Experiments that can resolve gas flows of a few atoms per hour through micrometre-sized membranes found that monocrystalline graphene is completely impermeable to helium, the smallest atom5. Such membranes were also shown to be impermeable to all ions, including the smallest one, lithium7. By contrast, graphene was reported to be highly permeable to protons, nuclei of hydrogen atoms9. There is no consensus, however, either on the mechanism behind the unexpectedly high proton permeability14 or even on whether it requires defects in graphene’s crystal lattice17. Here, using high-resolution scanning electrochemical cell microscopy, we show that, although proton permeation through mechanically exfoliated monolayers of graphene and hexagonal boron nitride cannot be attributed to any structural defects, nanoscale non-flatness of two-dimensional membranes greatly facilitates proton transport. The spatial distribution of proton currents visualized by scanning electrochemical cell microscopy reveals marked inhomogeneities that are strongly correlated with nanoscale wrinkles and other features where strain is accumulated. Our results highlight nanoscale morphology as an important parameter enabling proton transport through two-dimensional crystals, mostly considered and modelled as flat, and indicate that strain and curvature can be used as additional degrees of freedom to control the proton permeability of two-dimensional materials.Defect-free graphene is impermeable to all atoms A study using high-resolution scanning electrochemical cell microscopy attributes proton permeation through defect-free graphene and hexagonal boron nitride to transport across areas of the structure that are under strain. Additional experiments with hydrogen’s heavier isotope deuterium revealed that the initial energy of incoming protons is not given by thermal excitations (about 25 meV) but is instead about 0.2 eV owing to zero-point oscillations of protons bound to oxygen atoms in the proton-conductive media9. This correction lifts the total energy barriers, E, posed by the crystals to about 1.0 eV and about 0.5 eV for graphene and hBN, respectively. Despite these insights, the mechanism for proton permeation through the 2D crystals remains controversial. The general consensus from density functional theory calculations is that the energy barriers should be notably larger14. The studies  have yielded a rather wide range of E but always exceeding the value of about 1 eV found experimentally. The spread of values arises from the various assumptions made in the models, such as whether the process is slower than the lattice relaxation timescale14, protons tunnel quantum mechanically12 or protons locally hydrogenate the carbon lattice  before transfer19. This uncertainty has motivated an alternative explanation widely speculated in the literature, namely that proton permeation takes place through structural defects in the crystal lattice. This hypothesis is based on experiments using graphene grown by chemical vapour deposition (CVD)17, which has grain boundaries, pinholes and other imperfections that appear during growth and transfer22. Experiments using CVD graphene typically report very high proton permeation rates and, sometimes, even the loss of graphene’s impermeability to other ions16. However, the explanation that assumes atomic-scale defects as the only proton conductive sites is inapplicable to mechanically exfoliated graphene. Indeed, transmission and tunnelling electron microscopy have failed to observe any vacancies or other atomic-scale imperfections for scans over relatively large areas of such crystals. Even more decisively, gas permeation experiments that can easily detect a single-angstrom-scale defect permeable to gases within micrometre-sized membranes5 detected none in exfoliated graphene and hBN monolayers6. Further experimental evidence is necessary to understand proton transport through defect-free 2D crystals and resolve the existing controversy.Measurements of proton transport through two-dimensional (2D) crystals demonstrated that these crystals pose an energy barrier for incoming protons of about 0.8 eV and about 0.3 eV for graphene and hexagonal boron nitride (hBN), respectivelyx) substrates (2 (see the section in the Eapp and Ebias set so as to fix Ecollector = −0.5 V at the Pt electrode (H+ collector) with respect to Ag/AgCl (see the section in the + pump) and the Nafion–Pt collector, and a current (Icollector) is detected only when the probe is at locations where H+ transmission occurs  and high current (fA) resolution using scanning electrochemical cell microscopy (SECCM). The devices for this study consisted of graphene and hBN monolayer