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Fluorescence excitation enhancement is important for biosensing; we for the first time study it quantitatively for GaP NWs.

We theoretically investigate the extractable work in single molecule unfolding-folding experiments with applied feedback. Using a simple two-state model, we obtain a description of the full work distribution, from discrete to continuous feedback. The effect of the feedback is captured by a detailed fluctuation theorem, accounting for the information aquired. We find analytical expressions for the average work extraction as well as an experimentally measurable bound thereof, which becomes tight in the continuous feedback limit. We further determine the parameters for maximal power, or rate of work extraction. While our two-state model only depends on a single, effective transition rate, we find quantitative agreement with Monte Carlo simulations of DNA hairpin unfolding-folding dynamics., Comment: 5 pages, 4 figures, 5 pages of supplementary information

Information processing by traditional, serial electronic processors consumes an ever-increasing part of the global electricity supply. An alternative, highly energy efficient, parallel computing paradigm is network-based biocomputation (NBC). In NBC a given combinatorial problem is encoded into a nanofabricated, modular network. Parallel exploration of the network by a very large number of independent molecular-motor-propelled protein filaments solves the encoded problem. Here we demonstrate a significant scale-up of this technology by solving four instances of Exact Cover, a nondeterministic polynomial time (NP) complete problem with applications in resource scheduling. The difficulty of the largest instances solved here is 128 times greater in comparison to the current state of the art for NBC.

Sensitive detection of low-abundance biomolecules is central for diagnostic applications. Semiconductor nanowires can be designed to enhance the fluorescence signal from surface-bound molecules, prospectively improving the limit of optical detection. However, to achieve the desired control of physical dimensions and material properties, one currently uses relatively expensive substrates and slow epitaxy techniques. An alternative approach is aerotaxy, a high-throughput and substrate-free production technique for high-quality semiconductor nanowires. Here, we compare the optical sensing performance of custom-grown aerotaxy-produced Ga(As)P nanowires vertically aligned on a polymer substrate to GaP nanowires batch-produced by epitaxy on GaP substrates. We find that signal enhancement by individual aerotaxy nanowires is comparable to that from epitaxy nanowires and present evidence of single-molecule detection. Platforms based on both types of nanowires show substantially higher normalized-to-blank signal intensity than planar glass surfaces, with the epitaxy platforms performing somewhat better, owing to a higher density of nanowires. With further optimization, aerotaxy nanowires thus offer a pathway to scalable, low-cost production of highly sensitive nanowire-based platforms for optical biosensing applications.

Network-based biocomputation (NBC) is an alternative, parallel computation approach that can potentially solve technologically important, combinatorial problems with much lower energy consumption than electronic processors. In NBC, a combinatorial problem is encoded into a physical, nanofabricated network. The problem is solved by biological agents (such as cytoskeletal filaments driven by molecular motors) that explore all possible pathways through the network in a massively parallel and highly energy-efficient manner. Whereas there is currently a rapid development in the size and types of problems that can be solved by NBC in proof-of-principle experiments, significant challenges still need to be overcome before NBC can be scaled up to fill a technological niche and reach an industrial level of manufacturing. Here, we provide a roadmap that identifies key scientific and technological needs. Specifically, we identify technology benchmarks that need to be reached or overcome, as well as possible solutions for how to achieve this. These include methods for large-scale production of nanoscale physical networks, for dynamically changing pathways in these networks, for encoding information onto biological agents, for single-molecule readout technology, as well as the integration of each of these approaches in large-scale production. We also introduce figures of merit that help analyze the scalability of various types of NBC networks and we use these to evaluate scenarios for major technological impact of NBC. A major milestone for NBC will be to increase parallelization to a point where the technology is able to outperform the current run time of electronic processors. If this can be achieved, NBC would offer a drastic advantage in terms of orders of magnitude lower energy consumption. In addition, the fundamentally different architecture of NBC compared to conventional electronic computers may make it more advantageous to use NBC to solve certain types of problems and instances that are easy to parallelize. To achieve these objectives, the purpose of this roadmap is to identify pre-competitive research domains, enabling cooperation between industry, institutes, and universities for sharing research and development efforts and reducing development cost and time.

