-ADN was evaluated using circular phantom data and the animal in vivo experimental data. The results demonstrate that PAT-ADN exhibits excellent performance in effectively removing artifacts. In particular, under extremely sparse view (e.g., 16 projections), structural similarity index and peak signal-to-noise ratio are improved by ∼188 % and ∼85 % in in vivo experimental data using the proposed method compared to traditional reconstruction methods. PAT-ADN improves the imaging performance of PAT, opening up possibilities for its application in multiple domains.

A miniaturized photoacoustic spectroscopy-based gas sensor is proposed for the purpose of detecting sub-ppm-level carbonyl sulfide (OCS) using a tunable mid-infrared interband cascade laser (ICL) and a Helmholtz photoacoustic cell. The tuning characteristics of the tunable ICL with a center wavelength of 4823.3 nm were investigated to achieve the optimal driving parameters. A Helmholtz photoacoustic cell with a volume of ∼2.45 mL was designed and optimized to miniaturize the measurement system. By optimizing the modulation parameters and signal processing, the system was verified to have a good linear response to OCS concentration. With a lock-in amplifier integration time of 10 s, the 1σ noise standard deviation in differential mode was 0.84 mV and a minimum detection limit (MDL) of 409.2 ppbV was achieved at atmospheric pressure and room temperature.

Photoacoustic microscopy (PAM) has gained increasing popularity in biomedical imaging, providing new opportunities for tissue monitoring and characterization. With the development of deep learning techniques, convolutional neural networks have been used for PAM image resolution enhancement and denoising. However, there exist several inherent challenges for this approach. This work presents a Unified PhotoAcoustic Microscopy image reconstruction Network (UPAMNet) for both PAM image super-resolution and denoising. The proposed method takes advantage of deep image priors by incorporating three effective attention-based modules and a mixed training constraint at both pixel and perception levels. The generalization ability of the model is evaluated in details and experimental results on different PAM datasets demonstrate the superior performance of the method. Experimental results show improvements of 0.59 dB and 1.37 dB, respectively, for 1/4 and 1/16 sparse image reconstruction, and 3.9 dB for image denoising in peak signal-to-noise ratio.

We present a technique called photoacoustic vector-flow (PAVF) to quantify the speed and direction of flowing optical absorbers at each pixel from acoustic-resolution PA images. By varying the receiving angle at each pixel in post-processing, we obtain multiple estimates of the phase difference between consecutive frames. These are used to solve the overdetermined photoacoustic Doppler equation with a least-squares approach to estimate a velocity vector at each pixel. This technique is tested in bench-top experiments and compared to simultaneous pulse-echo ultrasound vector-flow (USVF) on whole rat blood at speeds on the order of 1 mm/s. Unlike USVF, PAVF can detect flow without stationary clutter filtering in this experiment, although the velocity estimates are highly underestimated. When applying spatio-temporal singular value decomposition clutter filtering, the flow speed can be accurately estimated with an error of 16.8% for USVF and −8.9% for PAVF for an average flow speed of 2.5 mm/s.

In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) – providing clinically relevant information about the human health. This is achieved via the development of a CO2-triggered breath sampling system, which collected alveolar breath over several minutes in sterile and inert containers. A real-time mass spectrometer is coupled to serve as a reference device for calibration measurements and subsequent breath analysis. The new sensor system provided a 3σ detection limit of 8.3 ppbV and an NNEA of 1.4E-9 Wcm−1Hz−0.5. In terms of the performed breath analysis measurements, 12 out of 13 fell within the error margin of the photoacoustic measurement system, demonstrating the reliability of the measurements in the field.

Dual-comb photoacoustic spectroscopy (DC-PAS) advances spectral measurements by offering high-sensitivity and compact size in a wavelength-independent manner. Here, we present a novel cantilever-enhanced DC-PAS scheme, employing a high-sensitivity fiber-optic acoustic sensor based on an optical cantilever and a non-resonant photoacoustic cell (PAC) featuring a flat-response characteristic. The dual comb is down-converted to the audio frequency range, and the resulting multiheterodyne sound waves from the photoacoustic effect, are mapped into the response frequency region of the optical cantilever microphone. This cantilever-enhanced DC-PAS method provides advantages such as high sensitivity, compact design, and immunity to electromagnetic interference. Through 10 seconds averaging time, the proposed approach experimentally achieved a minimum detection limit of 860 ppb for acetylene. This technology presents outstanding opportunities for highly sensitive detection of trace gases in a wavelength-independent manner, all within a compact volume.

