Macro-scale Systems Research Articles

A computational model for ion and electron energization during macroscale magnetic reconnection

A set of equations is developed that extends the macroscale magnetic reconnection simulation model kglobal to include particle ions. The extension from earlier versions of kglobal, which included only particle electrons, requires the inclusion of the inertia of particle ions in the fluid momentum equation. The new equations will facilitate the exploration of the simultaneous non-thermal energization of ions and electrons during magnetic reconnection in macroscale systems. Numerical tests of the propagation of Alfvén waves and the growth of firehose modes in a plasma with anisotropic electron and ion pressure are presented to benchmark the new model.

Beta-Gamma Phase-Amplitude Coupling as a Non-Invasive Biomarker for Parkinson's Disease: Insights from Electroencephalography Studies.

Phase-amplitude coupling (PAC) describes the interaction of two separate frequencies in which the lower frequency phase acts as a carrier frequency of the higher frequency amplitude. It is a means of carrying integrated streams of information between micro- and macroscale systems in the brain, allowing for coordinated activity of separate brain regions. A beta-gamma PAC increase over the sensorimotor cortex has been observed consistently in people with Parkinson's disease (PD). Its cause is attributed to neural entrainment in the basal ganglia, caused by pathological degeneration characteristic of PD. Disruptions in this phenomenon in PD patients have been observed in the resting state as well as during movement recordings and have reliably distinguished patients from healthy participants. The changes can be detected non-invasively with the electroencephalogram (EEG). They correspond to the severity of the motor symptoms and the medication status of people with PD. Furthermore, a medication-induced decrease in PAC in PD correlates with the alleviation of motor symptoms measured by assessment scales. A beta-gamma PAC increase has, therefore, been explored as a possible means of quantifying motor pathology in PD. The application of this parameter to closed-loop deep brain stimulation could serve as a self-adaptation measure of such treatment, responding to fluctuations of motor symptom severity in PD. Furthermore, phase-dependent stimulation provides a new precise method for modulating PAC increases in the cortex. This review offers a comprehensive synthesis of the current EEG-based evidence on PAC fluctuations in PD, explores the potential practical utility of this biomarker, and provides recommendations for future research.

A deep learning upscaling framework: Reactive transport and mineral precipitation in fracture-matrix systems

Pore-scale modeling has limited applicability at large scales due to its high computational cost. One common approach to upscale pore-scale models is the use of effective medium theories, which homogenize small-scale features in a porous structure and characterize the medium by macroscale properties (e.g., permeability) and equations (e.g., Darcy’s law). However, there are classes of physical processes for which effective medium approximations may become inaccurate, e.g., mineral precipitation and clogging during reactive transport. We have developed a deep learning upscaling framework, in which pore-scale modeling is directly employed in macroscale systems, without relying on effective medium approximations. The upscaling framework is first developed for general multiscale systems and then applied to modeling reactive transport with mineral precipitation in the altered layer in fracture-matrix structures. Solute transport from the fractures to the matrix is modeled as a wall boundary condition for the fractures, which, in turn, is predicted by recurrent neural networks using the concentration histories at the fracture-matrix boundary. Specifically, we consider a meter-scale fracture network embedded in sandstones, where the smallest feature is at the micron scale. The proposed framework allows us to span five orders of magnitude in length scales by capturing mineral precipitation in the altered layer of the rock matrix at the pore scale across the entire meter-scale fracture network.

Electroviscous effects in pressure-driven flow of electrolyte liquid through an asymmetrically charged non-uniform microfluidic device