crystals, which were suspended over micrometre-sized holes (2 μm in diameter) etched into silicon nitride  currents of about 10 fA are observed because the SiNx substrate blocks proton transport , each exhibiting a proton current17 of about 0.3–1 nA under similar Ebias. Our present SECCM measurements using higher-quality CVD graphene have not found such isolated highly conductive defects (possibly pinholes) and instead show enhanced permeation over large areas, mostly at what seems to be grain boundaries, a common feature of CVD-grown graphene20  images of the 2D crystals. Figure x aperture is covered with monolayer hBN and the other half with tetralayer  in the SECCM map is concentrated around wrinkles and the rim. However, the maps for hBN monolayers also reveal many active areas that do not correspond to any obvious morphological features. In the statistical distribution  or static (caused by strain or adsorbates), as previously revealed by transmission electron microscopy26. Although our AFM maps do show a difference in apparent roughness for monolayer and tetralayer regions in Fig. L of several nanometres26) to be quantified using our AFM. Nevertheless, direct evidence from transmission electron microscopy has previously found26 that static ripples have typical h/L ≈ 0.1, comparable to the aspect ratios observed for the wrinkles. On this basis, we propose that unavoidable nanorippling of 2D crystals enhances their proton permeability in much the same way as larger wrinkles. As nanoripples have smaller L, their smaller areas result in smaller proton currents within individual pixels. To corroborate this microscopic picture provided by SECCM, we integrated the observed currents over the entire area of the 2D membranes. This allows for an estimate of the proton conductivities of graphene and hBN monolayers as about 10 mS cm−2 and about 300 mS cm−2, respectively. Taking into account our experimental uncertainty (factor of about three that comes mostly from assessing the area contacted by the probe during the scans), the found conductivities are in good agreement with the previous measurements of average proton conductivities of the 2D crystals8.We attribute the smaller proton currents away from apparent morphological features to transport through nanoscale ripples that are ubiquitous in 2D crystals8. For example, monolayer hBN presents a sparser electron density than graphene and, accordingly, is more permeable to protons8. Strain and curvature modify the electron-density distribution within 2D materials  seem to be consistent with the experiments reporting barriers of about 1.0 eV (ref. 8). Finally, strain and curvature can be exploited to enhance proton conductivity of 2D crystals, which is of interest for various applications involving proton transport30.In conclusion, our experiments show that strain-inducing morphological features in otherwise defect-free 2D crystals are associated with enhanced proton conductivity around them. A notable example of this is graphene wrinkles that do not require any crystal-lattice defects but result in high proton currents, not dissimilar to the case of grain boundaries in CVD graphene . Our finx) using photolithography, wet etching and reactive ion etching, following the protocol previously reported8. Our devices had several apertures next to each other and were 2 μm in diameter each  to obtain ≈10-μm-thick films. The devices were annealed in a water-saturated environment at 130 °C to crosslink the polymer. The collector electrode was prepared by laminating a Pt foil  onto a cylindrical carbon block with a hot compression mounting machine (SimpliMet). The exposed Pt surface was then subjected to mechanical and electrochemical polishing. Gaskets were used to cover the carbon block and expose only the Pt surface for contact with Nafion–2D crystal devices34. For measurements, the Nafion film was hydrated with deionized water and allowed to equilibrate before placing it in contact with the Pt collector.Micrometre-sized apertures were etched into silicon-nitride-coated silicon substrates (500 nm SiN2-laser puller (Sutter Instruments P-2000). The nanopipette was then filled with 100 mM HCl electrolyte, and a silicone oil layer was added on top of the electrolyte solution in the tip to minimize evaporation during prolonged scanning procedures35. Two AgCl-coated Ag wires, fabricated by electrochemically oxidizing Ag wires (0.125 mm in diameter) in saturated KCl solution36, were used as quasi-reference counter electrodes (QRCEs). Each of the nanopipette channels was fitted with a QRCE positioned about 3–4 cm away from the tip end36.Nanopipettes for SECCM were fabricated from quartz theta capillaries with