arXiv subjects

Murat Kuscu

Publications and source records attributed to Murat Kuscu.

At least 19 recordsLinked to original sources

arXiv2026

Information Theoretic Modeling of Interspecies Molecular Communication

Plants and insects communicate using chemical signals like volatile organic compounds (VOCs). A plant encodes information using different blends of VOCs, which propagate through the air to represent different symbolic information. This communication occurs in a noisy environment, characterized by wind, distance, and complex biological reactions. At the receiver, cross-reactive olfactory receptors produce stochastic binding events whose discretized durations form the receiver observation. In this paper, an information-theoretic framework is developed to model interspecies molecular communication (MC), where receptor responses are modeled probabilistically using a multinomial distribution. Numerical results show that the communication depends on environmental parameters such as wind speed, distance, and the number of released molecules. The proposed framework provides fundamental insights into the VOC-based interspecies communication under realistic biological and environmental conditions.

cs.IT↗

arXiv2026

Task-Adaptive Physical Reservoir Computing via Tunable Molecular Communication Dynamics

Physical Reservoir Computing (PRC) offers an efficient paradigm for processing temporal data, yet most physical implementations are static, limiting their performance to a narrow range of tasks. In this work, we demonstrate in silico that a canonical Molecular Communication (MC) channel can function as a highly versatile and task-adaptive PRC whose computational properties are reconfigurable. Using a dual-simulation approach -- a computationally efficient deterministic mean-field model and a high-fidelity particle-based stochastic model (Smoldyn) -- we show that tuning the channel's underlying biophysical parameters, such as ligand-receptor kinetics and diffusion dynamics, allows the reservoir to be optimized for distinct classes of computation. We employ Bayesian optimization to efficiently navigate this high-dimensional parameter space, identifying discrete operational regimes. Our results reveal a clear trade-off: parameter sets rich in channel memory excel at chaotic time-series forecasting tasks (e.g., Mackey Glass), while regimes that promote strong receptor nonlinearity are superior for nonlinear data transformation. We further demonstrate that post-processing methods improve the performance of the stochastic reservoir by mitigating intrinsic molecular noise. These findings establish the MC channel not merely as a computational substrate, but as a design blueprint for tunable, bioinspired computing systems, providing a clear optimization framework for future wetware AI implementations.

cs.ET↗

arXiv2026

Hybrid Artificial-Living Cell Collectives for Wetware Computing

Living systems continuously sense, integrate, and act on chemical information using multiscale biochemical networks whose dynamics are inherently nonlinear, adaptive, and energy-efficient. Yet, most attempts to harness such "wetware" for external computational tasks have centered on neural tissue and electrical interfaces, leaving the information-processing potential of non-neural collectives comparatively underexplored. In this letter, we study a hybrid artificial-living cell network in which programmable artificial cells write time-varying inputs into a biochemical microenvironment, while a living bacterial collective provides the nonlinear spatiotemporal dynamics required for temporal information processing. Specifically, artificial cells transduce an external input sequence into the controlled secretion of attractant and repellent molecules, thereby modulating the "local biochemical context" that bacteria naturally sense and respond to. The resulting collective bacterial dynamics, together with the evolving molecular fields, form a high-dimensional reservoir state that is sampled coarsely (voxel-wise) and mapped to outputs through a trained linear readout within a physical reservoir computing framework. Using an agent-based in silico model, we evaluate the proposed hybrid reservoir on the Mackey-Glass chaotic time-series prediction benchmark. The system achieves normalized root mean square error (NRMSE) values of approximately 0.33-0.40 for prediction horizons H=1 to 5, and exhibits measurable short-term memory as encoded in the distributed spatiotemporal patterns of bacteria and biochemicals. These results motivate the future exploration of non-neural hybrid cell networks for in situ temporal signal processing towards novel biomedical applications.

cs.ET↗

arXiv2025

Reservoir Computing-Based Detection for Molecular Communications

Diffusion-based Molecular Communication (MC) is inherently challenged by severe inter-symbol interference (ISI). This is significantly amplified in mobile scenarios, where the channel impulse response (CIR) becomes time-varying and stochastic. Obtaining accurate Channel State Information (CSI) for traditional model-based detection is intractable in such dynamic environments. While deep learning (DL) offers adaptability, its complexity is unsuitable for resource-constrained micro/nanodevices. This paper proposes a low-complexity Reservoir Computing (RC) based detector. The RC architecture utilizes a fixed, recurrent non-linear reservoir to project the time-varying received signal into a high-dimensional state space. This effectively transforms the complex temporal detection problem into a simple linear classification task, capturing ISI dynamics without explicit channel modeling or complex retraining. Evaluated in a realistic 3D mobile MC simulation environment (Smoldyn), our RC detector significantly outperforms classical detectors and achieves superior performance compared to complex ML methods (LSTM, CNN, MLP) under severe ISI. Importantly, RC achieves this with significantly fewer trainable parameters (e.g., 300 vs. up to 264k for MLP) and ultra-low latency inference (approx. 1 $μ$s per symbol).