Inspired by molecular motors in biology, there has been significant progress in building artificial molecular motors, using a number of quite distinct approaches. As the constructs become more sophisticated, there is also an increasing need to directly observe the motion of artificial motors at the nanoscale and to characterize their performance. Here, we review the most used methods that tackle those tasks. We aim to help experimentalists with an overview of the available tools used for different types of synthetic motors and to choose the method most suited for the size of a motor and the desired measurements, such as the generated force or distances in the moving system. Furthermore, for many envisioned applications of synthetic motors, it will be a requirement to guide and control directed motions. We therefore also provide a perspective on how motors can be observed on structures that allow for directional guidance, such as nanowires and microchannels. Thus, this Review facilitates the future research on synthetic molecular motors, where observations at a single-motor level and a detailed characterization of motion will promote applications.

Within just a couple of decades, Maxwell’s demon has gone from being one of the most fundamental and intriguing Gedankenexperiments in physics—but one that appeared impossible to imagine in practice—to being a real setup in several laboratories around the world (1). Maxwell introduced his demon in 1867 to question the validity of the second law of thermodynamics (2). He imagined a “very observant and neat-fingered being” able to monitor the velocity and position of the molecules of a gas and use this information to separate the fast from the slow ones without energy expenditure. This operation is compatible with Newton’s mechanics but appears to defeat the second law, which rules out that temperature differences can develop without energy dissipation somewhere else. The solution to this apparent failure of the second law came when analyses included the physical nature of the demon as well as the thermodynamic consequences of the measurement and the information processing needed by the demon’s actions. Nowadays, we are interested not only in reconciling the Maxwell demon and the second law but also in exploring information as a fuel or thermodynamic resource (3) in artificial microscopic devices as well as in biological motors. In PNAS, Saha et al. (4) tackle an issue that has been barely studied to date: the maximum speed that a Maxwell demon or information engine can reach and the maximum power that it can supply. Maxwell’s observation was based on his own discovery, a few years earlier, of the distribution of molecular velocities in a gas, a manifestation of the randomness of microscopic magnitudes at finite temperature. In general, an information engine consists of a device that monitors thermal fluctuations, for example, the wiggling position of individual particles, and uses this information to extract energy from a thermal bath, essentially converting heat to … [↵][1]1To whom correspondence may be addressed. Email: heiner.linke{at}ftf.lth.se. [1]: #xref-corresp-1-1

Nanowires offer remarkable opportunities for realizing new optoelectronic devices because of their unique fundamental properties. The ability to engineer nanowire heterostructures with large bandgap variations is particularly interesting for technologically important broadband photodetector applications. Here we report on infrared photodetectors based on arrays of InP nanowires with embedded InAsP quantum discs. We demonstrate a strongly reduced dark current in the detector elements by compensating the unintentional n-doping in the nominal intrinsic region of the InP nanowires by in-situ doping with Zn, a crucial step towards realizing high-performance devices. The optimized array detectors show a broad spectral sensitivity at normal incidence for wavelengths from visible to far-infrared up to 20 μm, promoted by both interband and intersubband transitions. Optical simulations show that the unexpected normal incidence response at long wavelengths is due to non-zero longitudinal modes hosted by the nanowires.

In optoelectronic devices such as solar cells and photodetectors, a portion of electron-hole pairs are generated as so called hot carriers with an excess energy that is typically lost as heat. The long standing aim to harvest this excess energy to enhance device performance has proven to be very challenging, largely due to the extremely short-lived nature of hot carriers. Efforts thus focus on increasing the hot carrier relaxation time, and on tailoring heterostructures that allow for hot-carrier extraction on short time- and length-scales. Recently, semiconductor nanowires have emerged as a promising system to achieve these aims, because they offer unique opportunities for heterostructure engineering as well as for potentially modified phononic properties that can lead to increased relaxation times. In this review we assess the current state of theory and experiments relating to hot-carrier dynamics in nanowires, with a focus on hot-carrier photovoltaics. To provide a foundation, we begin with a brief overview of the fundamental processes involved in hot-carrier relaxation, and how these can be tailored and characterized in nanowires. We then analyze the advantages offered by nanowires as a system for hot-carrier devices and review the status of proof-of-principle experiments related to hot-carrier photovoltaics. To help interpret existing experiments on photocurrent extraction in nanowires we provide modelling based on non-equilibrium Green's functions. Finally, we identify open research questions that need to be answered in order to fully evaluate the potential nanowires offer towards achieving more efficient, hot-carrier based, optoelectronic devices., This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Appl. Phys. Rev. 8, 021309 (2021), and may be found at https://doi.org/10.1063/5.0038263