filaments . The capillary  was pulled to form a fine sharp point with a tip opening diameter of about 200 nm, using a CO37. The SECCM probe was mounted on a z piezoelectric positioner  whereas the studied graphene or hBN device was mounted on an x–y piezoelectric positioner . The SECCM probe was moved to the initial scan position using an X–Y-micropositioner  controlled with Picomotor Actuators . An optical camera provided a visual guide for the probe positioning. The microscopy stage and all positioners were enclosed in a Faraday cage with heat sinks and vacuum panels to minimize noise and thermal drift. The Faraday cage was placed on an optical tabletop with tuned damping  balanced on a high-performance laminar flow isolator .SECCM was carried out using a home-built workstationhttps://www.warwick.ac.uk/electrochemistry/wec-spm). Two home-built electrometers were used for current measurements, together with home-built eighth-order brick-wall filters with the time constant of the current amplifier set to 10 ms. Influence of acquisition parameters on the noise level is detailed elsewhere38. The current data were acquired every 4 μs, and 256 samples were averaged to give a data acquisition rate of about 1 ms.Data acquisition and instrumental control were carried out using an FPGA card (PCIe-7852R) running the Warwick Electrochemical Scanning Probe Microscopy software  traces of the reduction of protons at the bottom Pt collector electrode  (ref. 42). This potential is chosen as Ecollector = −0.5 V versus Ag/AgCl QRCE . This was the maximum voltage used in ref. 8 in which the linear-response proton transport was studied in similar devices. Ecollector drives the electrochemical proton reduction at the Pt electrode, which results in current Icollector . SECCM topographical maps of mechanically exfoliated graphene devices (not shown) were similar to those subsequently obtained by AFM, as expected. Such maps, recorded synchronously with proton transport activity, were especially valuable as they revealed morphology around proton-conducting sites in CVD graphene ) and Idc = Idc = Idc first sharply increasing and then returning to the initial value. These steps were clearly visible throughout scanning of entire samples.Extended Data Fig. Icollector . Extended Data Fig. Idc exhibits the same features both in areas of high proton conductivity (blue curve) and in areas where no proton transport takes place (red). This shows that meniscus wetting of the sample is independent of proton transport through 2D crystals. Note, however, that the magnitude of Idc does change for active and inactive areas because the Ag/AgCl electrodes are also the counter electrodes for proton conductivity measurements42. This change served as independent confirmation of those sites where there was notable proton permeation through 2D crystals.The described behaviour was observed independently of 44.Note that the above also rules out changes in the droplet cell size as the source of the observed spatial inhomogeneity of the proton currents. The consistency of the SECCM cell size across the surface is also in accord with the following considerations. First, wrinkles protrude at most a few nanometres from flat areas of graphene, which leads to only small variations in the involved surface area as compared to the area probed in each pixel (about 200 nm in diameter). Therefore, this cannot explain the orders of magnitude difference in the observed SECCM activity. Second, the roughness associated with the wrinkles is much less than a typical surface roughness of a wide range of samples previously studied by SECCM for which consistent meniscus cell size was observed or deducedk = 0.4 N m−1, resonant frequency of 70 kHz and a tip radius of 2 nm. The resulting AFM maps were used to estimate strain across different areas of the 2D membranes. From AFM traces through the membrane centre, we estimate that the membranes were globally strained by typically 0.5%. However, the strain ε was distributed not uniformly but accumulated around the aperture rim23, leading to ε several times higher than away from it23. This yields ε of a few percent around the rim. Such strain is also expected to accumulate around wrinkles in the 2D membranes, whose complex morphology cannot be attained using strain-free  deformations26. From the height (h) and base (L) of the wrinkles measured in AFM, we also estimate strain of a few percent, consistent with the above expectations.High-resolution topography and adhesion AFM imaging was carried out under ambient conditions with a Bruker Dimension Icon AFM using the PeakForce mode. The instrument was equipped with SCANASYST-AIR silicon tips (Bruker). The tips had a