cs.ET↗

arXiv2025

Molecular Communication Channel as a Physical Reservoir Computer

Molecular Communication (MC) channels are characterized by significant memory and nonlinear dynamics arising from diffusion and receptor kinetics. While often viewed as impairments to reliable data transmission, this work introduces a paradigm shift by reconceptualizing these intrinsic physical properties as computational resources. We frame a canonical point-to-point MC channel, comprising ligand diffusion and reversible ligand-receptor binding at a spherical receiver, as a Physical Reservoir Computer (PRC). Utilizing deterministic mean-field modeling and particle-based spatial stochastic simulations, we demonstrate the MC system's inherent capability for complex temporal information processing on standard chaotic time-series benchmarks. We comprehensively evaluate performance using both task-specific Normalized Root Mean Square Error (NRMSE) and the task-independent Information Processing Capacity (IPC). Our results reveal a non-monotonic dependence of computational power on key biophysical parameters (receptor kinetic rates, diffusion coefficient, and transmitter-receiver distance), identifying optimal operational regimes where memory and nonlinearity are balanced. These findings establish the MC channel as a viable computational substrate, paving the way for novel architectures in \emph{wetware} artificial intelligence.

cs.ET↗

arXiv2025

Hijacking Living Cells with Surface Engineering for the Internet of Bio-Nano Things

The Internet of Bio-Nano Things (IoBNT) promises to revolutionize healthcare by interfacing the cyber domain with the living systems at unprecedented resolution. Realizing this vision hinges on the development of Bio-Nano Things (BNTs), i.e., functional nodes capable of sensing, actuation, and communications within biological environments. Existing BNT architectures, e.g., nanomaterial-based, biosynthetic, and passive molecular agents, face significant limitations, including toxicity, lack of autonomy, or the safety and metabolic burdens associated with genetic modification. This paper posits a fourth paradigm: the transient hijacking of living cells via non-genetic cell surface engineering (NG-CSE) to enable living BNTs. NGCSE allows for the precise, reversible functionalization of cell membranes with synthetic molecular machinery, reprogramming cellular functions and interactions without altering the genome. It uniquely combines the inherent biocompatibility and agency of living cells with the programmability enabled by nanotechnology, mitigating the risks of genetic engineering. We critically review the toolbox of NG-CSE and explore the opportunities it unlocks for IoBNT, including programmable cell-cell communication, dynamic network topologies, and improved bio-cyber interfacing. Moreover, we propose novel IoBNT architectures that leverage these capabilities, such as circulating sentinel networks exploiting cellular agency for continuous liquid biopsy, and rationally designed, in vitro biocomputers exploiting interkingdom interactions. We also outline the critical challenges in modeling and exploiting cellular agency with NG-CSE, providing a roadmap for the effective utilization of NG-CSE-enabled living BNTs within IoBNT.

cs.ET↗

arXiv2025

Microdroplet-Based Communications with Frequency Shift Keying Modulation

Droplet-based communications has been investigated as a more robust alternative to diffusion-based molecular communications (MC), yet most existing demonstrations employ large "plug-like" droplets or simple T-junction designs for droplet generation, restricting modulation strategies and achievable data rates. Here, we report a microfluidic communication system that encodes information via the generation rate of sub-100 $μ$m water-in-oil microdroplets using a microfabricated flow focusing architecture. By precisely tuning the flow rate of the dispersed-phase (water) via a pressure-regulated flow controller, we implement frequency shift keying modulation with four symbols (4-FSK). A high-speed optical detection and video processing setup serves as the receiver, tracking system response in the microfluidic channel across different symbol durations (20 s and 12 s) and quantifying error performance. Despite the miniaturized device and channel architecture, our experiments demonstrate programmable and reliable data transmission with minimal symbol errors. Beyond water-in-oil systems, the same encoding principles can be extended to other compartmentalized carriers (e.g., giant unilamellar vesicles, polymersomes) that can also be synthesized via flow focusing techniques, paving the way for biocompatible, robust, and high-capacity communication in intrabody networks and the emerging Internet of Bio-Nano Things.