Molecular motor gliding motility assays based on myosin/actin or kinesin/microtubules are of interest for nanotechnology applications ranging from cargo-trafficking in lab-on-a-chip devices to novel biocomputation strategies. Prototype systems are typically monitored by expensive and bulky fluorescence microscopy systems and the development of integrated, direct electric detection of single filaments would strongly benefit applications and scale-up. We present estimates for the viability of such a detector by calculating the electrostatic potential change generated at a carbon nanotube transistor by a motile actin filament or microtubule under realistic gliding assay conditions. We combine this with detection limits based on previous state-of-the-art experiments using carbon nanotube transistors to detect catalysis by a bound lysozyme molecule and melting of a bound short-strand DNA molecule. Our results show that detection should be possible for both actin and microtubules using existing low ionic strength buffers given good device design, e.g., by raising the transistor slightly above the guiding channel floor. We perform studies as a function of buffer ionic strength, height of the transistor above the guiding channel floor, presence/absence of the casein surface passivation layer for microtubule assays and the linear charge density of the actin filaments/microtubules. We show that detection of microtubules is a more likely prospect given their smaller height of travel above the surface, higher negative charge density and the casein passivation, and may possibly be achieved with the nanoscale transistor sitting directly on the guiding channel floor., Submitted to New Journal of Physics

Exact cover is a non-deterministic polynomial time (NP)—complete problem that is central to optimization challenges such as airline fleet planning and allocation of cloud computing resources. Solving exact cover requires the exploration of a solution space that increases exponentially with cardinality. Hence, it is time- and energy consuming to solve large instances of exact cover by serial computers. One approach to address these challenges is to utilize the inherent parallelism and high energy efficiency of biological systems in a network-based biocomputation (NBC) device. NBC is a parallel computing paradigm in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. The network is then explored in parallel using a large number of biological agents, such as molecular-motor-propelled protein filaments. The answer to the combinatorial problem can then be inferred by measuring the positions through which the agents exit the network. Here, we (i) show how exact cover can be encoded and solved in an NBC device, (ii) define a formalization that allows to prove the correctness of our approach and provides a mathematical basis for further studying NBC, and (iii) demonstrate various optimizations that significantly improve the computing performance of NBC. This work lays the ground for fabricating and scaling NBC devices to solve significantly larger combinatorial problems than have been demonstrated so far.

We consider the solution of the subset sum problem based on a parallel computer consisting of self-propelled biological agents moving in a nanostructured network that encodes the computing task in its geometry. We develop an approximate analytical method to analyze the effects of small errors in the nonideal junctions composing the computing network by using a Gaussian confidence interval approximation of the multinomial distribution. We concretely evaluate the probability distribution for error-induced paths and determine the minimal number of agents required to obtain a proper solution. We finally validate our theoretical results with exact numerical simulations of the subset sum problem for different set sizes and error probabilities, and discuss the scalability of the nonideal problem using realistic experimental error probabilities.

The high energy consumption of electronic data processors, together with physical challenges limiting their further improvement, has triggered intensive interest in alternative computation paradigms. Here we focus on network-based biocomputation (NBC), a massively parallel approach that benefits from the energy efficiency of biological agents, such as molecular motors or bacteria, and their availability in large numbers. We analyse and define the fundamental requirements that need to be fulfilled to scale up NBC computers to become a viable technology that can solve large NP-complete problem instances faster or with less energy consumption than electronic computers. Our work can serve as a guide for further efforts to contribute to elements of future NBC devices, and as the theoretical basis for a detailed NBC roadmap., Comment: 9 pages, 3 figures

Fluorescence-based detection assays play an essential role in the life sciences and medicine. To offer better detection sensitivity and lower limits of detection (LOD), there is a growing need for novel platforms with an improved readout capacity. In this context, substrates containing semiconductor nanowires may offer significant advantages, due to their proven light-emission enhancing, waveguiding properties, and increased surface area. To demonstrate and evaluate the potential of such nanowires in the context of diagnostic assays, we have in this work adopted a well-established single-chain fragment antibody-based assay, based on a protocol previously designed for biomarker detection using planar microarrays, to freestanding, SiO2-coated gallium phosphide nanowires. The assay was used for the detection of protein biomarkers in highly complex human serum at high dilution. The signal quality was quantified and compared with results obtained on conventional flat silicon and plastic substrates used in the established microarray applications. Our results show that using the nanowire-sensor platform in combination with conventional readout methods, improves the signal intensity, contrast, and signal-to-noise by more than one order of magnitude compared to flat surfaces. The results confirm the potential of lightguiding nanowires for signal enhancement and their capacity to improve the LOD of standard diagnostic assays.

