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In-sensor computing with halide perovskite-based optoelectronic reservoir networks
Full text linkThe bigger picture
Detecting and classifying data, for example, from video cameras, is a key capability for many applications using artificial intelligence, including robotics, self-driving cars, image detection, and biometrics. However, the impressive progress in the capabilities of artificial intelligence comes at the cost of rapidly increasing energy consumption. A large contributor to this energy consumption is the transfer of data from sensors to processors in order to detect or classify the input data. In this work, we demonstrate a microscale halide perovskite semiconductor device that simultaneously senses and processes information. The information can be provided as electrical or optical input, and we show that the classification accuracy is highest if the two inputs are combined. This resembles how the brain merges information from, for example, sight and touch to gain a better understanding of the world.
Summary: Physical reservoir computing can provide efficient neuromorphic in- and near-sensor computing applications. Typically, reservoir networks are designed to process light or voltage inputs. Here, we demonstrate a multimodal optoelectronic reservoir network based on halide perovskite semiconductor devices capable of processing voltage and light inputs, which is also scalable for constructing high-density sensor arrays. The devices consist of micrometer-sized, asymmetric crossbars covered with a methylammonium lead iodide (MAPbI3) perovskite film. Using 4-bit inputs and linear readout layers for classification, we demonstrate multimodal networks capable of processing both voltage and light inputs. The networks reach mean accuracies up to 95.3% ± 0.1% and 87.8% ± 0.1% for image and video classification, respectively. The networks significantly outperformed linear classifier references by 3.1% for images and 14.6% for video. We show that longer retention times benefit classification accuracy for single-mode networks and give guidelines for choosing optimal experimental parameters.</p
Selective-Area Deposition of Indium and Its Plasmonic Properties
Full text linkWe present an effective process sequence for the deposition of indium nanostructures using molecular beam epitaxy (MBE) on a silicon substrate. Using a template structure composed of inverted pyramids and V-grooves, we deposit indium nanostructures with various dimensions. Spatially resolved cathodoluminescence spectroscopy (CL) using an electron-beam energy of 30 keV electrons shows a localized surface plasmon (LSP) resonance in spherical particles with a peak wavelength at 300 nm and a full width at half-maximum of 70 nm for the smallest particles (diameter of 85 nm), showing high optical quality of the grown indium. V-groove template structures create indium nanowires for which CL spectroscopy reveals efficient propagation of surface plasmon polaritons (SPPs), and angle-resolved CL on the periodic inverted pyramids reveals optical lattice resonances arising from the array’s periodicity. The high optical quality of these nanostructures enables further applications of plasmonic nanostructures in the ultraviolet (UV) spectral range
Toward developing a compact total artificial heart using a soft robotic fluidic transmission system
Full text linkCardiovascular diseases are a leading cause of mortality, with limited possibilities for transplantation due to a critical shortage of donor hearts. Replacing the heart with total artificial hearts (TAHs) remains challenging, due to size constraints and energy requirements, among others. To address this, we introduce the LIMO heart, a compact TAH concept based on an efficient soft fluidic transmission system. By reducing actuator volume and enhancing energy transfer, LIMO enables a more compact and efficient design. We developed a soft ventricle prototype using thin-walled pouch actuators that achieve transmission ratios above one via circumferential shrinkage. A fast, cost-effective prototyping method accelerated testing. Experimental results showed high energy transfer efficiency (82 to 91%), and in vitro tests demonstrated promising cardiac outputs of 5.9 liters per minute against aortic pressure and 7.6 liters per minute against pulmonary pressure. These findings represent a step toward a more broadly applicable biventricular soft robotic TAH for treating end-stage heart failure
Roadmap on embodying mechano-intelligence and computing in functional materials and structures
Full text linkThis is a roadmap article with multiple contributors on different aspects of embodying intelligence and computing in the mechanical domain of functional materials and structures. Overall, an IOP roadmap article is a broad, multi-author review with leaders in the field discussing the latest developments, commissioned by the editorial board. The intention here is to cover various topics of adaptive structural and material systems with mechano-intelligence in the overall roadmap, with twelve sections in total. These sections cover topics from materials to devices to systems, such as computational metamaterials, neuromorphic materials, mechanical and material logic, mechanical memory, soft matter computing, physical reservoir computing, wave-based computing, morphological computing, mechanical neural networks, plant-inspired intelligence, pneumatic logic circuits, intelligent robotics, and embodying mechano-intelligence for engineering functionalities via physical computing. In this paper, we view all the 2-page sections with equal contributions to the overall roadmap article and thus list the authorship on the front page via alphabetical order of their last names. On the other hand, for each individual section, the authors decide on their own the order of authorship. 