cs.ET↗

arXiv2025

Low-cost Microfluidic Testbed for Molecular Communications with Integrated Hydrodynamic Gating and Screen-printed Sensors

Molecular Communications (MC), transferring information via chemical signals, holds promise for transformative healthcare applications within the Internet of Bio-Nano Things (IoBNT) framework. Despite promising advances toward practical MC systems, progress has been constrained by experimental testbeds that are costly, difficult to customize, and require labor-intensive fabrication. Here, we address these challenges by introducing a low-cost ($\sim$\$1 per unit), rapidly fabricated ($<$1 hour), and highly customizable microfluidic testbed that integrates hydrodynamic gating and screen-printed potentiometric sensors. This platform enables precise spatiotemporal control over chemical signals and supports reconfigurable channel architectures along with on-demand sensor functionalization. As a proof of concept, we demonstrate a pH-based MC system combining a polyaniline (PANI)-functionalized sensor for real-time signal detection with a programmable hydrodynamic gating architecture, patterned in a double-sided adhesive tape, as the transmitter. By dynamically mixing phosphate-buffered saline (PBS) with an acidic solution (pH 3), the testbed reliably generates pH-encoded pulses. Experimental results confirm robust control over pulse amplitude and pulse width, enabling the simulation of end-to-end MC scenarios with 4-ary concentration shift keying (CSK) modulation. By combining affordability and rapid prototyping without compromising customizability, this platform is poised to accelerate the translation of MC concepts into practical IoBNT applications.

cs.ET↗

arXiv2024

Experimental Characterization of Hydrodynamic Gating-Based Molecular Communication Transmitter

Molecular communication (MC) is a bio-inspired method of transmitting information using biochemical signals, promising for novel medical, agricultural, and environmental applications at the intersection of bio-, nano-, and communication technologies. Developing reliable MC systems for high-rate information transfer remains challenging due to the complex and dynamic nature of application environments and the physical and resource limitations of micro/nanoscale transmitters and receivers. Microfluidics can help overcome many such practical challenges by enabling testbeds that can replicate the application media with precise control over flow conditions. However, existing microfluidic MC testbeds face significant limitations in chemical signal generation with programmable signal waveforms, e.g., in terms of pulse width. To tackle this, we previously proposed a practical microfluidic MC transmitter architecture based on the hydrodynamic gating technique, a prevalent chemical waveform generation method. This paper reports the experimental validation and characterization of this method, examining its precision in terms of spatiotemporal control on the generated molecular concentration pulses. We detail the fabrication of the transmitter, its working mechanism and discuss its potential limitations based on empirical data. We show that the microfluidic transmitter is capable of providing precise, programmable, and reproducible molecular concentration pulses, which would facilitate the experimental research in MC.

cs.ET↗

arXiv2024

ProtoFlakes: A Conceptual Modular and Plug-and-Play Prototyping Tool Kit for Smart Jewelry Design Exploration

The design of smart jewelry can be challenging as it requires technical knowledge and practice to explore form and function. Adressing this issue, we propose ProtoFlakes, a design speculation for a modular prototyping tool kit for smart jewelry design. ProtoFlakes builds upon the our prior work of Snowflakes, targeting designers with limited technical expertise with a tool kit to make creative explorations and develop prototypes closely resembling the final products they envision. The design requirements for ProtoFlakes were determined by conducting ideation workshops. From these workshops, we extracted four design parameters that informed the development of the tool kit. ProtoFlakes allows the exploration of form and function in a flexible and modular way and provides a fresh perspective on smart jewelry design. Exploring this emerging area with design speculations informed by ideation workshops has the potential to drive advancements towards more accessible and user-friendly tools for smart jewellery design.

cs.HC↗

arXiv2023

Frequency-Domain Detection for Molecular Communication with Cross-Reactive Receptors

Molecular Communications (MC) is a bio-inspired communication paradigm that uses molecules as information carriers, requiring unconventional transceivers and modulation/detection techniques. Practical MC receivers (MC-Rxs) can be implemented using field-effect transistor biosensor (bioFET) architectures, where surface receptors reversibly react with ligands. The time-varying concentration of ligand-bound receptors is translated into electrical signals via field effect, which is used to decode the transmitted information. However, ligand-receptor interactions do not provide an ideal molecular selectivity, as similar ligand types, i.e., interferers, co-existing in the MC channel, can interact with the same type of receptors. Overcoming this molecular cross-talk in the time domain can be challenging, especially when Rx has no knowledge of the interferer statistics or operates near saturation. Therefore, we propose a frequency-domain detection (FDD) technique for bioFET-based MC-Rxs that exploits the difference in binding reaction rates of different ligand types reflected in the power spectrum of the ligand-receptor binding noise. We derive the bit error probability (BEP) of the FDD technique and demonstrate its effectiveness in decoding transmitted concentration signals under stochastic molecular interference compared to a widely used time-domain detection (TDD) technique. We then verified the analytical performance bounds of the FDD through a particle-based spatial stochastic simulator simulating reactions on the MC-Rx in microfluidic channels.