Neural node components consisting of III-V nanowire devices are introduced. This allows for the construction of a small footprint specialized neural network. A broadcasting strategy is developed which removes the need for inter-node wiring. As a model system, an insect brain navigational circuit is chosen and successfully emulated using the introduced nodes and network architecture. The results are based on electronic transport simulations in each device as well as finite-difference time-domain simulations for the broadcasting of optical signals.

Nanowires bring new possibilities to the field of hot-carrier photovoltaics by providing flexibility in combining materials for band engineering and using nanophotonic effects to control light absorption. Previously, an open-circuit voltage beyond the Shockley-Queisser limit was demonstrated in hot-carrier devices based on InAs-InP-InAs nanowire heterostructures. However, in these first experiments, the location of light absorption, and therefore the precise mechanism of hot-carrier extraction, was uncontrolled. In this Letter, we combine plasmonic nanoantennas with InAs-InP-InAs nanowire devices to enhance light absorption within a subwavelength region near an InP energy barrier that serves as an energy filter. From photon-energy- and irradiance-dependent photocurrent and photovoltage measurements, we find that photocurrent generation is dominated by internal photoemission of nonthermalized hot electrons when the photoexcited electron energy is above the barrier and by photothermionic emission when the energy is below the barrier. We estimate that an internal quantum efficiency up to 0.5-1.2% is achieved. Insights from this study provide guidelines to improve internal quantum efficiencies based on nanowire heterostructures.

Molecular motors and machines are essential for all cellular processes that together enable life. Built from proteins with a wide range of properties, functionalities and performance characteristics, biological motors perform complex tasks and can transduce chemical energy into mechanical work more efficiently than human-made combustion engines. Sophisticated studies of biological protein motors have provided many structural and biophysical insights and enabled the development of models for motor function. However, from the study of highly evolved, biological motors, it remains difficult to discern detailed mechanisms, for example, about the relative role of different force generation mechanisms, or how information is communicated across a protein to achieve the necessary coordination. A promising, complementary approach to answering these questions is to build synthetic protein motors from the bottom up. Indeed, much effort has been invested in functional protein design, but so far, the "holy grail" of designing and building a functional synthetic protein motor has not been realized. Here, we review the progress made to date, and we put forward a roadmap for achieving the aim of constructing the first artificial, autonomously running protein motor. Specifically, we propose to break down the task into (i) enzymatic control of track binding, (ii) the engineering of asymmetry and (iii) the engineering of allosteric control for internal communication. We also propose specific approaches for solving each of these challenges.

Molecular junctions offer unique opportunities for controlling charge transport on the atomic scale and for studying energy conversion. For example, quantum interference effects in molecular junctions have been proposed as an avenue for highly efficient thermoelectric power conversion at room temperature. Toward this goal, we investigated the effect of quantum interference on the thermoelectric properties of molecular junctions. Specifically, we employed oligo(phenylene ethynylene) (OPE) derivatives with a para-connected central phenyl ring ( para-OPE3) and meta-connected central ring ( meta-OPE3), which both covalently bind to gold via sulfur anchoring atoms located at their ends. In agreement with predictions from ab initio modeling, our experiments on both single molecules and monolayers show that meta-OPE3 junctions, which are expected to exhibit destructive interference effects, yield a higher thermopower (with approximately 20 muV/K) compared with para-OPE3 (with approximately 10 muV/K). Our results show that quantum interference effects can indeed be employed to enhance the thermoelectric properties of molecular junctions.

Cyclical heat engines are a paradigm of classical thermodynamics, but are impractical for miniaturization because they rely on moving parts. A more recent concept is particle-exchange (PE) heat engines, which uses energy filtering to control a thermally driven particle flow between two heat reservoirs. As they do not require moving parts and can be realized in solid-state materials, they are suitable for low-power applications and miniaturization. It was predicted that PE engines could reach the same thermodynamically ideal efficiency limits as those accessible to cyclical engines, but this prediction has not been verified experimentally. Here, we demonstrate a PE heat engine based on a quantum dot (QD) embedded into a semiconductor nanowire. We directly measure the engine's steady-state electric power output and combine it with the calculated electronic heat flow to determine the electronic efficiency $\eta$. We find that at the maximum power conditions, $\eta$ is in agreement with the Curzon-Ahlborn efficiency and that the overall maximum $\eta$ is in excess of 70$\%$ of the Carnot efficiency while maintaining a finite power output. Our results demonstrate that thermoelectric power conversion can, in principle, be achieved close to the thermodynamic limits, with direct relevance for future hot-carrier photovoltaics, on-chip coolers or energy harvesters for quantum technologies.

