Nearby Charge Research Articles

Freezing Conformers for Gas-Phase Förster Resonance Energy Transfer.

Various techniques are available to illuminate geometric structures of molecular ions in gas phase, such as Förster Resonance Energy Transfer (FRET) informing on distances between two dyes covalently attached to a molecule. Typically, cationic rhodamines, which absorb and emit visible light, are used for labeling. Extensive work has revealed that the transition energy of a rhodamine is intricately linked to its nearby microenvironment, with nearby charges causing Stark-shifted emission. This occurs because the inter-dye Coulomb interaction is weaker in the excited state (S1) than in the ground state (S0) due to the increase in polarizability upon excitation. Therefore, absorption and emission spectra, along with FRET efficiencies, provide insights into structural motifs. At room temperature, multiple conformers often co-exist, leading to overlapping absorption bands among different conformers and broad spectra. To study specific conformers, it is necessary to isolate them, for example, using ion-mobility spectrometry. Another approach is to reduce temperature, which results in spectral narrowing and distinct absorption bands, allowing for the selection of specific conformers through selective excitation. Here, we describe the instrumentation used for cryogenically cold FRET experiments and discuss recent results for small model systems, as well as future directions for a technique still in its infancy.

(Invited) Developing a Graphene Field-Effect Biosensor for Genetic Biomarkers: Simulations Unveil How the Device Sensitivity Is Related to DNA-Graphene Interactions at the Nanoscale

Graphene field-effect transistor biosensors (GFETs) offer a promising platform to detect cancer DNA biomarkers at low concentration [1]. At their core, they have an electronic circuit containing a graphene sheet – a two-dimensional nanomaterial made of a single layer of carbon atoms – whose electronic properties are very sensitive to nearby electric charges. Leveraging that feature, the electrical current generated by a GFET can thus be made very sensitive to the concentration of a specific DNA sequence in a biological sample. To achieve this, the complementary DNA sequence is linked to the graphene to bind specifically the target DNA. In most GFETs, the link is done using 1-pyrenebutanoic acid succinimidyl ester (PBASE) because its pyrene group stacks on the graphene through pi-pi interactions, without disrupting the electronic properties of the graphene. However, recent experiments in the Bouilly group have shown variations in GFET sensitivity depending on the incubation time of graphene with PBASE.Here, we use a computational approach developed in our previous work [2] to investigate at the nanoscale the role of PBASE linker molecules on the sensitivity of the GFET. First, we use molecular dynamics simulations to characterize the conformational ensemble of a 10-nt single-stranded DNA sequence linked to a graphene sheet using PBASE. Second, we estimate the electrical response of the GFET from the electrostatic potential generated by these DNA conformations on the graphene, as determined using electrostatic Poisson-Boltzmann simulations. Our results show that the conformational ensemble of DNA is strongly affected by the presence of other PBASE adsorbed on the graphene, thus changing the electrostatic potential generated on the graphene. The predicted change of the electrostatic potential should impact measurably the detection signal of the GFET.We are now using these simulations to explain the experimental characterizations of a GFET designed to detect a genetic biomarker important in breast cancer profiling. Our simulations have the potential to support the development of GFETs with better sensitivity for DNA detection.[1] Béraud, A., Sauvage, M., Bazán, C. M., Tie, M., Bencherif, A., and Bouilly, D. (2021) Graphene field-effect transistors as bioanalytical sensors: design, operation and performance. Analyst. 146:403-428.[2] Côté, S., Mousseau, N., and Bouilly, D. (2022) The molecular origin of the electrostatic gating of single-molecule field-effect biosensors investigated by molecular dynamics simulations. Phys. Chem. Chem. Phys. 24:4174-4186.

Diffraction order penalization to improve spectrometer calibrations

Wavelength calibration in diffraction spectroscopy typically depends on identifying strong, well-known lines in the recorded spectra and fitting a calibration function to them. In this paper, we outline a novel method (order penalization) for improving spectroscopic calibrations by extending non-linear least squares fitting of the calibration curve. The method introduces an extra term into the minimized quantity that penalizes disagreement in the positions of spectral lines observed in multiple diffraction orders. The primary advantage of this method is that the lines used do not have to be identified, except for establishing the fact that they are different orders of the same line. This increases the number of constraints on the calibration curve, potentially in spectral regions where no regular calibration lines are available. The mathematical basis of this method is described, and the performance of this method is evaluated on simulated data and experimental data from the National Institute of Standards and Technology (NIST) Electron Beam Ion Trap. We demonstrate the effectiveness of the method on the spectra of highly charged Ag-like Re28+ and nearby charge state ions.

