Power Source Research Articles

Comparative Study of Power Tiller Operated Machines for Small Holders Farming in Conservation Agriculture

Timeliness is very crucial in all farm operations in general and in seeding and planting in particular. Slightly delay in sowing operation may lead to tremendous loss in production, productivity and sometimes quality of the grains followed by plant health. Power tiller operated machineries play very vital role for small scale farming system as the average holding size is close to one hectare and more than 86% of India’s farming community are small and marginal farmers. Practice of conservation agriculture with natural resource management has made the use of power tiller or hand tractors very essential for small holders farming. The power tiller with matching implements is cost effective source of farm power and it also enables farmers to diversify cropping pattern and increase in yield of crops. Present efforts were carried out to study the performance of various types of power tiller operated machines for different farm operations in conservation agriculture starting from seedbed preparation to crop harvesting for various crops like wheat, paddy, maize, gram, soybean, pigeon pea, sunflower, groundnut etc. Comparative field performance parameters such as field capacity, field efficiency, operating cost etc. and machine parameters have been presented in this paper.

A Comprehensive Investigation of Optoelectronic and Thermoelectric Attributes of VCu3X4 (X=S,Se,Te) Compounds for Renewable Energy Applications

Abstract Research on sustainable, environmentally friendly power sources aims to address potential energy issues caused by the decreasing availability of renewable resources. The V-series compounds are considered the most promising materials for the next generation because they are ecologically friendly. In the present work, we used First-Principle computation to investigate the structural, mechanical, optical, electronic, thermodynamic, and thermoelectric attributes of VCu₃X₄ (X=S,Se,Te) compounds using Density Functional Theory (DFT). First, we applied the PBE-GGA method to calculate the lattice constants, which were found to be 5.437 Å, 5.669 Å, and 5.954 Å for VCu₃S₄, VCu₃Se₄, and VCu₃Te₄, respectively. We thoroughly examined the binding energy to assess the structural stability of VCu₃X₄ compounds, revealing the thermodynamical stability of the uunder-study compounds. Furthermore, mechanical stability was confirmed using elastic stiffness constants, satisfying the Born-Stability criteria (C_44<0). Pugh’s and Poisson’s ratios, along with the Cauchy pressure, indicated ductile behavior in all compounds except VCu₃S₄, which exhibited brittle characteristics. The compounds demonstrate significant optical conductivity and absorption coefficients, with VCu₃Te₄ being particularly responsive to intense photon streams due to its smaller band gap of 0.57 eV, while VCu₃S₄ and VCu₃Se₄ have band gaps of 1.01 eV and 0.88 eV, respectively. We assessed the electronic properties by examining the band structure and the total and partial density of states (TDOS/PDOS), which illustrated that the under studied compounds have indirect band gaps of 1.01 eV (VCu₃S₄), 0.88 eV (VCu₃Se₄), and 0.57 eV (VCu₃Te₄). Using BoltzTraP coding, we evaluated the Seebeck coefficient, electrical and thermal conductivity, and power factor, demonstrating that VCu₃Te₄, with its small energy gap, is particularly promising for high-temperature thermoelectric and optoelectronic applications.

Visual Politics, Protest, and Power: Who Shaped the Climate Visual Discourse at COP26?

ABSTRACT Despite the importance of visual imagery for how people conceptualise issues in the news media, most research on journalism and communication prioritises textual media. This research examines the visual imagery accompanying news stories about the 2021 UN Climate Summit in Glasgow (COP26). Using a mixed-methods approach, we analyse over 1,300 images from eight UK news outlets using content and critical visual discourse analysis. We then contextualise these images, drawing on interviews and participant observation with key visual media actors including image agency photojournalists and news journalists, editors and correspondents. First, we find that the visual discourse of COP26 is limited to politicians and “talking heads” imagery, and images of protest. Second, we explore the journey that images take through the news media ecosystem, from the camera lens to the published news article, identifying the sources of power which act on visuals throughout this journey. Sources of power can be obvious (e.g., individual photographers), whilst others are obscured or misattributed (e.g., curation and editing). Overall, we empirically demonstrate the importance of understanding the networked nature of images and how they move through a complex globalised media ecosystem, rather than conceptualising them simply as static objects in the news cycle.