Although zinc-blende (ZB) and wurtzite (WZ) structures differ only in the atomic stacking sequence, mixing of crystal phases can strongly affect the electronic properties, a problem particularly common to bottom up-grown nanostructures. A lack of understanding of the nature of electronic transport at crystal phase junctions thus severely limits our ability to develop functional nanowire devices. In this work we investigated electron transport in InAs nanowires with designed mixing of crystal structures, ZB/WZ/ZB, by temperature-dependent electrical measurements. The WZ inclusion gives rise to an energy barrier in the conduction band. Interpreting the experimental result in terms of thermionic emission and using a drift-diffusion model, we extracted values for the WZ/ZB band offset, 135 ± 10 meV, and interface sheet polarization charge density on the order of 10–3 C/m2. The extracted polarization charge density is 1–2 orders of magnitude smaller than previous experimental results, but in good agreement wit...

Quantum dots (QDs) are good model systems for fundamental studies of mesoscopic transport phenomena using thermoelectric effects because of their small size, electrostatically tunable properties and thermoelectric response characteristics that are very sensitive to small thermal biases. Here we provide a review of experimental studies on thermoelectric properties of single QDs realized in two-dimensional electron gases, single-walled carbon nanotubes and semiconductor nanowires. A key requirement for such experiments is to have some methods for nanoscale thermal biasing at one's disposal. We briefly review the main techniques used in the field, namely, heating of the QD contacts, side heating and top heating, and touch upon their relative advantages. The thermoelectric response of a QD as a function of gate potential has a characteristic oscillatory behavior with the same period as is observed for conductance peaks. Much of the existing literature focuses on the agreement between experiments and theory, particularly for amplitude and line-shape of the thermovoltage Vth. A general observation is that the widely used single-electron tunneling approximation for QDs has limited success in reproducing measured Vth. Landauer-type calculations are often found to describe measurement results better, despite the large electron–electron interactions in QDs. More recently, nonlinear thermoelectric effects have moved into the focus of attention, and we offer a brief overview of the experiments done so far. We conclude by discussing open questions and avenues for future work, including the role of asymmetries in tunnel- and capacitive couplings in the thermoelectric behavior of QDs.

Determining the surface concentration and diffusivity of cell-membrane-bound molecules is central to the understanding of numerous important biochemical processes taking place at cell membranes. Here we use the high aspect ratio and lightguiding properties of semiconductor nanowires (NWs) to detect the presence of single freely diffusing proteins bound to a lipid bilayer covering the NW surface. Simultaneous observation of light-emission dynamics of hundreds of individual NWs occurring on the time scale of only a few seconds is interpreted using analytical models and employed to determine both surface concentration and diffusivity of cholera toxin subunit B (CTxB) bound to GM1 gangliosides in supported lipid bilayer (SLB) at surface concentrations down to below one CTxB per μm2. In particular, a decrease in diffusivity was observed with increasing GM1 content in the SLB, suggesting increasing multivalent binding of CTxB to GM1. The lightguiding capability of the NWs makes the method compatible with conventional epifluorescence microscopy, and it is shown to work well for both photostable and photosensitive dyes. These features make the concept an interesting complement to existing techniques for studying the diffusivity of low-abundance cell-membrane-bound molecules, expanding the rapidly growing use of semiconductor NWs in various bioanalytical sensor applications and live cell studies.

Quantum dots (QDs) can serve as near perfect energy filters and are therefore of significant interest for the study of thermoelectric energy conversion close to thermodynamic efficiency limits. Indeed, recent experiments in [Nat. Nano. 13, 920 (2018)1748-338710.1038/s41565-018-0200-5] realized a QD heat engine with performance near these limits and in excellent agreement with theoretical predictions. However, these experiments also highlighted a need for more theory to help guide and understand the practical optimization of QD heat engines, in particular regarding the role of tunnel couplings on the performance at maximum power and efficiency for QDs that couple seemingly weakly to electronic reservoirs. Furthermore, these experiments also highlighted the critical role of the external load when optimizing the performance of a QD heat engine in practice. To provide further insight into the operation of these engines we use the Anderson impurity model together with a Master equation approach to perform power and efficiency calculations up to co-tunneling order. This is combined with additional thermoelectric experiments on a QD embedded in a nanowire where the power is measured using two methods. We use the measurements to present an experimental procedure for efficiently finding the external load RP which should be connected to the engine to optimize power output. Our theoretical estimates of RP show good agreement with the experimental results, and we show that second order tunneling processes and nonlinear effects have little impact close to maximum power, allowing us to derive a simple analytic expression for RP. In contrast, we find that the electron contribution to the thermoelectric efficiency is significantly reduced by second order tunneling processes, even for rather weak tunnel couplings. (Less)