The unique advantage of optical-resolution photoacoustic microscopy (OR-PAM) is its ability to achieve high-resolution microvascular imaging without exogenous agents. This ability has excellent potential in the study of tissue microcirculation. However, tracing and monitoring microvascular morphology and hemodynamics in tissues is challenging because the segmentation of microvascular in OR-PAM images is complex due to the high density, structure complexity, and low contrast of vascular structures. Various microvasculature extraction techniques have been developed over the years but have many limitations: they cannot consider both thick and thin blood vessel segmentation simultaneously, they cannot address incompleteness and discontinuity in microvasculature, there is a lack of open-access datasets for DL-based algorithms. We have developed a novel segmentation approach to extract vascularity in OR-PAM images using a deep learning network incorporating a weak signal attention mechanism and multi-scale perception (WSA-MP-Net) model. The proposed WSA network focuses on weak and tiny vessels, while the MP module extracts features from different vessel sizes. In addition, Hessian-matrix enhancement is incorporated into the pre-and post-processing of the input and output data of the network to enhance vessel continuity. We constructed normal vessel (NV-ORPAM, 660 data pairs) and tumor vessel (TV-ORPAM, 1168 data pairs) datasets to verify the performance of the proposed method. We developed a semi-automatic annotation algorithm to obtain the ground truth for our network optimization. We applied our optimized model successfully to monitor glioma angiogenesis in mouse brains, thus demonstrating the feasibility and excellent generalization ability of our model. Compared to previous works, our proposed WSA-MP-Net extracts a significant number of microvascular while maintaining vessel continuity and signal fidelity. In quantitative analysis, the indicator values of our method improved by about 1.3% to 25.9%. We believe our proposed approach provides a promising way to extract a complete and continuous microvascular network of OR-PAM and enables its use in many microvascular-related biological studies and medical diagnoses.

Photoacoustic tomography (PAT) is a promising imaging technique that can visualize the distribution of chromophores within biological tissue. However, the accuracy of PAT imaging is compromised by light fluence (LF), which hinders the quantification of light absorbers. Currently, model-based iterative methods are used for LF correction, but they require extensive computational resources due to repeated LF estimation based on differential light transport models. To improve LF correction efficiency, we propose to use Fourier neural operator (FNO), a neural network specially designed for estimating partial differential equations, to learn the forward projection of light transport in PAT. Trained using paired finite-element-based LF simulation data, our FNO model replaces the traditional computational heavy LF estimator during iterative correction, such that the correction procedure is considerably accelerated. Simulation and experimental results demonstrate that our method achieves comparable LF correction quality to traditional iterative methods while reducing the correction time by over 30 times.

Introduction: In this study, we utilized the pulsed photoacoustic (PA) technique to analyze globular sedimentation in whole human blood, with a focus on distinguishing between healthy individuals and those with hemolytic anemia. Methods: Blood samples were collected from both healthy individuals (women and men) and those with hemolytic anemia, and temporal and spectral parameters of PA signals were employed for analysis. Results: Significant differences (p < 0.05) were observed in PA metrics between the two groups. The proposed spectral analysis allowed significant differentiation within a 25-minute measurement window. Anemic blood samples exhibited higher erythrocyte sedimentation rate (ESR) values, indicating increased erythrocyte aggregation. Discussion: This study underscores the potential of PA signal analysis in ESR assessment as an efficient method for distinguishing between healthy and anemic blood, surpassing traditional approaches. It represents a promising contribution to the development of precise and sensitive techniques for analyzing human blood samples in clinical settings.