BackgroundMicro-scale systems depict a different flow behavior from the macro-scale systems due to more vital surface forces such as surface tension, electrical charges, magnetic field, etc., which significantly affect the micro-scale flow. Further, among others, electrokinetic phenomena play a significant role at the micro-scale for controlling practical microfluidic applications. Therefore, it is essential to understand the fluid dynamics in micron-sized channels to develop efficient and reliable microfluidic devices. MethodsThe electroviscous effects in pressure-driven flow of electrolyte liquid through an asymmetrically charged contraction-expansion (4:1:4) slit microfluidic device have been investigated numerically. The mathematical model (i.e., Poisson's, Navier-Stokes, and Nernst-Planck equations) is solved using the finite element method to obtain the electrical potential, velocity, pressure, ion concentration fields, excess charge, an induced electric field strength for the following ranges of parameters: Reynolds number (Re=0.01), Schmidt number (Sc=1000), inverse Debye length (2≤K≤20), top wall surface charge density (4≤St≤16), surface charge density ratio (0≤Sr≤2) and contraction ratio (dc=0.25). Significant FindingsResults show that the charge asymmetry (Sr) at the different walls of the microfluidic device plays a significant role on the induced electric field development and microfluidic hydrodynamics. The total potential (|ΔU|) and pressure drop (|ΔP|) maximally increase by 197.45% and 25.46%, respectively with asymmetry of the charge. The electroviscous correction factor (ratio of apparent to physical viscosity) maximally changes by 20.85% (at K=2, St=16 for 0≤Sr≤2), 34.16% (at St=16, Sr=2 for 2≤K≤20), and 39.13% (at K=2, Sr=2 for 0≤St≤16). Thus, charge asymmetry (0≤Sr≤2) remarkably influences the fluid flow in the microfluidic devices, which is used for controlling the microfluidic processes, such as, mixing efficiency, heat, and mass transfer rates. Further, a simpler analytical model is developed to predict the pressure drop in electroviscous flow considering asymmetrically charged surface, based on the Poiseuille flow in the individual uniform sections and pressure losses due to orifice, estimates the pressure drop 1–2% within the numerical results. The robustness of this model enables the use of present numerical results for design aspects in the microfluidic applications.

Simulation and Performance Evaluation of a Bio-Inspired Nanogenerator for Medical Applications.

Providing sufficient energy for autonomous systems at the nanoscale is one of the major challenges of the Internet of Nano Things (IoNT). Existing battery technologies and conventional integrated circuits cannot be used in such small dimensions. Even if they are small enough to be used at the nano level, they still cannot be used in medical applications due to biocompatibility issues. M13 is a very promising virus with piezoelectric properties, which has attracted much interest in the scientific community as a bioenergy harvester. However, M13 studies presented so far in the literature are designed only for macroscale systems. In this paper, we simulate two designs of a bio-inspired nanogenerator based on the properties of M13 for nanosystems. We derive the stiffness matrix of M13, its dielectric and piezoelectric matrices and its density. We verify our calculated values by comparing our simulations with the results of experimental studies presented in the literature. We also evaluate the system's performance in terms of frequency response and loading characteristics. The results presented in this study show that a single M13 is a very promising nano-generator that can be used for medical applications.

The advanced wireless sensor networks’ routing protocol to detect malicious nodes and behavior

ABSTRACT This paper analyzes the trust problem in computer wireless sensor networks, WSNs. This study presents a reliable routing method in WSNs. Trust is an essential question although endeavors to prevent attacks on the networks have been made, the problem has not been satisfactorily resolved. The novelties of this paper are its improvement of the FETRP protocol in WSNs while considering recent advancements in related technologies like the Internet of Things (IoT) and its applicability in micro and macro-scale systems. Some malicious nodes deceive systems with incompatible behaviors, but this protocol detects them. This paper introduces fuzzy energy and a reliable routing protocol, FETRP, to solve problems. The protocol is upon fuzzy cluster development and has been designed to manage reliable routing of information transmission.

Mechanical stratigraphy controls fracture pattern and karst epigenic dissolution in folded Cretaceous carbonates in semiarid Brazil

Carbonate reservoirs are often affected by fractures and karst that increase rock's permeability. An accurate characterization of reservoir architecture, fracture attributes and distribution of karst features are critical to modeling carbonate reservoirs, predicting flow behavior and estimating geofluids recoveries. In this contribution, we describe a case study of epigenic karst dissolution concentrated in a fold hinge zone and controlled by stratigraphic and structural processes in Cretaceous layered carbonates in the Potiguar Basin, Brazil. The stratigraphic setting and petrographic/petrophysical properties of host rocks were defined before fracture analysis. Two main joint sets were recognized: master joints (persistent fold hinge parallel set) and cross-joints (orthogonal to fold hinge and confined within master joints). The quantitative mesoscale fracture analysis was performed on a hinge-parallel joint set in 10 field sites distributed across the fold using scanlines to determine two parameters: Fracture Spacing Ratio in individual beds and the Fracture Spacing Index of bed packages. Fracture density and intensity of cross-joints were analyzed in one site using digital scanlines and scanareas on drone images. Results indicate that (i) systematic fractures consist of strata-bound joints, mostly oriented parallel to fold hinge, (ii) fracture intensity does not depend on intrinsic petrophysical properties of individual beds, and (iii) fracture intensity increases within a ∼2.5 km-wide fold hinge zone, consistent with previous studies performed via remote sensing analysis. By integrating our new results with published data, we provide a conceptual model that considers the role of regional-scale tectonic process and local-scale mechanical stratigraphy in controlling the size, shape and distribution of epigenic karst dissolution. Our findings indicate that facture permeability anisotropy, inferred from the karst pattern, is imparted by the combination of bed's attributes (mechanical stratigraphy) and fold-related fracturing. These results are an effective tool to predict the meso- and macro-scale porosity systems in fractured and karstified hydrocarbon reservoirs.