Intermediate Intercluster Bond Orders. Electronic Communication in Au38(SR)24 Superatomic Molecules.

Ligand-protected gold clusters remain potential building blocks for envisaged molecular materials. The archetypal Au38(SR)24 cluster can be viewed as a robust template for the fusion of two Au25(SR)18 - cluster units, retaining a bi-icosahedral Au23 core. Via electrochemical properties, the overall charge state can be selectively tuned, enabling the access of 14 valence electron (ve) species featuring a single intercluster bond and nearby charge from -1 to +3, achieving related species bearing 15- to 11-ve with variable intercluster bond orders. Here, we explore the characteristics of intermediate intercluster bond orders in order to provide insights into the plausible electron communication between the constituent building blocks, with Au38(SR)24, as a representative template. Our results denote a small structural variation along -1 to +3 charge states, provided by the core-protecting ligand interaction, which is enhanced towards more oxidized species. The remaining unpaired electron from intermediate intercluster bond orders of 1.5 for Au38(SR)24 1-, 1.5 for Au38(SR)24 1+, and 2.5 for Au38(SR)24 3+, holds delocalized characteristics between the building block units, favoring electron communication for conductive and cooperative cluster aggregates. Such features are relevant for the formation of molecular electronic device applications, favoring the rationalization prior to engaging in explorative synthesis of larger ligand-protected cluster aggregates.

Smart Slot Assignment for Urban EV Charging Using Folium API Integration

Abstract: Efficient management of electric vehicle (EV) charging distribution in urban areas is crucial amid increasing demand and varying traffic conditions. This study proposes a novel web-based solution that integrates Folium Map API for realtime location tracking and Python Flask backend with MySQL database storage to allocate charging demands. By leveraging real-time traffic information from the Folium Map API, the proposed model optimizes charging resource allocation across multiple stations and road networks. The web interface, built using HTML, CSS, and JavaScript, allows users to interact with the system seamlessly. Charging allocation is dynamically adjusted based on real-time data, prioritizing maxi- mum returns. Additionally, an emergency charge counter facility is introduced to cater to unforeseen charging needs, enhancing user flexibility. The system offers two interfaces and a dashboard for both station administrators and users, en- abling pre-booking services for travelers during their journey, facilitating access to nearby charging stations, and providing a facility for prebooking. These features contribute to improved station revenue and pile utilization, highlighting the efficacy of the proposed web-based approach. By leveraging advanced web technologies and APIs, this comprehensive strategy enhances charging infrastructure efficiency, fosters the widespread adoption of electric vehicles, and contributes to sustainable urban mobility management.

Effects of valence changes of iodine on perovskite (CH3NH3PbI3) Raman

In recent years, organic–inorganic hybrid perovskite materials have garnered extensive attention from scholars. Given its high absorption coefficient, carrier mobility, and diffusion length, it is widely studied for applications in various optoelectronic devices, such as solar cells, photodetectors, field-effect transistors, and light emitting diodes. Among them, the interfacial charge transfer process is a key factor influencing the performance of devices using perovskite materials. The charge transfer (CT) at the interface is typically detected via Raman spectroscopy. There are three types of related CT processes, namely, the interfacial ground state charge transfer, the photoinduced charge transfer resonance, and the electronic excitation resonance within the molecule itself. Among these factors, electronic excitation resonance manifests as an exciton resonance within the perovskite structure, providing energy for nearby charge transfer, thereby promoting charge transfer and enhancing Raman signals. Therefore, enhancing exciton resonance within the perovskite structure plays a crucial role in optoelectronic devices. This paper aimed to study the mechanism of oxygen plasma passivation of interstitial iodine defects and its enhancement effect on the Raman of perovskite substrates. Typically, interstitial iodine defects induce electron–hole recombination. In the process of oxygen plasma treatment, interstitial iodine is converted into pentavalent iodine, which can effectively fill related defects, inhibit electron–hole recombination, and prolong exciton lifetime, thereby promoting charge transfer and enhancing Raman intensity.