An innovative hybrid model combining informer and K‐Means clustering methods for invisible multisite solar power estimation

AbstractThe employment of behind‐the‐meter solar photovoltaic (PV) systems has gained increasing popularity in recent years as more individuals and organizations aim to reduce their reliance on conventional grid‐connected power sources and take advantage of the environmental and economic benefits of solar power. However, precisely estimating the potential output of PV systems is a challenging task, since most of the PV systems used in residential properties have been installed behind the meter. Consequently, electric power companies are limited to accessing only the recorded net electricity consumption. This article introduces an innovative approach to estimate behind‐the‐meter PV power generation within a large region, utilizing a limited representative subset. The proposed framework integrates Missforest, that is, a robust tool for missing data imputation, with a hybrid application of K‐Means, Pearson Correlation Coefficient, and Principal Component Analysis, for the precise selection of representative PV sites. Additionally, it leverages the Informer model, a cutting‐edge deep learning‐based time series model, to link the relationship between the PV power generation at representative sites and the total PV power output on the entire region. To conduct a case study, the power output of 367 PV sites and solar radiation measured at 105 weather stations in Taiwan were collected and analyzed. The application of this comprehensive methodology demonstrates a notable advancement in the estimation of “invisible” PV power generation in comparison to other established techniques.

Assessing Grid Reliability for Optimal Integration of System-Integrated Modular Advanced Reactor Technology (SMART) for Kenya: A Case of the Nairobi Distribution Network

The integration of advanced nuclear technologies like the System-Integrated Modular Advanced Reactor (SMART) offers a transformative approach to enhancing grid reliability in developing countries. This study focuses on the Nairobi distribution network in Kenya, a critical region characterized by an evolving energy mix of geothermal, hydro, solar, and wind power sources, comprising 220 kV and 132 kV transmission lines feeding 66 kV, 33 kV, and 11 kV distribution lines to various load centers. Using ETAP 22 simulation software, the research evaluates the impact of SMART integration through three scenarios: baseline operation, grid compensator-only operation, and SMART-SMR integration. Key reliability indices such as the System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), and Expected Energy Not Supplied (EENS) were analyzed. Results reveal that integrating a 100 MW SMART reactor reduces SAIDI by 2.8% (5.0433 h/customer-year) and SAIFI by 5.1% (0.0516 interruptions/customer-year), while maintaining voltage profiles within 98.21–98.91% of nominal. This analysis bridges gaps in prior research by demonstrating SMART’s ability to stabilize power grids in emerging economies, providing critical insights for policymakers aiming to achieve reliable and sustainable energy systems.

Development of a Methodology for Obtaining Solid Models of Products That Are Objects of Reverse Engineering Using the Example of the Capstone Micro-GTU C 65

Currently, about a thousand micro gas turbine units of small and medium capacity are in operation in the Russian Federation, which are used as an autonomous power source at critical infrastructure facilities. During long-term operation, the component parts of the micro GTU may fail and require replacement or repair. The lack of spare parts and design documentation for their production makes it impossible to operate. As a way to solve the problem, the reverse engineering process can be used to produce components. One of the stages of reverse engineering is to determine the geometric parameters of the object. The fastest and most accurate way to obtain geometric characteristics in the reverse engineering process is 3D scanning. Three-dimensional scanning technology is used to obtain a solid 3D model of the prototype surface, based on which design documentation is subsequently developed. This article presents the results of a study of the influence of the parameters of the distance between polygonal grid points and the scanner exposure on the detailing of the outer surface and the geometric parameters of the resulting polygonal model. As a result of this study, the dependence of the final file size and the time spent on scanning and processing on the distance between the points of the polygonal grid and the model was established. Based on the dependence of the parameters, recommendations were obtained for choosing the distance between the points of the polygonal grid of laser 3D scanning. Also, after performing the stages of reverse engineering, the methodology for creating solid models and design documentation of parts of power equipment units using 3D scanning technology was improved.