Photoacoustic imaging creates light-induced ultrasonic signals to provide valuable information on internal body structures and tissue morphology non-invasively. A multi-aperture photoacoustic imaging (MP-PAI) system is an improvement over conventional photoacoustic imaging (PAI) systems in terms of resolution, contrast, and field of view. Previously, a prototype MP-PAI system was introduced based on multiple capacitive micromachined ultrasound transducers (CMUTs) with shared channels, such that each element in a CMUT shares its channel with its counterpart in other CMUTs. The system uses the biasing voltages of the CMUTs to switch between them and multiplex the received signals in time. Notwithstanding all the enhancements, the signal-to-noise ratio (SNR) remains limited in PAI. To address this issue, we are proposing a multi-aperture encoding scheme (MAES) to further increase the SNR in a multi-aperture PAI system. The proposed method involves receiving signals with multiple CMUTs simultaneously based on an encoding matrix, instead of switching between individual CMUTs. As a result, shared channels contain a superposition of signals, which are later recovered by applying a decoding matrix. Here, an analytical model for computing SNR with an arbitrary encoding sequence is presented, and the method is validated through numerical simulations and in an experimental study. Bipolar and unipolar encoding sequences were considered for the experiments. The numerical results show, in comparison to conventional MP-PAI, that MAES will obtain an SNR gain of 5.8 and 8.8 dB for S-sequence and truncated Hadamard encodings, respectively, when using 15 transducers. In experiments, three transducers are encoded by S-sequences and show 1.5 dB improvement in SNR over conventional MP-PAI method, which aligns well with the analytical model.

Real-time applications in three-dimensional photoacoustic tomography from planar sensors rely on fast reconstruction algorithms that assume the speed of sound (SoS) in the tissue is homogeneous. Moreover, the reconstruction quality depends on the correct choice for the constant SoS. In this study, we discuss the possibility of ameliorating the problem of unknown or heterogeneous SoS distributions by using learned reconstruction methods. This can be done by modelling the uncertainties in the training data. In addition, a correction term can be included in the learned reconstruction method. We investigate the influence of both and while a learned correction component can improve reconstruction quality further, we show that a careful choice of uncertainties in the training data is the primary factor to overcome unknown SoS. We support our findings with simulated and in vivo measurements in 3D.

This paper reports a mini-resonant photoacoustic sensor for high-sensitivity trace gas sensing. The sensor primarily contains a sphere-cylinder coupled acoustic resonator, a cylindrical buffer chamber, and a fiber-optic acoustic sensor. The acoustic field distributions of this mini-resonant photoacoustic sensor and the conventional T-type resonant photoacoustic sensor have been carefully evaluated, showing that the first-order resonance frequency of the present mini-resonant photoacoustic sensor is reduced by nearly a half compared to that of the T-type resonant photoacoustic sensor. The volume of the developed photoacoustic cavity is only about 0.8 cm3. Trace methane is selected as the target analytical gas and a detection limit of 101 parts-per-billion at 100-s integration time has been achieved, corresponding to a normalized noise equivalent absorption (NNEA) coefficient of 1.04 × 10−8 W·cm−1·Hz−1/2. The developed mini-resonant photoacoustic sensor provides potential for high-sensitivity trace gas sensing in narrow spaces.

The X-ray free-electron laser (XFEL) has remarkably advanced X-ray imaging technology and enabled important scientific achievements. The XFEL’s extremely high power, short pulse width, low emittance, and high coherence make possible such diverse imaging techniques as absorption/emission spectroscopy, diffraction imaging, and scattering imaging. Here, we demonstrate a novel XFEL-based imaging modality that uses the X-ray induced acoustic (XA) effect, which we call X-ray free-electron laser induced acoustic microscopy (XFELAM). Initially, we verified the XA effect by detecting XA signals from various materials, then we validated the experimental results with simulation outcomes. Next, in resolution experiments, we successfully imaged a patterned tungsten target with drilled various-sized circles at a spatial resolution of 7.8 ± 5.1 µm, which is the first micron-scale resolution achieved by XA imaging. Our results suggest that the novel XFELAM can expand the usability of XFEL in various areas of fundamental scientific research.