eess.SP↗

arXiv2023

Microfluidic Molecular Communication Transmitter Based on Hydrodynamic Gating

Molecular Communications (MC) is a bio-inspired paradigm for transmitting information using chemical signals, which can enable novel applications at the junction of biotechnology, nanotechnology, and information and communication technologies. However, designing efficient and reliable MC systems poses significant challenges due to the complex nature of the physical channel and the limitations of the micro/nanoscale transmitter and receiver devices. In this paper, we propose a practical microfluidic transmitter architecture for MC based on hydrodynamic gating, a widely utilized technique for generating chemical waveforms in microfluidic channels with high spatiotemporal resolution. We develop an approximate analytical model that can capture the fundamental characteristics of the generated molecular pulses, such as pulse width, pulse amplitude, and pulse delay, as functions of main system parameters, such as flow velocity and gating duration. We validate the accuracy of our model by comparing it with finite element simulations using COMSOL Multiphysics under various system settings. Our analytical model can enable the optimization of microfluidic transmitters for MC applications in terms of minimizing intersymbol interference and maximizing data transmission rate.

cs.ET↗

arXiv2023

Frequency-Domain Model of Microfluidic Molecular Communication Channels with Graphene BioFET-based Receivers

Molecular Communication (MC) is a bio-inspired communication paradigm utilizing molecules for information transfer. Research on this unconventional communication technique has recently started to transition from theoretical investigations to practical testbed implementations, primarily harnessing microfluidics and sensor technologies. Developing accurate models for input-output relationships on these platforms, which mirror real-world scenarios, is crucial for assessing modulation and detection techniques, devising optimized MC methods, and understanding the impact of physical parameters on performance. In this study, we consider a practical microfluidic MC system equipped with a graphene field effect transistor biosensor (bioFET)-based MC receiver as the model system, and develop an analytical end-to-end frequency-domain model. The model provides practical insights into the dispersion and distortion of received signals, thus potentially informing the design of new frequency-domain MC techniques, such as modulation and detection methods. The accuracy of the developed model is verified through particle-based spatial stochastic simulations of pulse transmission in microfluidic channels and ligand-receptor binding reactions on the receiver surface.

cs.ET↗

arXiv2023

Adaptive Molecular Communication Receivers with Tunable Ligand-Receptor Interactions

Molecular Communications (MC) underpins signaling in biological systems, enabling information transfer through biochemical molecules. The prospect of engineering this natural communication mechanism has inspired the Internet of Bio-Nano Things (IoBNT) applications, which rely on heterogeneous collaborative networks of natural and engineered biological devices, as well as artificial micro/nanomachines. A key attribute of natural MC systems is their adaptability, ensuring accurate information transmission in dynamic, time-varying biochemical environments. Therefore, integrating biological adaptation techniques into artificial MC networks, which are expected to operate in various biochemical environments, such as inside human body, is essential for robust and biocompatible IoBNT applications. This study explores the design of bio-inspired adaptive MC receivers capable of tuning their response functions for maintaining optimal detection performance in scenarios with time-varying received signals. The proposed receiver architectures are based on ligand-receptor interactions, with adaptivity achieved by modifying the sigmoidal-shaped ligand-receptor response curve in response to fluctuations in received signal statistics. The performance of these adaptive receivers is evaluated across a range of MC scenarios, including those with stochastic background interference, inter-symbol interference (ISI), and degrading enzymes, which involve time-varying scaling or shifting of received signals. Numerical results demonstrate the significant improvement in detection performance provided by adaptive receivers in dynamic MC scenarios.

cs.ET↗

arXiv2023

Affinity-Division Multiplexing for Molecular Communications with Promiscuous Ligand Receptors