Porous frameworks for uranium extraction from seawater

The utilization of uranium (U) fission energy as a high-density, clean power source plays a pivotal role in mitigating greenhouse gas emissions. Uranium extraction from seawater exhibits superior environmental friendliness compared to terrestrial uranium mining, as it avoids substantial generation of radioactive waste and harmful chemicals. However, conventional adsorbents such as fiber, polymer, and biomass materials exhibit slow adsorption rates and low ion selectivity. Porous frameworks with large inner surface, full host-guest interaction, and site utilization are utilized to improve uranium absorption performance. Consequently, devising and synthesizing materials that enable efficient and cost-effective extraction of U(VI) from seawater poses a formidable challenge. Recently, there has been a considerable surge in academic interest regarding the synthesis and design of porous frameworks. By integrating experimental data, spectroscopic analysis, and theoretical calculations, we have conducted an extensive investigation into the actual performance, underlying principles, and practicality of conventional materials (such as fibers) and novel porous materials serving as adsorbents, photocatalysts, and electrocatalysts for U(VI) extraction from seawater.

State-of-the-Art and Advancement of Charging Infrastructure in Electric Mobility: An Integrated Review

Electric mobility is attracting significant attention in the current era due to its environmental benefits, sustainable transportation options, and the absence of carbon emissions. However, challenges such as the high price of batteries, inefficient charging techniques, and compatibility linking the charging station with electric vehicles (EVs) must be addressed. This article reviews advancements and identifies challenges in charging infrastructure for electric mobility. This study incorporates and analyzes an integrated review of approximately 223 research articles. Current research trends and states of charging infrastructure are prepared as per the Web of Science (WoS) database from 2013 to 2023. In light of recent extensions in wireless power transfer technology, including capacitive, inductive, and magnetic gear topology, are presented to advance the charging infrastructure. Different charging tactics based on power source, such as level-1 AC, level-2 AC, level-3 DC fast, and level-3 DC ultra-rapid charging, related to charging infrastructure are addressed. The vehicle-to-grid (V2G) integration methodology is addressed to construct a smart city by presenting the transfer of power and related data through linkage and moving systems. The exploration of artificial intelligence, global connectivity of electric vehicles (EVs), sun-to-vehicle (S2V), and vehicle-to-everything (V2X) techniques with EVs is conducted to enhance and progress the charging infrastructure. Key barriers associated with charging infrastructure are identified.

Enhancing Recoverable Bendability of Ag2Te‐Based Thermoelectrics by Elastic Strain Manipulation

AbstractInherent rigidity of high‐performing inorganic thermoelectric materials constrains their potential applications as flexible power sources for the wearable electronics. Deformation within the elastic region ensures the reservation of a material's initial functionalities, motivating the current work to focus on the elasticity enhancement of Ag2Te thermoelectric. Ag2S‐alloying results in an observable reduction in the modulus of Ag2Te1‐xSx alloys (x ≤ 0.3), which thereby enables not only a great increase in the elastic strain but also a significant plasticization of the alloys, allowing the plastic deformability by the rolling at a temperature of ≈120 °C. Such a plastic deformation‐induced improvement in yield strength leads to a further improvement of the elastic strain up to 1.8%, corresponding to ≈200% enhancements as compared to pristine Ag2Te (≈0.6%). Eventually, the multi‐pass hot‐rolled Ag2Te0.9S0.1 film achieves a full recoverability in transport properties even after elastic bending within a tiny radius of ≈3 mm for 100 000 times and a power density as high as ≈25 W m−2 in six‐leg device. This work robustly demonstrates a universal strategy to advance the recoverable bendability of inorganic thermoelectric materials for flexible applications.

Customizable Twisted Nanofluidic Cellulose Fibers by Asymmetric Microfluidics for Self‐Powered Urine Monitoring

AbstractThe unique selective ion‐transport characteristics of nanofluids make them applicable in energy harvesting and sensing. However, developing scalable, self‐powered nanofluidic devices remains challenging due to high cost, processing complexity, and reliance on external power sources. In this work, surface‐twisted, internally aligned algae fibers (twisted fibers) are fabricated using an asymmetric flow field to regulate the assembly process of the algae cellulose nanofibers. Unlike aligned fibers from the symmetrical process, asymmetric flow‐mediated twisted fibers exhibit a significantly reduced diameter (33.6–20.4 µm), increased packing density (0.87–1.47 g cm−3), superior fractured stress (249.4–468.5 MPa), and an enhanced Herman's orientation parameter (from 0.77 to 0.89). Importantly, twisted fibers demonstrate energy‐harvesting up to 12.87 W m−2 under a 50‐fold salinity gradient and can serve as self‐powered urine monitors, effectively distinguishing infants' urination from motility behaviors and alerting urine saturation due to high ionic conductivity (7.8 mS cm−1) at dilute electrolyte concentrations. This study provides a novel design concept for a self‐powered biomass‐based nanofluidic health sensing system.