Wireless Power Transfer: A simulation-focused exploration

Wireless power transfer (WPT) is leading a technological revolution, redefining how we transmit electrical energy without the usage of cables or connectors. This exploration peeks into various WPT systems, each offering unique benefits and applications. From magnetic inductive coupling for nearby charging to resonant inductive coupling for power transfer across longer distances, and from capacitive coupling for low-power needs to magnetic resonance coupling for mid-range transmission, this paper presents an introduction to the world of WPT. Through simulations in MATLAB and Simulink, we gain insights into various applications like consumer electronics, healthcare, automotive, and more. Looking ahead, we foresee a future where WPT uses sustainable energy practices and creates entirely wireless environments.

Enhancing Electric Bus Charging Scheduling: An Energy-Integrated Dynamic Bus Replacement Strategy with Time-of-Use Pricing

Existing studies on electric bus (EB) scheduling mainly focus on the arrangement of bus charging at the bus terminals, which may lead to inflexible charging plans, high scheduling costs, and low utilization of electricity energy. To address these challenges, this paper proposes a dynamic bus replacement strategy. When the power of an in-service EB is insufficient, a standby EB stationed at nearby charging stations is dispatched in advance to replace this in-service EB at a designated bus stop. Passengers then transfer to the standby bus to complete their journey. The replaced bus proceeds to the charging station and transitions into a “standby bus” status after recharging. A mixed-integer nonlinear programming (MINLP) model is established to determine the dispatching plan for both standby and in-service EBs while also designing optimal charging schemes (i.e., the charging time, location, and the amount of charged power) for electric bus systems. Additionally, this study also incorporates the strategy of time-of-use electricity prices to mitigate the adverse impact on the power grid. The proposed model is linearized to the mixed-integer linear programming (MILP) model and efficiently solved by commercial solvers (e.g., GUROBI). The case study demonstrates that EBs with different energy levels can be dynamically assigned to different bus lines using bus replacement strategies, resulting in reduced electricity costs for EB systems without compromising on scheduling efficiency.

Electric Vehicle Battery State of Charge and Charging Station Distance Estimation Using IoT

Background: The global transition to green energy and the rapid development of Electric Vehicle (EV) technology, along with falling component costs, have fueled the growing popularity of electric vehicles. To support the widespread adoption of EVs, an efficient and userfriendly charging infrastructure is crucial. Objective: This work aims to propose a comprehensive EV charging system that addresses the rising demand for charging stations, streamlines the charging process, and empowers EV drivers with essential information. The primary focus is on an economical and effective booking system, enabling users to locate nearby charging stations and make informed choices about their charging preferences. Method: We suggest developing a EVs Charging Finder App, serving as a central platform for EV users to find nearby charging stations. The app will provide vital details, including ratings, reviews, available time slots, charging duration estimates, and more. Users can also contribute new charging station data, fostering app growth. Additionally, an alert system will notify users when nearby charging slots become available, enhancing convenience for EV drivers. Results: The EVs Charging Finder App is anticipated to significantly enhance the accessibility and convenience of EV charging. Users can effortlessly locate charging stations, assess quality through reviews and ratings, and plan charging sessions based on real-time availability. The battery voltage of 45.2 V is a critical parameter for monitoring the health and performance of the battery, influencing the accuracy of state of charge (SoC) estimations and potentially impacting the efficiency of the electric vehicle. The 47.7 km driven is a key factor in assessing energy consumption and vehicle efficiency, which can affect the remaining state of charge in the battery. The battery's state of charge (SOC) is at 85%, indicating a relatively high charge level. Knowing that the charging station is available is crucial for planning charging activities, allowing users to proceed without concerns about station availability. The booking time at 10:00 AM is essential for efficiently managing charging infrastructure, especially in scenarios with high demand for charging services. These data points collectively contribute to optimizing the charging experience and ensuring the effective utilization of electric vehicle resources. Conclusion: The proposed EVs Charging Finder App offers a practical and efficient solution to address the surging demand for charging stations. By providing comprehensive information and real-time alerts, this system aims to make EV charging more accessible, user-friendly, and environmentally sustainable.