Harnessing a paper-folding mechanism for reconfigurable DNA origami.

The paper-folding mechanism has been widely adopted in building of reconfigurable macroscale systems because of its unique capabilities and advantages in programming variable shapes and stiffness into a structure1-5. However, it has barely been exploited in the construction of molecular-level systems owing to the lack of a suitable design principle, even though various dynamic structures based on DNA self-assembly6-9 have been developed10-23. Here we propose a method to harness the paper-folding mechanism to create reconfigurable DNA origami structures. The main idea is to build a reference, planar wireframe structure24 whose edges follow a crease pattern in paper folding so that it can be folded into various target shapes. We realized several paper-like folding and unfolding patterns using DNA strand displacement25 with high yield. Orthogonal folding, repeatable folding and unfolding, folding-based microRNA detection and fluorescence signal control were demonstrated. Stimuli-responsive folding and unfolding triggered by pH or light-source change were also possible. Moreover, by employing hierarchical assembly26 we could expand the design space and complexity of the paper-folding mechanism in a highly programmable manner. Because of its high programmability and scalability, we expect that the proposed paper-folding-based reconfiguration method will advance the development of complex molecular systems.

Electron hopping heat transport in molecules.

The realization of single-molecule thermal conductance measurements has driven the need for theoretical tools to describe conduction processes that occur over atomistic length scales. In macroscale systems, the principle that is typically used to understand thermal conductivity is Fourier's law. At molecular length scales, however, deviations from Fourier's law are common in part because microscale thermal transport properties typically depend on the complex interplay between multiple heat conduction mechanisms. Here, the thermal transport properties that arise from electron transfer across a thermal gradient in a molecular conduction junction are examined theoretically. We illustrate how transport in a model junction is affected by varying the electronic structure and length of the molecular bridge in the junction as well as the strength of the coupling between the bridge and its surrounding environment. Three findings are of note: First, the transport properties can vary significantly depending on the characteristics of the molecular bridge and its environment; second, the system's thermal conductance commonly deviates from Fourier's law; and third, in properly engineered systems, the magnitude of electron hopping thermal conductance is similar to what has been measured in single-molecule devices.

The effects of propofol anaesthesia on molecular-enriched networks during resting-state and naturalistic listening

Placing a patient in a state of anaesthesia is crucial for modern surgical practice. However, the mechanisms by which anaesthetic drugs, such as propofol, impart their effects on consciousness remain poorly understood. Propofol potentiates GABAergic transmission, which purportedly has direct actions on cortex as well as indirect actions via ascending neuromodulatory systems. Functional imaging studies to date have been limited in their ability to unravel how these effects on neurotransmission impact the system-level dynamics of the brain. Here, we leveraged advances in multi-modal imaging, Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), to investigate how different levels of propofol-induced sedation alter neurotransmission-related functional connectivity (FC), both at rest and when individuals are exposed to naturalistic auditory stimulation. Propofol increased GABA-A- and noradrenaline transporter-enriched FC within occipital and somatosensory regions respectively. Additionally, during auditory stimulation, the network related to the dopamine transporter showed reduced FC within bilateral regions of temporal and mid/posterior cingulate cortices, with the right temporal cluster showing an interaction between auditory stimulation and level of consciousness. In bringing together these micro- and macro-scale systems, we provide support for both direct GABAergic and indirect noradrenergic and dopaminergic-related network changes under propofol sedation. Further, we delineate a cognition-related reconfiguration of the dopaminergic network, highlighting the utility of REACT to explore the molecular substrates of consciousness and cognition.

A robust and memory-efficient transition state search method for complex energy landscapes.

Locating transition states is crucial for investigating transition mechanisms in wide-ranging phenomena, from atomistic to macroscale systems. Existing methods, however, can struggle in problems with a large number of degrees of freedom, on-the-fly adaptive remeshing and coarse-graining, and energy landscapes that are locally flat or discontinuous. To resolve these challenges, we introduce a new double-ended method, the Binary-Image Transition State Search (BITSS). It uses just two states that converge to the transition state, resulting in a fast, flexible, and memory-efficient method. We also show that it is more robust compared to existing bracketing methods that use only two states. We demonstrate its versatility by applying BITSS to three very different classes of problems: Lennard-Jones clusters, shell buckling, and multiphase phase-field models.