Reducing the MAPbI3 microstrain by fast crystallization
Full text linkControl over perovskite crystal growth, resulting in thin film morphology, has been at the very foundation of the evolution of perovskite photovoltaics (PVs). Methylammonium lead triiodide (MAPbI3) perovskite has been the workhorse material for this class of semiconductors, offering good efficiency with a relatively simple composition, which attracts industrial scale production. Despite that, instability has hampered their further exploitation. In this work, we explored the effect of different types and timing of the antisolvents on MAPbI3 perovskite crystallization. This approach enabled control of the crystalline microstrain while reducing unwanted trap density. This effect impacted device performances, enabling the achievement of MAPbI3 solar cell with power conversion efficiency (PCE) approaching 22%. Importantly, we demonstrated that an efficient MAPbI3 perovskite solar cell is also a stable one. Our solar cells showed an efficiency loss of only 10% after 900 h at 85°C, putting MA-based PSCs back among promising PV technologies
Proteome-wide determinants of co-translational chaperone binding in bacteria
Full text linkChaperones are essential to the co-translational folding of most proteins. However, the principles of co-translational chaperone interaction throughout the proteome are poorly understood, as current methods are restricted to few substrates and cannot capture nascent protein folding or chaperone binding sites, precluding a comprehensive understanding of productive and erroneous protein biosynthesis. Here, by integrating genome-wide selective ribosome profiling, single-molecule tools, and computational predictions using AlphaFold we show that the binding of the main E. coli chaperones involved in co-translational folding, Trigger Factor (TF) and DnaK correlates with "unsatisfied residues" exposed on nascent partial folds - residues that have begun to form tertiary structure but cannot yet form all native contacts due to ongoing translation. This general principle allows us to predict their co-translational binding across the proteome based on sequence only, which we verify experimentally. The results show that TF and DnaK stably bind partially folded rather than unfolded conformers. They also indicate a synergistic action of TF guiding intra-domain folding and DnaK preventing premature inter-domain contacts, and reveal robustness in the larger chaperone network (TF, DnaK, GroEL). Given the complexity of translation, folding, and chaperone functions, our predictions based on general chaperone binding rules indicate an unexpected underlying simplicity
Label-free cell imaging and tracking in 3D organoids
Full text linkFluorescence live-cell microscopy is one of the most frequently used techniques to study dynamic processes in organoids. However, it is often limited by laborious fluorescent reporter engineering, limited numbers of fluorescence channels, and adverse phototoxicity and protein overexpression effects. Label-free imaging is a promising alternative but not yet established for 3D cultures. Here, we introduce LabelFreeTracker, a label-free machine-learning-based method to visualize the nuclei and membranes in bright-field images of 3D mouse intestinal organoids. The approach uses U-Net neural networks trained on the bright-field transmitted light and fluorescence images of mouse intestinal organoids as obtained by standard confocal microscopy. LabelFreeTracker frees up fluorescence channels to study fluorescent reporters and allows (semi-)automated quantification of cell movement, cell shape and volume changes, proliferation, differentiation, and lineage trees. This method greatly simplifies live-cell imaging of tissue dynamics and will accelerate screening of patient-derived organoids, for which reporter engineering is not feasible
Magnetically and optically active edges in phosphorene nanoribbons