Heavy-flavor transport and hadronization in pp collisions

Recent experimental results on the Λc+/D0 ratio in proton-proton (pp) collisions have revealed a significant enhancement compared to expectations based on universal fragmentation fractions/functions across different colliding systems, from e+e− to pp. This unexpected enhancement has sparked speculation about the potential effects of a deconfined medium impacting hadronization, previously considered exclusive to heavy-ion collisions. In this study, we propose a novel approach that assumes the formation of a small, deconfined, and expanding fireball even in pp collisions, where charm quarks can undergo rescattering and hadronization. We make use of the same in-medium hadronization mechanism developed for heavy-ion collisions, which involves local color-neutralization through recombination of charm quarks with nearby opposite color charges from the background fireball. Our model incorporates the presence of diquark excitations in the hot medium, which promotes the formation of charmed baryons. Moreover, the recombination process, involving closely aligned partons from the same fluid cell, effectively transfers the collective flow of the system to the final charmed hadrons. We show that this framework can qualitatively reproduce the observed experimental findings in heavy-flavor particle-yield ratios, pT-spectra and elliptic-flow coefficients. Our results provide new, complementary supporting evidence that the collective phenomena observed in small systems naturally have the same origin as those observed in heavy-ion collisions. Published by the American Physical Society 2024

New method of fabrication of suspended metallic single electron transistor (SET)

Charge sensing applications utilizing single electron transistors (SETs) as electrometers face challenges due to nearby background charge movements. In this study, we present an innovative fabrication method for creating suspended Al-AlOx-Al SETs positioned above a cavity. These suspended SETs exhibit significantly reduced flicker noise with 1fα noise spectral density when compared to their substrate-based counterparts. This noise reduction can be attributed to the elimination of the substrate beneath the SET island. Consequently, our fabricated suspended SETs are highly suitable for demanding charge sensing applications and provide a promising platform for in-depth investigations into the sources of charge noise in such devices.

Heavy-flavor transport and hadronization in a small fireball

We study heavy-flavor hadron production in high-energy pp collisions, assuming the formation of a small, deconfined and expanding fireball where charm quarks can undergo rescattering and hadronization. We adopt the same in-medium hadronization mechanism developed for heavy-ion collisions, which involves Local Color-Neutralization (LCN) through recombination of charm quarks with nearby opposite color charges from the background fireball. Diquark excitations in the hot medium favor the formation of charmed baryons. The recombination process, involving closely aligned partons from the same fluid cell, effectively transfers the collective flow of the system to the final charmed hadrons. This framework can qualitatively reproduce the observed experimental findings in heavy-flavor particle-yield ratios, pT -spectra and ellipticflow coefficients. Our results provide new, complementary support to the idea that the collective phenomena observed in small systems have the same origin as those observed in heavy-ion collisions.

Enhancing Resilience With Electric Vehicles Charging Redispatching and Vehicle-to-Grid in Traffic-Electric Networks

Electric vehicles (EVs) can be viewed as both electric loads and a type of mobile storage resource. Effective management and utilization of EVs can yield significant benefits for networks. This paper proposes a novel resilience enhancement method for coupled traffic-electric networks with a high penetration of EVs, incorporating two specific strategies in response to contingencies. The first strategy involves rerouting and reselecting charging stations for power-deficient EVs, while the second entails redispatching power-sufficient EVs to the most suitable nearby charging stations to provide grid support through vehicle-to-grid technology. A carefully designed pricing mechanism, which includes imposing additional road congestion tolls and charging station charging fees, is incorporated to facilitate rerouting and charging station reselection for EVs under the user equilibrium principle. Furthermore, a formulation incorporating the two proposed resilience enhancement strategies for coupled traffic-electric networks is presented. This formulation enables coordination between the two networks to capitalize on flexibility derived from sector coupling. A series of linearization techniques are then introduced to transform the original problem into a mixed-integer quadratically constrained programming model. Numerical results based on a coupled network with 20 traffic roads and 21 electric buses are presented to demonstrate the effectiveness of the proposed resilience enhancement method.

Power on the Go: A Solution to Address Electric Vehicle Charging Challenges

In this article, we propose a novel solution to address the current challenges related to charging an Electric Vehicle (EV). The Power on the Go: Single-drop and Double-drop problems allow an EV to be charged at a convenient location, where a service vehicle (drone), which is launched from a nearby charging station, can bring a compatible power bank at the request of the driver through an app. The objective is to reduce the cumulative wait time between service requests and the start of charging. We present mathematical formulations and two order-first split-second-based heuristic approaches for both problems. While the mathematical formulations can generate optimal solutions for small instances in a reasonable amount of time, the heuristics are fast and perform very well, with gaps < 5% for up to 20 node instances. Moreover, the formulations highlight the mean savings in wait time (29.37%) when the power bank can charge two EVs consecutively before a replacement is needed. The implications of the proposed model can be extensive, as we seek to overcome the availability and technological challenges of EV charging while advocating its adoption.