Big picture transdisciplinary practice - extending key ideas of a Department of Methodology towards a wider ecological view of practitioner-scientist integration

ABSTRACT In high-performance sport, a multidisciplinary approach is proposed as essential in providing an effective environment to service all aspects of athlete development and performance. A Department of Methodology (DoM) conceptualisation, based on an ecological dynamics rationale, provides a framework for coaches, sport scientists and support practitioners to collaboratively conceptualise integrated team and athlete development practices. Previous research has highlighted several principles for holistic system development of athletes, such as importance of embracing non-linearity, prioritising athlete–environment relations, and identifying constraints on performance. While sports organisations are continuously shaped by constraints operating at multiple scales, the overarching purpose of this paper is to highlight specifically how macro-scale ecological constraints may shape integrated practice design from a transdisciplinary perspective. To achieve this aim, we expound on the DoM concept by drawing on Bronfenbrenner’s bioecological model of human development, to elaborate on how interconnected system components, simultaneously operating at multiple scales, continuously contextualise athlete development experiences. Further, we seek to sensitise coaches, scientists, and support staff to the ‘big-picture of athlete development’, discussing how sports organisations may adapt to the ubiquitous influences of macro-scale ecological systems (e.g., national associations and sport governing bodies). Finally, numerous association football (soccer) examples, and a recent case report about developments within the German FA (DFB) and youth football structure, attempt to make theoretical ideas tangible and understandable for coaching practitioners in the field.

Non-negligible effects of reinforcing structures inside ion exchange membrane on stabilization of electroconvective vortices

Concentration polarization (CP) phenomena near ion-exchange membranes have been utilized not only in micro/nanofluidic platforms but also in macro-scale systems such as electro-desalination and battery, etc. Such systems are highly demanded to have high energy efficiency and stability so that the stabilizing unstable electroconvection as a major nuisance of CP system has been widely studied. However, the methods for controlling electroconvection were mainly limited to structural modifications outside a membrane such as microstructures in a bulk and heterogeneous membrane surfaces, despite ions should flow through inside a membrane. Thus, the internal structures of the membrane may have a significant effect on ion transportation. One example of the structure is dielectric reinforcing structures that mechanically hold the membrane. Therefore, in this work, we investigate the non-negligible effect of the reinforcing structures on an electric field near the membrane for the alignment of electroconvection. The alignment was demonstrated that it depends on the geometry of the reinforcements through numerical simulations and experiments. Moreover, the stabilization of electroconvection with the reinforcements in chaotic regime was demonstrated through the visualization of ion depletion zone and electrical measurements. While the stabilization of electroconvection was validated in a micro/nanofluidic platform in this work, it is easy to expand for designing macro scale CP system due to the high scalability of micro/nanofluidic platform. Thus, the presenting results would be strongly useful for a highly energy-efficient and stable CP system.

Gigahertz topological valley Hall effect in nanoelectromechanical phononic crystals

Topological phononics offers numerous opportunities in manipulating elastic waves that can propagate in solids without being backscattered. Due to the lack of nanoscale imaging tools that aid the system design, however, acoustic topological metamaterials have been mostly demonstrated in macroscale systems operating at low (kilohertz to megahertz) frequencies. Here, we report the realization of gigahertz topological valley Hall effect in nanoelectromechanical AlN membranes. Propagation of elastic wave through phononic crystals is directly visualized by microwave microscopy with unprecedented sensitivity and spatial resolution. The valley Hall edge states, protected by band topology, are vividly seen in both real- and momentum-space. The robust valley-polarized transport is evident from the wave transmission across local disorder and around sharp corners, as well as the power distribution into multiple edge channels. Our work paves the way to exploit topological physics in integrated acousto-electronic systems for classical and quantum information processing in the microwave regime.