A Coaxial Triboelectric Fiber Sensor for Human Motion Recognition and Rehabilitation via Machine Learning

This work presents the fabrication of a coaxial fiber triboelectric sensor (CFTES) designed for efficient energy harvesting and gesture detection in wearable electronics. The CFTES was fabricated using a facile one-step wet-spinning approach, with PVDF-HFP/CNTs/Carbon black as the conductive electrode and PVDF-HFP/MoS2 as the triboelectric layer. The incorporation of 1T phase MoS2 into the PVDF-HFP matrix significantly improves the sensor’s output owing to its electron capture capabilities. The sensor’s performance was carefully optimized by varying the weight percentage of MoS2, the thickness of the fiber core, and the CNT ratio. The optimized CFTES, with a core thickness of 156 µm and 0.6 wt% MoS2, achieved a stable output voltage of ~8.2 V at a frequency of 4 Hz and 10 N applied force, exhibiting remarkable robustness over 3600 s. Furthermore, the CFTES effectively detects human finger gestures, with machine learning algorithms further enhancing its accuracy. This innovative sensor offers a sustainable solution for energy transformation and has promising applications in smart portable power sources and wearable electronic devices.

A New Methodology for Estimating the Potential for Photovoltaic Electricity Generation on Urban Building Rooftops for Self-Consumption Applications

As the world increasingly embraces renewable energy as a sustainable power source, accurately assessing of solar energy potential becomes paramount. Photovoltaic (PV) systems, especially those integrated into urban rooftops, offer a promising solution to address the challenges posed by aging energy grids and rising fossil fuel prices. However, optimizing the placement of PV panels on rooftops remains a complex task due to factors like building shape, location, and the surrounding environment. This study introduces the Roof-Solar-Max methodology, which aims to maximize the placement of PV panels on urban rooftops while avoiding shading and panel overlap. Leveraging geographic information systems technology and 3D models, this methodology provides precise estimates of PV generation potential. Key contributions of this research include a roof categorization model, identification of PV-ready rooftops, optimal spatial distribution of PV panels, and innovative evaluation technology. Practical implementation in a real urban setting demonstrates the methodology’s utility for decision making in the planning and development of solar energy systems in urban areas. The main findings highlight substantial potential for PV energy generation in the studied urban area, with capacities reaching up to 444.44 kW. Furthermore, implementing PV systems on residential rooftops has proven to be an effective strategy for reducing CO2 emissions and addressing climate change, contributing to a cleaner and more sustainable energy mix in urban environments.

Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System

This study introduces an advanced Mixed-Integer Linear Programming model tailored for comprehensive electrical and thermal energy management in small-scale smart grids, addressing emergency load shedding and overload situations. The model integrates combined heat and power sources, capable of simultaneous electricity and heat generation, alongside a mobile photovoltaic battery storage system, a wind resource, a thermal storage tank, and demand response programs (DRPs) for both electrical and thermal demands. Power-to-hydrogen systems are also incorporated to efficiently convert electrical energy into heat, enhancing network synergies. Utilizing the robust Gurobi solver, the model aims to minimize operating, fuel, and maintenance costs while mitigating environmental impact. Simulation results under various scenarios demonstrate the model’s superior performance. Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. This study emphasizes the advantages of employing DRP and heat tank equations to balance electrical and thermal energy relationships, reduce heat losses, and enable the integration of larger photovoltaic systems to meet thermal constraints, thus broadening the problem’s feasible solution space.

A Critical Discourse Analysis of Feminine and Masculine Identity in August Wilson’s Pittsburg Cycle

In his collection of ten plays, The Pittsburg Cycle, August Wilson (1945-2005) presents the social dynamism of African Americans across the twentieth century America. In his plays, many newly freed African slaves move to the North, hoping to shape their identity as respectable citizens of great worth. They are, however, reckoned as foreigners in a new habitus. Since they have lost contact with their past heritage and have no access to their social codes as a source of power, they search for means through which they can concretize the song they carry within themselves as a sign of their true African heritage. Through the theory of critical discourse analysis, this article focuses on Michel Foucault’s theory of discourse to study, analyze, and compare the discourse of both male and female characters of the plays. According to the age-old western tradition, male discourse represents power, assurance, and certainty in contrast to female discourse imbued with characteristics opposite to the mentioned ones. This article aims to explore how Wilson subverts the male and female discourse to create a nongendered African soul, who embodies characteristics of both sexes.