A high sensitivity and ultra-low concentration range photoacoustic spectroscopy (PAS) gas detection system, which was based on a novel trapezoid compound ellipsoid resonant photoacoustic cell (TCER-PAC) and partial least square (PLS), was proposed to detect acetylene (C2H2) gas. In the concentration range of 0.5 ppm ∼ 10.0 ppm, the limit of detection (LOD) values of TCER-PAC-based PAS system without data processing was 66.4 ppb, which was lower than that of the traditional trapezoid compound cylindrical resonant photoacoustic cell (TCCR-PAC). The experimental results indicated that the TCER-PAC had higher sensitivity than of TCCR-PAC. Within the concentration range of 12.5 ppb ∼ 125.0 ppb, the LOD and limit of quantification (LOQ) of TCER-PAC-based PAS system combined with PLS regression algorithm were 1.1 ppb and 3.7 ppb, respectively. The results showed that higher detection sensitivity and lower LOD were obtained by PAS system with TCER-PAC and PLS than that of TCCR-PAC-based PAS system.

Optoacoustic (photoacoustic) mesoscopy bridges the gap between optoacoustic microscopy and macroscopy and enables high-resolution visualization deeper than optical microscopy. Nevertheless, as images may be affected by motion and noise, it is critical to develop methodologies that offer standardization and quality control to ensure that high-quality datasets are reproducibly obtained from patient scans. Such development is particularly important for ensuring reliability in applying machine learning methods or for reliably measuring disease biomarkers. We propose herein a quality control scheme to assess the quality of data collected. A reference scan of a suture phantom is performed to characterize the system noise level before each raster-scan optoacoustic mesoscopy (RSOM) measurement. Using the recorded RSOM data, we develop a method that estimates the amount of motion in the raw data. These motion metrics are employed to classify the quality of raw data collected and derive a quality assessment index (QASIN) for each raw measurement. Using simulations, we propose a selection criterion of images with sufficient QASIN, leading to the compilation of RSOM datasets with consistent quality. Using 160 RSOM measurements from healthy volunteers, we show that RSOM images that were selected using QASIN were of higher quality and fidelity compared to non-selected images. We discuss how this quality control scheme can enable the standardization of RSOM images for clinical and biomedical applications.

In this paper, we present a novel on-demand modular robotic photoacoustic tomography (PAT) probe integrated into an endoscopic device, potentially for deep intragastric sensing. The proposed solution offers a plug-and-play approach through the use of meso-scale steerable endoscopy and a new ‘snap-on’ 3D robotic PAT probe that can reconfigure the geometry of the intracorporeal light delivery, inspired by an umbrella structure. Specifically, using the limited esophageal access, steerable endoscopy allows navigation and advancement of a distally mounted robotic add-on for PAT that is folded until it reaches the deep-seated gastric lesion. Once the tip is positioned near the lesion site in the gastric cavity, there is ample working space for the robotic probe to adjust its umbrella-like unfolded shape. This allows fine-tuning of the laser delivery orientation of the fiber bundles to achieve the lesion-specific light delivery scheme. This design allows volumetric imaging of the intragastric PAT with enhanced sensitivity. To evaluate the performance of the modular robotic PAT probe, we performed a simulation analysis of the light intensity and ultrasound field distribution. The simulation results show that the robotic probe is feasible for intracorporeal PAT imaging. In addition, we printed a 3D model of a human stomach containing a simulated gastric tumour. Both the phantom and ex vivo experimental results validate the feasibility of the proposed robotic PAT probe.

Folded-optics-based quartz-enhanced photoacoustic and photothermal hybrid spectroscopy (FO-QEPA-PTS) is reported for the first time. In FO-QEPA-PTS, the detection of the photoacoustic and photothermal hybrid signal is achieved through the use of a custom quartz tuning fork (QTF), thereby mitigating the issue of resonant frequency mismatch typically encountered in quartz-enhanced photoacoustic-photothermal spectroscopy employing multiple QTFs. A multi-laser beam, created by a multi-pass cell (MPC) with a designed single-line spot pattern, partially strikes the inner edge of the QTF and partially passes through the prong of the QTF, thereby generating photoacoustic and photothermal hybrid signals. To assess the performance of FO-QEPA-PTS, 1 % acetylene is selected as the analyte gas and the 2f signals produced by the photoacoustic, the photothermal, and their hybrid effects are measured. Comparative analysis against QEPAS and QEPTS reveals signal gain factors of ∼ 79 and ∼ 14, respectively, when these laser beams created by MPC excite the QTF operating at fundamental resonance mode in phase. In the FO-QEPA-PTS signal, the proportions of the photoacoustic and the photothermal effects induced by the multiple beams are ∼7 % and 93 %, respectively.