Mission net-zero America: The nation-building path to a prosperous, net-zero emissions economy

Jesse D. Jenkins is an assistant professor at Princeton University in the department of mechanical and aerospace engineering and the Andlinger Center for Energy and the Environment. He is a macro-scale energy systems engineer with a focus on the rapidly evolving electricity sector and leads the Princeton ZERO Lab, which focuses on improving and applying optimization-based energy systems models to evaluate low-carbon energy technologies and generate insights to guide policy and planning decisions. Jesse earned a PhD and SM from the Massachusetts Institute of Technology and was previously a postdoctoral environmental fellow at Harvard University. Erin N. Mayfield is an assistant professor at the Thayer School of Engineering at Dartmouth College focusing her research on sustainable-systems engineering and public policy. She develops and applies multi-objective computational models that integrate techno-economic, environmental, and social equity objectives to inform energy and industrial infrastructure transitions. Prior to her academic research career, her work with other organizations included regulatory assessments of environmental rule-makings, hazardous waste remediation in environmental justice communities, and ecosystem services valuation related to petrochemical and pesticide contamination. Erin has a PhD in engineering and public policy from Carnegie Mellon University and was previously a postdoctoral scholar at Princeton University. Eric Larson is a senior research engineer at Princeton University leading the Energy Systems Analysis Group in the Andlinger Center for Energy and the Environment. He holds courtesy appointments with the High Meadows Environmental Institute and the Center for Policy Research on Energy and the Environment in the School of Public and International Affairs. His research, intersecting engineering, environmental science, economics, and public policy, aims to identify sustainable, engineering-based solutions to major energy-related problems and to help inform public and private decision-making in the U.S. and elsewhere. Eric has a PhD in mechanical engineering from the University of Minnesota. Stephen Pacala is the Frederick D. Petrie professor in ecology and evolutionary biology at Princeton University and director of the Princeton Carbon Mitigation Initiative. His research interests are in the design and testing of mathematical models to investigate interactions between greenhouse gases, climate, and the biosphere and to predict their effects on local and global ecosystems. He is a member of the U.S. National Academy of Sciences, the American Association for the Advancement of Science, and the American Academy of Arts and Sciences. Steve has a PhD in biology from Stanford University. Chris Greig is the Theodora D. and William H. Walton III senior research scientist in the Andlinger Center for Energy and the Environment at Princeton University. His research interests lie in energy transitions, economics, and policy; capital project investment decision-making and implementation; and carbon capture, utilization, and storage. Chris has a PhD in chemical engineering from the University of Queensland and is a fellow of the Australian Academy of Technology and Engineering. His academic career was preceded by 25 years in senior project and executive roles in the resources and energy sectors.

Insights into scale translation of methane transport in nanopores

Accurate prediction of flow behavior in shale matrix is critical for efficient development of shale gas reservoirs. In these systems, the majority of pores are in the nano-size range. As a result, continuum-based approaches may not be appropriate to simulate flow in such systems. Molecular dynamics (MD) simulations are capable of capturing the relevant microscale physics. Their relatively high computational expense, however, restricts MD simulations to rather small systems and domains. This limitation creates a gap between computational need of macroscale systems and capabilities of MD simulations. The lattice Boltzmann method (LBM) is a suitable candidate to bridge this gap. In this work, the multiple-relaxation-time (MRT)-LBM is used to study methane transport in nano-size pores. Adsorption effects near solid boundaries, as well as non-ideal behavior of fluids, are accounted for via incorporating appropriate force terms in LBM. Parameters associated with the force terms in the equation of state are studied in detail, and a workflow is proposed to determine optimal values of these parameters for gas flow in slit pores. Specifically, we establish these parameters such that the range of density values that the model is able to simulate is maximized. We demonstrate this workflow by simulating gas flow where velocity and density profiles from MD simulations are used as reference data. Results from LBM simulations are in good agreement with MD reference data for pores that are 4 nm in width or larger. Moreover, we propose a preconditioning scheme to improve the stability of LBM in dealing with complex geometries. The robustness of this scheme is demonstrated by simulating several roughness geometries. This work motivates the use of LBM in scale translation of the physics of mass transport in more complex permeable media.

Long-duration energy storage: A blueprint for research and innovation

Jesse D. Jenkins is an assistant professor at Princeton University in the department of mechanical and aerospace engineering and the Andlinger Center for Energy and the Environment. He is a macro-scale energy systems engineer with a focus on the rapidly evolving electricity sector and leads the Princeton ZERO Lab, which focuses on improving and applying optimization-based energy systems models to evaluate low-carbon energy technologies and generate insights to guide policy and planning decisions. Jesse earned a PhD and SM from the Massachusetts Institute of Technology and was previously a postdoctoral environmental fellow at Harvard University. Nestor A. Sepulveda is a management consultant working in corporate strategy, technology development, decarbonization, sustainable investing, and advanced analytics. Nestor earned a PhD from the Massachusetts Institute of Technology developing methodologies that combine operations research and analytics to guide the energy transition and cleantech development. He received a SM in technology and policy working on energy policy and economics and a SM in nuclear science and engineering, both from MIT. Nestor is a former Naval Officer who served for more than 10 years in the Chilean Navy.