A key challenge in Molecular Communications (MC) is low data transmission rates, which can be addressed by channel multiplexing techniques. One way to achieve channel multiplexing in MC is to leverage the diversity of different molecule types with respect to their receptor binding characteristics, such as affinity and kinetic binding/unbinding rates. In this study, we propose a practical multiplexing scheme for MC, which is based on the diversity of ligand-receptor binding affinities. This method requires only a single type of promiscuous receptor on the receiver side, capable of interacting with multiple ligand types. We analytically derive the mean Bit Error Probability (BEP) over all multiplexed MC channels as a function of similarity among ligands in terms of their receptor affinities, the number of receptors, the number of multiplexed channels, and the ratio of concentrations encoding bit-1 and bit-0. We investigate the impact of each design parameter on the performance of multiplexed MC system.

cs.ET↗

arXiv2023

Graphene and Related Materials for the Internet of Bio-Nano Things

Internet of Bio-Nano Things (IoBNT) is a transformative communication framework, characterized by heterogeneous networks comprising both biological entities and artificial micro/nano-scale devices, so-called Bio-Nano Things (BNTs), interfaced with conventional communication networks for enabling innovative biomedical and environmental applications. Realizing the potential of IoBNT requires the development of new and unconventional communication technologies, such as molecular communications, as well as the corresponding transceivers, bio-cyber interfacing technologies connecting the biochemical domain of IoBNT to the electromagnetic domain of conventional networks, and miniaturized energy harvesting and storage components for the continuous power supply to BNTs. Graphene and related materials (GRMs) exhibit exceptional electrical, optical, biochemical, and mechanical properties, rendering them ideal candidates for addressing the challenges posed by IoBNT. This perspective article highlights recent advancements in GRM-based device technologies that are promising for implementing the core components of IoBNT. By identifying the unique opportunities afforded by GRMs and aligning them with the practical challenges associated with IoBNT, particularly in the materials domain, our aim is to accelerate the transition of envisaged IoBNT applications from theoretical concepts to practical implementations, while also uncovering new application areas for GRMs.

cs.ET↗

arXiv2023

Ratio Shift Keying Modulation for Time-Varying Molecular Communication Channels

Molecular Communications (MC) is a bio-inspired communication technique that uses molecules to encode and transfer information. Many efforts have been devoted to developing novel modulation techniques for MC based on various distinguishable characteristics of molecules, such as their concentrations or types. In this paper, we investigate a particular modulation scheme called Ratio Shift Keying (RSK), where the information is encoded in the concentration ratio of two different types of molecules. RSK modulation is hypothesized to enable accurate information transfer in dynamic MC scenarios where the time-varying channel characteristics affect both types of molecules equally. To validate this hypothesis, we first conduct an information-theoretical analysis of RSK modulation and derive the capacity of the end-to-end MC channel where the receiver estimates concentration ratio based on ligand-receptor binding statistics in an optimal or suboptimal manner. We then analyze the error performance of RSK modulation in a practical time-varying MC scenario, that is mobile MC, in which both the transmitter and the receiver undergo diffusion-based propagation. Our numerical and analytical results, obtained for varying levels of similarity between the ligand types used for ratio-encoding, and varying number of receptors, show that RSK can significantly outperform the most commonly considered MC modulation technique, concentration shift keying (CSK), in dynamic MC scenarios.

cs.ET↗

arXiv2023

Microfluidic Pulse Shaping Methods for Molecular Communications

Molecular Communication (MC) is a bio-inspired communication modality that utilizes chemical signals in the form of molecules to exchange information between spatially separated entities. Pulse shaping is an important process in all communication systems, as it modifies the waveform of transmitted signals to match the characteristics of the communication channel for reliable and high-speed information transfer. In MC systems, the unconventional architectures of components, such as transmitters and receivers, and the complex, nonlinear, and time-varying nature of MC channels make pulse shaping even more important. While several pulse shaping methods have been theoretically proposed for MC, their practicality and performance are still uncertain. Moreover, the majority of recently proposed experimental MC testbeds that rely on microfluidics technology lack the incorporation of programmable pulse shaping methods, which hinders the accurate evaluation of MC techniques in practical settings. To address the challenges associated with pulse shaping in microfluidic MC systems, we provide a comprehensive overview of practical microfluidic chemical waveform generation techniques that have been experimentally validated and whose architectures can inform the design of pulse shaping methods for microfluidic MC systems and testbeds. These techniques include those based on hydrodynamic and acoustofluidic force fields, as well as electrochemical reactions. We also discuss the fundamental working mechanisms and system architectures of these techniques, and compare their performances in terms of spatiotemporal resolution, selectivity, system complexity, and other performance metrics relevant to MC applications, as well as their feasibility for practical MC applications.

cs.ET↗