In this work, we report on the novel employment of lithium niobate tuning forks as acoustic transducers in photoacoustic spectroscopy for gas sensing. The lithium niobate tuning fork (LiNTF) exhibits a fundamental resonance frequency of 39196.6 Hz and a quality factor Q = 5900 at atmospheric pressure. The possibility to operate the LiNTF as a photoacoustic wave detector was demonstrated targeting a water vapor absorption line falling at 7181.14 cm−1 (1.39 µm). A noise equivalent concentration of 2 ppm was reached with a signal integration time of 20 s. These preliminary results open the path towards integrated photonic devices for gas sensing with LiNTF-based detectors on lithium niobate platforms.

Peripheral arterial disease (PAD) leads to chronic vascular occlusion and results in end organ damage in critically perfused limbs. There are currently no clinical methods available to determine the muscular damage induced by chronic mal-perfusion. This monocentric prospective cross-sectional study investigated n = 193 adults, healthy to severe PAD, in order to quantify the degree of calf muscle degeneration caused by PAD using a non-invasive hybrid ultrasound and single wavelength optoacoustic imaging (US/SWL-OAI) approach. While US provides morphologic information, SWL-OAI visualizes the absorption of pulsed laser light and the resulting sound waves from molecules undergoing thermoelastic expansion. US/SWL-OAI was compared to multispectral data, clinical disease severity, angiographic findings, phantom experiments, and histological examinations from calf muscle biopsies. We were able to show that synergistic use of US/SWL-OAI is most likely to map clinical degeneration of the muscle and progressive PAD.

Multispectral optoacoustic tomography (MSOT) allows non-invasive molecular disease activity assessment in adults with inflammatory bowel disease (IBD). In this prospective pilot-study, we investigated, whether increased levels of MSOT haemoglobin parameters corresponded to inflammatory activity in paediatric IBD patients, too. 23 children with suspected IBD underwent MSOT of the terminal ileum and sigmoid colon with standard validation (e.g. endoscopy). In Crohn`s disease (CD) and ulcerative colitis (UC) patients with endoscopically confirmed disease activity, MSOT total haemoglobin (HbT) signals were increased in the terminal ileum of CD (72.1 ± 13.0 a.u. vs. 32.9 ± 15.4 a.u., p = 0.0049) and in the sigmoid colon of UC patients (62.9 ± 13.8 a.u. vs. 35.1 ± 16.3 a.u., p = 0.0311) as compared to controls, respectively. Furthermore, MSOT haemoglobin parameters correlated well with standard disease activity assessment (e.g. SES-CD and MSOT HbT (rs =0.69, p = 0.0075). Summarizing, MSOT is a novel technology for non-invasive molecular disease activity assessment in paediatric patients with inflammatory bowel disease.

Accurate needle guidance is crucial for safe and effective clinical diagnosis and treatment procedures. Conventional ultrasound (US)-guided needle insertion often encounters challenges in consistency and precisely visualizing the needle, necessitating the development of reliable methods to track the needle. As a powerful tool in image processing, deep learning has shown promise for enhancing needle visibility in US images, although its dependence on manual annotation or simulated data as ground truth can lead to potential bias or difficulties in generalizing to real US images. Photoacoustic (PA) imaging has demonstrated its capability for high-contrast needle visualization. In this study, we explore the potential of PA imaging as a reliable ground truth for deep learning network training without the need for expert annotation. Our network (UIU-Net), trained on ex vivo tissue image datasets, has shown remarkable precision in localizing needles within US images. The evaluation of needle segmentation performance extends across previously unseen ex vivo data and in vivo human data (collected from an open-source data repository). Specifically, for human data, the Modified Hausdorff Distance (MHD) value stands at approximately 3.73, and the targeting error value is around 2.03, indicating the strong similarity and small needle orientation deviation between the predicted needle and actual needle location. A key advantage of our method is its applicability beyond US images captured from specific imaging systems, extending to images from other US imaging systems.