Occurrence Modes of AAEMs (Na+ and Ca2+) and the Effect on the Molecular Structures of Zhundong Coal via Quantum Chemistry.

Zhundong coal is known for its high content of alkali and alkaline earth metals (AAEMs), which greatly influences coal processing and utilization. To reveal the occurrence modes and the effect of AAEM ions on the molecular structures of Zhundong coal, the previously constructed molecular structure models of vitrinite-rich and inertinite-rich Zhundong coal (ZD-V and ZD-I) were selected to simulate using quantum chemical methods. By focusing on Na+ and Ca2+, the adsorption capacity at different adsorption sites was investigated based on the density functional theory (DFT), and the effects of adsorption of Na+ and Ca2+ on nearby atomic charges, chemical bonds, and molecular orbitals were investigated. Results show that compared with ZD-I, ZD-V contains a more negative electrostatic potential (ESP) distribution and lower bond order, indicating that vitrinite contains more adsorption sites for AAEM ions and exhibits stronger chemical reactivity. Na+ and Ca2+ are easily adsorbed to the most negative ESP with the optimal adsorption site near the carbonyl group (C=O). Compared with adsorbed Na+, Ca2+ has a smaller adsorption distance from the molecule and a higher adsorption energy. Ca2+ can transfer more charge than Na+ and has more affinity with the coal molecule. Ca2+ at all adsorption sites is bound to organic molecules by chemisorption, which also reveals the reason for the low water-soluble Ca content in coal at the molecular level. Adsorption of AAEM ions has a more significant effect on the chemical bond of oxygen-containing functional groups near AAEM ions compared to the overall molecular fragments, which makes the nearby chemical bonds (C-O/C=O) decrease in bond order and increase in bond length. Ca2+ makes the nearby chemical bonds more prone to break than Na+. Additionally, Ca2+ has a more significant impact on the energy gaps (ΔEgap) compared to Na+. Adsorption of Ca2+ near the carbonyl and carboxyl groups leads to a significant decrease in ΔEgap, indicating an enhanced chemical reactivity of coal molecular fragments.

Electric Vehicle Charging Station Automation

Electric vehicles are a promising class of drive trains in the coming years especially in urban regions it is revolution helpful in shifting the decentralized exhaust emission in mega-cities to centralized power plants in rural areas. An intelligent system can be used to manage all the systems using automation technology. Searching for charging stations for electric vehicles is an important issue for drivers which needs the implementation of a smart charging infrastructure network. The automation helps to check the charging slot availability and booking slot for electrical vehicle charging. It is important to reduce waiting time as well as provide improved efficiency. Our system is intended for locating nearby charging stations and slot booking according to waiting time and availability of charging stations. The booking process is automated to improve efficiency in accessing the charging station facilities.

Home charging for all: Techno-economic and life cycle assessment of multi-unit dwelling electric vehicle charging hubs

Ubiquitous electric vehicle adoption can drastically reduce greenhouse gas emissions (GHG) but will require equitable home charging infrastructure for all residences. Unlike single-family homes, Multi-Unit Dwellings (MUD) currently lack market share and access to nearby charging infrastructure partly due to expensive capital costs for reluctant residential property-owners. This work evaluates the levelized cost of charging (LCOC) for Battery Electric Vehicles (BEVs) at MUD community charging hubs through a techno-economic analysis (TEA) that leverages real-world charging data and costs. Three different MUD charging types are investigated for a baseline and optimistic case: 1.9-kW Level 1 (L1), 6.6-kW Level 2 (L2), and 50-kW Direct Current Fast Charging (DCFC) stations under three different ownership models: resident, utility, and private company. Results demonstrate L1 and L2 chargers to be less expensive than the gasoline equivalent across the United States. Further, utility and private company ownership models, which avoid initial costs for residential property owners, result in a large LCOC premium for L1 and moderate LCOC premium for L2 relative to the resident ownership model. In contrast, DCFC is shown to be expensive for baseline scenarios but economical for optimistic scenarios especially under private company ownership. This work also performs a cradle to grave (C2G) life cycle assessment (LCA) of an average passenger BEV and gasoline conventional vehicle (CV) using yearly (grid mix & vehicle parameters), hourly (grid mix), and state-level (grid mix) resolution. Results show BEVs to have lower GHG emissions (−86% to −10%) than gasoline CVs in the contiguous U.S. Next, the system boundary of the TEA is extended to the total cost of ownership (TCO) of BEVs. The TCO is then coupled with the C2G GHG emissions to calculate the cost of GHG emissions reduction. Ultimately, the cost of GHG emissions reduction from MUD BEVs relative to gasoline CVs is shown to be negative for every scenario except baseline DCFC, meaning MUD BEV charging infrastructure can be a cost-effective endeavor to reduce GHG emissions.