Due to their high aspect ratio and increased surface-to-foot-print area, arrays of vertical semiconductor nanowires are used in numerous biological applications, such as cell transfection and biosensing. Here we focus on two specific valuable biosensing approaches that, so far, have received relatively limited attention in terms of their potential capabilities: cellular mechanosensing and lightguiding-induced enhanced fluorescence detection. Although proposed a decade ago, these two applications for using vertical nanowire arrays have only very recently achieved significant breakthroughs, both in terms of understanding their fundamental phenomena, and in the ease of their implementation. We review the status of the field in these areas and describe significant findings and potential future directions.

The surface area of a building that could potentially be used for Building Integrated Photovoltaics would increase dramatically with the availability of transparent solar cells that could replace windows. The challenge is to capture energy from outside the visible region (UV or IR) while simultaneously allowing a high-quality observation of the outside world and transmitting sufficient light in the visible region to satisfactorily illuminate the interior of the building. In this paper, we show both computationally and experimentally that InP nanowire arrays can have good transparency in the visible region and high absorption in the near-infrared region. We show experimentally that we can achieve mean transparencies in the visible region of 65% and the radiative limit of more than 10% based on measured absorption and calculated emission. Our results demonstrate that nanowire arrays hold promise as a method to achieve transparent solar cells, which would fulfill the requirements to function as windows. In addition, we show that by optical design and by designing the geometry of nanowire arrays, solar cells can be achieved that absorb/transmit at wavelengths that are not decided by the bandgap of the material and that can be tailored to specific requirements such as colorful windows.

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.

The separation of hot carriers in semiconductors is of interest for applications such as thermovoltaic photodetection and third-generation photovoltaics. Semiconductor nanowires offer several potential advantages for effective hot-carrier separation such as: a high degree of control and flexibility in heterostructure-based band engineering, increased hot-carrier temperatures compared to bulk, and a geometry well suited for local control of light absorption. Indeed, InAs nanowires with a short InP energy barrier have been observed to produce electric power under global illumination, with an open-circuit voltage exceeding the Shockley-Queisser limit. To understand this behaviour in more detail, it is necessary to establish control over the precise location of electron-hole pair-generation in the nanowire. In this work we perform electron-beam induced current measurements with high spatial resolution, and demonstrate the role of the InP barrier in extracting energetic electrons.We interprete the results in terms of hot-carrier separation, and extract estimates of the hot carriers’ mean free path.

Although conventional computer technology made a huge leap forward in the past decade, a vast number of computational problems remain inaccessible due to their inherently complex nature. One solution to deal with this computational complexity is to highly parallelize computations and to explore new technologies beyond semiconductor computers. Here, we report on initial results leading to a device employing a biological computation approach called network-based biocomputation (NBC). So far, the manufacturing process relies on conventional Electron Beam Lithography (EBL). However we show first promising results expanding EBL patterning to the third dimension by employing Two-Photon Polymerization (2PP). The nanofabricated structures rely on a combination of physical and chemical guiding of the microtubules through channels. Microtubules travelling through the network make their way through a number of different junctions. Here it is imperative that they do not take wrong turns. In order to decrease the usage of erroneous paths in the network a transition from planar 2-dimensional (mesh structure) networks to a design in which the crossing points of the mesh extend into the 3rd dimension is made. EBL is used to fabricate the 2D network structure whereas for the 3D-junctions 2PP is used. The good adaptation of the individual technologies allows for the possibility of a future combination of the two complementary approaches. (Less)

We experimentally verify hitherto untested theoretical predictions about the thermoelectric properties of Kondo correlated quantum dots (QDs). The specific conditions required for this study are obtained by using QDs epitaxially grown in nanowires, combined with a recently developed method for controlling and measuring temperature differences at the nanoscale. This makes it possible to obtain data of very high quality both below and above the Kondo temperature, and allows a quantitative comparison with theoretical predictions. Specifically, we verify that Kondo correlations can induce a polarity change of the thermoelectric current, which can be reversed either by increasing the temperature or by applying a magnetic field.