An all-optical non-resonant photoacoustic spectroscopy system for multicomponent gas detection based on a silicon cantilever optical microphone (SCOM) and an aseismic photoacoustic cell is proposed and demonstrated. The SCOM has a high sensitivity of over 96.25 rad/Pa with sensitivity fluctuation less than ± 1.56 dB between 5 Hz and 250 Hz. Besides, the minimal detectable pressure (MDP) of the sensor is 0.55 μPa·Hz−1/2 at 200 Hz, which indicates that the fabricated sensor has high sensitivity and low noise level. Six different gases of CO2, CO, CH4, C2H6, C2H4, C2H2 are detected at the frequency of 10 Hz, whose detection limits (3σ) are 62.66 ppb, 929.11 ppb, 1494.97 ppb, 212.94 ppb, 1153.36 ppb and 417.61 ppb, respectively. The system achieves high sensitivity and low detection limits for trace gas detection. In addition, the system exhibits seismic performance with suppressing vibration noise by 4.5 times, and achieves long-term stable operation. The proposed non-resonant all-optical PAS multi-component gas detection system exhibits the advantages of anti-vibration performance, low gas consumption and long term stability, which provides a solution for working in complex environments with inherently safe.

By means of an ultrafast optical technique, picosecond acoustic strain pulses in a transparent medium are tomographically visualized at GHz frequencies. The strain distribution in BK7 glass is reconstructed from time-domain reflectivity changes of 415-nm probe light as a function of the optical incidence angle with 1 ps temporal and 120 nm spatial resolutions, enabled by automated angle scanning. The latter resolution is achieved owing to the commensurate acoustic wavelength. Applications include imaging strain, carrier and temperature distributions on ultrashort timescales.

Three-dimensional (3D) photoacoustic imaging (PAI) can provide rich information content and has gained increasingly more attention in various biomedical applications. However, current 3D PAI methods either involves pointwise scanning of the 3D volume using a single-element transducer, which can be time-consuming, or requires an array of transducers, which is known to be complex and expensive. By utilizing a 3D encoder and compressed sensing techniques, we develop a new imaging modality that is capable of single-shot 3D PAI using a single-element transducer. The proposed method is validated with phantom study, which demonstrates single-shot 3D imaging of different objects and 3D tracking of a moving object. After one-time calibration, while the system could perform single-shot 3D imaging for different objects, the calibration could remain effective over 7 days, which is highly beneficial for practical translation. Overall, the experimental results showcase the potential of this technique for both scientific research and clinical applications.

Combining the diffusive laser excitation and the photoacoustic signals detection, photoacoustic computed tomography (PACT) is uniquely suited for deep tissue imaging. A diffraction-limited ultrasound point detector is highly desirable for maximizing the spatial resolution and the field-of-view of the reconstructed volumetric images. Among all the available ultrasound detectors, micro-ring resonator (MRR) based ultrasound detectors offer the lowest area-normalized limit of detection (nLOD) in a miniature form-factor, making it an ideal candidate as an ultrasound point detector. However, despite their wide adoption for photoacoustic imaging, the underlying signal transduction process has not been systematically studied yet. Here we report a comprehensive theoretical model capturing the transduction of incident acoustic signals into digital data, and the associated noise propagation process, using experimentally calibrated key process parameters. The theoretical model quantifies the signal-to-noise ratio (SNR) and the nLOD under the influence of the key process variables, including the quality factor (Q-factor) of the MRR and the driving wavelength. While asserting the need for higher Q-factors, the theoretical model further quantifies the optimal driving wavelength for optimizing the nLOD. Given the MRR with a Q-factor of 1 × 105, the theoretical model predicts an optimal SNR of 30.1 dB and a corresponding nLOD of 3.75 × 10−2 mPa mm2/Hz1/2, which are in good agreement with the experimental measurements of 31.0 dB and 3.39 × 10−2 mPa mm2/Hz1/2, respectively. The reported theoretical model can be used in guiding the optimization of MRR-based ultrasonic detectors and PA experimental conditions, in attaining higher imaging resolution and contrast. The optimized operating condition has been further validated by performing PACT imaging of a human hair phantom.

We introduce a spectral analysis method in picosecond ultrasonics to derive strain pulse shapes in an opaque sample with known optical properties. The method makes use of both the amplitude and phase of optical transient relative reflectance changes obtained, for example, by interferometry. We demonstrate this method through numerical simulation and by analysis of experimental results for a chromium film.