Centralization under decentralization: The development of fishery clubs in Lesvos under the administrative reforms of Greece

Decentralization and local participatory arrangement are essential for successful fisheries governance. In EU member states, the persistent gap between macro-scale management systems and diverse conditions of local small-scale fisheries obscures the actual attributes and contexts of local fishing communities. This study empirically showcases a parallel process in Lesvos, Greece, whereby administrative decentralization at a higher level in the 2010′s accompanied the centralization and further restructuring of fisheries governance at a lower level. Semi-structured interviews were conducted in 18 villages supplemented by spatial analysis of the demographic trends and an audit of the official records. In contrast to the socially rooted population concentration, local fishers and their villages in Lesvos are dispersed across the island, isolated from one another. Under such disparity, local fishers had formed fishery clubs (FCs) as mutual aid organizations since 1980s. Survey results revealed that FCs had multitrack development routes depending on their local situation. The geographical proximity of the villages and the spontaneity of fishers’ decisions had fostered representativeness and a sense of community among local FC members. However, national-scale administrative decentralization conjunctly has led to an island-wide FC consolidation that replaced all local FCs with a singular large-scale one. Both advantages and disadvantages of fisheries governance under a large-scale FC were perceived by local fishers. To avoid precariousness in such a changing situation, a lesson from Lesvos is to deliberate on the local contexts of fishers’ communities to secure their presence in a renewed governance system that may become more complicated rather than simply decentralized.

How wettability affects boiling heat transfer: A three-dimensional analysis with surface potential energy

How surface wettability affects boiling heat transfer is still a challenging problem at nanoscale. In this work, a three-dimensional analysis of surface potential energy is used to address its relationship to surface wettability and nanoscale pool boiling characteristics of liquid molecules. It is found that the major reason for the enhanced heat transfer by increasing the surface wettability is essentially the improvement of surface potential energy, of which the influence is summarized using logic order. Moreover, the nanoscale boiling of water on copper surfaces with various wettability is investigated, which reveals that the increase in surface wettability can improve the heat transfer coefficient and critical heat flux under high superheat conditions in both nano- and macroscale systems. Besides, the effects of surface potential energy on contact angle, Kapitza resistance, heat transfer coefficient, and critical heat flux are analyzed systematically to demonstrate their relationships. A nondimensional analysis is finally implemented to correlate the normalized surface potential energy (P), the Nusselt number (Nu), and the normalized critical heat flux (J): Nu = 0.081P0.34, J = 0.827P0.50 (P < 2.387) and J = 1.221P0.05 (P > 2.387). This work provides insights into the enhancement mechanisms for the phase-change heat transfer of liquid molecules over surfaces with different wettability.

Mapping functional gradients of the striatal circuit using simultaneous microelectric stimulation and ultrahigh-field fMRI in non-human primates

Advances in functional magnetic resonance imaging (fMRI) have significantly enhanced our understanding of the striatal system of both humans and non-human primates (NHP) over the last few decades. However, its circuit-level functional anatomy remains poorly understood, partly because in-vivo fMRI cannot directly perturb a brain system and map its casual input-output relationship. Also, routine 3T fMRI has an insufficient spatial resolution. We performed electrical microstimulation (EM) of the striatum in lightly-anesthetized NHPs while simultaneously mapping whole-brain activation, using contrast-enhanced fMRI at ultra-high-field 7T. By stimulating multiple positions along the striatum's main (dorsal-to-ventral) axis, we revealed its complex functional circuit concerning mutually connected subsystems in both cortical and subcortical areas. Indeed, within the striatum, there were distinct brain activation patterns across different stimulation sites. Specifically, dorsal stimulation revealed a medial-to-lateral elongated shape of activation in upper caudate and putamen areas, whereas ventral stimulation evoked areas confined to the medial and lower caudate. Such dorsoventral gradients also appeared in neocortical and thalamic activations, indicating consistent embedding profiles of the striatal system across the whole brain. These findings reflect different forms of within-circuit and inter-regional neuronal connectivity between the dorsal and ventromedial striatum. These patterns both shared and contrasted with previous anatomical tract-tracing and in-vivo resting-state fMRI studies. Our approach of combining microstimulation and whole-brain fMRI mapping in NHPs provides a unique opportunity to integrate our understanding of a targeted brain area's meso- and macro-scale functional systems.