A Hybrid Parameters Estimation Approach for Power Consumption Modeling of Ground Mobile Robots With Unknown Payload

ABSTRACTTypically, batteries are the main power source for mobile robots, and the practical constraints in carrying them pose challenges in achieving efficiency, autonomy, and safety objectives in robotic missions. Moreover, dealing with battery degradation requires a precise understanding of energy consumers' behavior in the system. Therefore, establishing an energy consumption model has an important role in addressing these challenges. This study focuses on the modeling and estimation of power consumption in indoor ground mobile robots with unknown payloads. We investigate key components and parameters that influence the actuation energy consumption of ground mobile robots equipped with DC motors, particularly in the context of pure rolling without slipping. To estimate the actuation power consumption of ground mobile robots, we present a hybrid parameters estimation approach. This method includes an offline step for estimating the mass‐decoupled coefficients of a power model, followed by two online steps for estimating the robot's unknown payload and its actuation power consumption. Simulation and experimental results with a differential drive robot (Turtlebot3) validate the effectiveness of the proposed approach. Additionally, the performance of the proposed power consumption estimation method is compared with two other data‐driven models based on multivariate linear regression and multilayer perceptron neural networks. The results demonstrate that the proposed method provides improved power consumption estimation accuracy on the selected indicators compared to the others. We also emphasize the importance of balancing the accuracy of power consumption estimation with its associated costs in the context of the proposed approach. This extra cost includes the energy needed for additional data measurement and processing. Considering this trade‐off is crucial for the practical implementation and resource optimization in robotic systems.

A novel horizontal self-tuning piezoelectric energy harvester based on a beam-slider system

Abstract With the rapid development of piezoelectric energy harvesting technologies, this approach is emerging as a promising power source for smart sensors. Despite this progress, a significant challenge remains in achieving a wider bandwidth while increasing the output power. In response to this challenge, this paper introduces a horizontal self-tuning beam-slider piezoelectric energy harvester (STBS-PEH). This innovative harvester employs a unilateral beam-slider mechanism to enable self-tuning of the energy harvesting by adjusting its resonant frequency to match the external excitation frequency. The electromechanical coupled dynamic model of this harvester has been established. Comprehensive simulations and experimental analysis have been conducted to demonstrate the wide bandwidth and high output power characteristics of the proposed harvester. Notably, the simulation results exhibit strong agreement with the experimental findings. The resonance response bandwidth of the STBS-PEH is particularly noteworthy, which is twice that of a conventional cantilever beam piezoelectric energy harvester. The root mean square (RMS) voltage and output power of the developed STBS-PEH can reach 23.54 V and 194.61 µW, respectively, at a frequency of 21 Hz, with an excitation amplitude of 0.5 g. These results demonstrate that the STBS-PEH is capable of powering low-power electronic devices in a broadband vibrational environment.

Betavoltaic rechargeable Zn-ion battery based on hybrid cathode by combining betavoltaic structure with intercalation host

To address the issue of low power output of betavoltaic cells in practical applications, a 63Ni-powered betavoltaic rechargeable Zn-ion battery (BRZiB) is presented in this paper for simultaneously harvesting, converting, and storing beta-radioactive energy within one device. Experimentally, a patterned ZnO microrod array nanostructure was prepared using hydrothermal and lithography methods, in which a 63Ni beta source was deposited by chemical plating to form a 63Ni@ZnO structure for betavoltaic power generation. A carbon-coated VO2 nanocomposite (C@VO2), used as the intercalation host for Zn ions, was coated on the betavoltaic structure for fabricating the hybrid cathode of BRZiB. Without using any external power source, the 63Ni-powered BRZiB demonstrated a voltage rise of 0.3 V in 82 h, which was calculated to have an energy conversion efficiency of 5.1% and an energy density of 128 mWh/g over a half-life of 63Ni (∼100 years). The experimental results verify the effectiveness of multi-energy synergistic conversion in the electrochemical betavoltaic system.

Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm

Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group.

Characterization of tin oxide nanoparticles synthesized by discharging the non-thermal plasma jet in liquid and their application as an antibacterial agent

This study reports the synthesis of tin oxide nanoparticles using a non-thermal plasma jet technique. Spectroscopic analysis (OES) of plasma was carried out at atmospheric pressure to measure the plasma parameters used in the synthesis of nanoparticles. SnO2 NPs were synthesized at different durations (3 and 5 min) using a DC-high-voltage power source with a voltage of 13 kV.X-ray diffraction (XRD) showed that SnO2 NPs, prepared in 3 min, are rutile tetragonal polycrystalline and have an average crystallite size of 12.45 nm. Field emission scanning electron (FE-SEM) images also show that the nanoparticles are spherical and homogenous, with an average nanostructure diameter of 22 to 58 nm for both (3 and 5 min) preparation times. UV–Vis spectroscopy showed peaks of surface plasmon resonance around 255–260 nm. The ICP-mass technique was used to evaluate nanoparticle concentrations, which were between 90–100 μg/ml. Zeta potential (ZP) measurements revealed that the particles are relatively stable colloids. The study shows that synthesized nanoparticles have exceptional antibacterial efficacy against Escherichia coli and Staphylococcus aureus bacteria. These nanoparticles are low-cost, scalable, and can be synthesized using gas or liquid phases, enabling the synthesis of a wide range of nanoparticles suitable for various pathogenic bacterial types.

Bacteriology testing and antimicrobial resistance detection capacity of national tiered laboratory networks in sub-Saharan Africa: an analysis from 14 countries

Accurate detection of antimicrobial resistance (AMR) depends on adequate laboratory capacity. We aimed to document key weaknesses hindering AMR detection at various tiers of laboratory networks in 14countries in sub-Saharan Africa, and analyse their significance in AMR surveillance and policies. In this analysis, we obtained retrospective data on AMR and antimicrobial consumption from 14countries participating in the Mapping Antimicrobial Resistance and Antimicrobial Use Partnership between May 1, 2019, and June 30, 2020. We established the number, capacity for AMR detection, and other characteristics from all bacteriology laboratories within the national network from existing national health system compendiums, combined with a self-applied scored survey tool. We calculated AMR detection readiness scores at a facility and country level and analysed the pertinence of national strategies to address system gaps for AMR detection and surveillance. Of the 53 770listed laboratories, 675 (1%) were formally assigned to deliver bacterial testing and invited to complete the survey tool. Of the 504 (75%) facilities that returned the completed survey, 393 (78%) reported antimicrobial susceptibility testing (AST) capacity and collectively provided geographical access to less than 50% of the general population in seven countries. Continuous access to water was reported by 347 (88%) laboratories, power sources by 341 (87%) laboratories, and the presence of qualified laboratory scientist or technologist by 377 (96%) laboratories. By contrast, ISO15189 accreditation was reported by 90 (23%) laboratories and use of an electronic laboratory information system by 54 (13%). Reference laboratories were associated with higher AMR detection readiness scores than were district laboratories (odds ratio 4·7 [95% CI 1·3-10·2; p=0·014). Private, not-for-profit laboratories were associated with higher scores than were government-affiliated facilities (9·2 [1·6-53·8; p=0·014). Designated national AMR sentinel sites were associated with higher scores than were non-sentinel sites (5·8[2·9-11·8; p<0·001). Laboratories processing between 1001and 3000bacterial cultures annually were associated with higher scores than were those processing less than 200cultures annually (4·8 [1·7-13·7]; p=0·0040). Strengthening bacterial testing and capacity for AMR detection represented less than 20% of the proposed interventions in 12of the 14national AMR action plans. AMR action plans and other relevant national strategies should prioritise the scale-up of bacterial testing services to improve access to care and promote quality AMR surveillance. Interventions that democratise AST to lower laboratory tiers, formally designate AMR sentinel sites, and implement whole-of-network laboratory information and quality management systems are urgently needed. Fleming Fund, UK Aid, and US Centers for Disease Control and Prevention through the Training Programs in Epidemiology and Public Health Intervention Networks.