Full text linkNanoribbons, nanometre-wide strips of a two-dimensional material, are a unique system in condensed matter. They combine the exotic electronic structures of low-dimensional materials with an enhanced number of exposed edges, where phenomena including ultralong spin coherence times1,2, quantum confinement3 and topologically protected states4,5 can emerge. An exciting prospect for this material concept is the potential for both a tunable semiconducting electronic structure and magnetism along the nanoribbon edge, a key property for spin-based electronics such as (low-energy) non-volatile transistors6. Here we report the magnetic and semiconducting properties of phosphorene nanoribbons (PNRs). We demonstrate that at room temperature, films of PNRs show macroscopic magnetic properties arising from their edge, with internal fields of roughly 240 to 850 mT. In solution, a giant magnetic anisotropy enables the alignment of PNRs at sub-1-T fields. By leveraging this alignment effect, we discover that on photoexcitation, energy is rapidly funnelled to a state that is localized to the magnetic edge and coupled to a symmetry-forbidden edge phonon mode. Our results establish PNRs as a fascinating system for studying the interplay between magnetism and semiconducting ground states at room temperature and provide a stepping-stone towards using low-dimensional nanomaterials in quantum electronics
Nanophotonic-Enhanced Thermal Circular Dichroism for Chiral Sensing
Full text linkCircular dichroism (CD) can distinguish the handedness of the chiral molecules. However, it is typically very weak due to vanishing absorption at low molecular concentrations. Here, we suggest thermal CD (TCD) for chiral detection, leveraging the temperature difference in the chiral sample when subjected to right- and left-circularly polarized excitations. The TCD combines the enantiospecificity of CD with the higher sensitivity of thermal measurements while introducing new opportunities in the thermal domain that can be synergistically combined with optical approaches. We propose a theoretical framework to understand the TCD of individual and arrays of resonators covered by chiral molecules. To enhance the weak TCD of chiral samples, we first used individual dielectric Mie resonators and identified chirality transfer and self-heating as the underlying mechanisms giving rise to the differential temperature. However, inherent limitations imposed by the materials and geometries of such resonators make it challenging to surpass a certain level in enhancements. To overcome this, we suggest nonlocal thermal and electromagnetic interactions in the arrays. We predict that a combination of chirality transfer to Mie resonators, collective thermal effects, and optical lattice resonance could, in principle, offer more than four orders of magnitude enhancement in TCD. Our thermonanophotonic-based approach thus establishes key concepts for ultrasensitive chiral detection
Device Performance of Emerging Photovoltaic Materials (Version 6)
Full text linkThis 6th annual Emerging PV Report surveys peer-reviewed advances since August 2024 across perovskite, organic, kesterite, matildite, antimony seleno-sulfide, selenium, and tandem solar cell architectures. Updated graphs, tables, and analyses compile the best-performing devices from the emerging-pv.org database, benchmarking power conversion efficiency (PCE), flexible photovoltaic fatigue factor (F), light-utilization efficiency (LUE), and stability-test energy yield (STEY) against detailed-balance efficiency limits as functions of photovoltaic bandgap, and average visible transmittance (AVT) for (semi-)transparent devices. Beyond efficiency, operational stability is assessed via degradation rates (DR) and t95 lifetimes. Highlights include single-junction perovskite cells with efficiencies above 27%, organics surpassing 20%, and new Si/perovskite tandems exceeding 34%. Although multiple record efficiencies have been achieved this year, advances in mechanical robustness and operational stability remain inconsistent, especially in complex tandem stacks, emphasizing the urgent need for standardized protocols, improved large-area homogeneity, and database-driven benchmarks to accelerate the transition from laboratory demonstrations to scalable, real-world deployment