Quantifying the Spectral Diffusion of N- V Centers by Symmetry

The spectrally narrow, spin-dependent optical transitions of nitrogen-vacancy (N-$V$) center defects in diamond can be harnessed for quantum networking applications. Key to such networking schemes is the generation of indistinguishable photons. Two challenges limit scalability in such systems: defect-to-defect variations of the optical transition frequencies caused by local strain variation, and spectral diffusion of the optical frequencies on repeated measurement caused by photoexcitation of nearby charge traps. In this experimental study we undertake a group-theoretic approach to quantifying spectral diffusion and strain, decomposing each into components corresponding to Jahn-Teller symmetries of the N-$V$ center. We investigate correlations between the components of strain, spectral diffusion, and depth from the surface, finding that strain and spectral diffusion are each dominated by longitudinal perturbations. We also find a weak negative correlation between transverse static strain and total spectral diffusion, suggesting that transverse strain provides some degree of protection from spectral diffusion. Additionally, we find that spectral diffusion becomes more pronounced with increasing depth in the diamond bulk. Our symmetry-decomposed technique for quantifying spectral diffusion can be valuable for understanding how a given nanoscale charge trap environment influences spectral diffusion and for developing strategies of mitigation.

A new state of charge estimation technique of lithium-ion battery using adaptive extended Kalman filter and artificial neural network

Due to rapid rise in climate change, world is seeing a major technology shift from conventional vehicles to electric vehicles (EVs). Battery’s state of charge (SOC) is a critical parameter in EVs whose accuracy affects not only the battery management system but can also influence the driving range estimation for an EV. In this paper, a simulation-based hybrid technique is presented, that combines both adaptive extended Kalman filter (AEKF) and artificial neural network (ANN) for SOC estimation of lithium-ion battery. The proposed hybrid technique is validated using five different EV driving cycles, that is, LA92, US06, urban dynamometer driving schedule (UDDS), highway fuel economy test (HWFET) and a mixed driving cycle at four different temperature values, that is, 0°C, 10°C, 25°C and 40°C. To facilitate the potential EV users, a real-time SOC estimator is also implemented. The real-time SOC estimated through open circuit voltage method and Coulomb counting method is further used for reservation of a charging slot in a nearby charging station. Moreover, to monitor the charging status of a potential EV from a remote location, a cloud-based Internet of things (IoT) platform, that is, ThingSpeak, is used. This results into the reduction of waiting time for an EV user at a charging station. In addition to this, a comparative analysis is carried out between proposed hybrid method and existing methods. It is demonstrated that our hybrid technique achieves lower root mean square error and higher accuracy as compared to existing methods at different operating conditions.

Optimisation of electron spin qubits in electrically driven multi-donor quantum dots

Multi-donor quantum dots have been at the forefront of recent progress in Si-based quantum computation. Among them, 2P: 1P spin qubits have a built-in dipole moment, making them ideal for electron dipole spin resonance (EDSR) using the donor hyperfine interaction, and thus all-electrical spin operation. We report fast EDSR, with Tπ ~ 10 − 50 ns and a Rabi ratio (T1/Tπ) ~ 106. The fastest EDSR time Tπ occurs when the 2P: 1P axis is ∥ [111], while the best Rabi ratio occurs when it is ∥ [100]. Sensitivity to random telegraph noise due to nearby charge defects depends strongly on the location of the nearby defects. The qubit is robust against 1/f noise provided it is operated away from the charge anti-crossing. Entanglement via exchange is several orders of magnitude faster than dipole-dipole coupling. These findings pave the way towards fast, low-power, coherent and scalable donor dot-based quantum computing.