nominal spring constant, For scanning electron microscopy (SEM) characterization, we used a Zeiss Gemini500 scanning electron microscope, using an In-lens secondary electron detector, accelerating voltages of 0.5–2 keV and a working distance of about 2 mm.8. The images of Extended Data Fig. x substrate beyond individual apertures. These wrinkles exhibit notable proton-conducting activity in the SECCM maps that occurs not only above the Nafion region but extends onto the SiNx substrate. We attribute this observation to water that fills the space between the substrate and wrinkles and thus provides a proton-conducting medium inside the wrinkles.Extended Data Fig. 46 as well as gas permeation measurements5. None of those studies could detect any structural defects in the membranes. Nevertheless, it was important to ensure that the fabrication procedures used in the present report did not lead to accidental tears, cracks or pinholes that would break the continuity of the graphene lattice and leak protons through.Suspended membranes made from exfoliated 2D crystals have previously been characterized extensively using AFM, SEM, Raman spectroscopy, transmission electron microscopy and scanning tunnelling microscopy47, and graphene is no exception. To understand the formation of wrinkles in our devices we note that graphene sheets are initially suspended over holes, rather than supported. The membranes are therefore stretched laterally because of adhesion to the holes’ sidewalls and free to relax in the out-of-plane direction. In most cases, this results in wrinkle-free membranes2. The situation changes after depositing Nafion. Adhesion to sidewalls disappears in the presence of water (as observed in ref. 48) so that graphene is no longer stretched over the holes. The membrane therefore becomes looser, which unavoidably results in the formation of wrinkles. In addition, the now loose graphene sheets conform to the porous Nafion polymer surface, which further contributes to the wrinkling and rippling. Importantly, the wrinkles and roughness do not lead to cracks, tears or pinholes that would allow unimpeded proton permeation through them. This conclusion is supported by many experimental observations. For the sake of brevity, we describe below only three of them.The formation of wrinkles in supported thin sheets is a universal phenomenon that arises from non-uniform adhesion between the sheet and the substrate. For example, this phenomenon has been extensively studied for 2D polymers49). Our graphene monocrystals do not exhibit any discernible D peak, which allows us to put an upper bound on the atomic-scale defect density of about 109 cm−2. This translates into no more than 10 single-atom vacancies for our entire membranes of 2 μm in diameter . By contrast, the reported wrinkles are hundreds of nanometres long, and if there were any breakdown of crystallinity along them, an intense D peak would also be apparent. Occasionally, we found devices with accidental cracks formed during fabrication, and those exhibited a strong D peak. They were discarded. All of the devices reported in the manuscript had no discernible D peak  activate the so-called D peak in its Raman spectrum. The intensity of this peak increases with defect density . These experiments have found similar proton conductivity as in devices measured using Nafion. Unfortunately, we cannot remove Nafion after measurements, but we could remove electrolytes. In the latter case, the membranes did not show any D peak or any damage under AFM or SEM, which demonstrates that the membranes were not damaged during proton conductivity measurements. As the conductivity using electrolytes is the same as in the case of Nafion, we can safely conclude that Nafion does not damage graphene membranes either.The second piece of evidence that rules out lattice defects in our membranes comes from measurements using liquid electrolytes  exhibited notable helium leakage. This was measured using a He-leak detector that allowed us to resolve flows as low as 1050. To this end, the Cu foil that was covered on both sides with graphene was first exposed from one side to oxygen plasma, which removed graphene from that side. The CVD graphene remaining on the other side was then hot-pressed against the Nafion film, and the Cu foil was etched away in an ammonium persulfate solution. The resulting graphene-on-Nafion stack was left in deionized water for days to remove etchant residues. For SECCM measurements, centimetre-sized graphene-on-Nafion samples were fixed17 to the Pt electrode (as described above) and characterized using the same procedures as for micrometre-sized 2D crystals.For these measurements, centimetre-scale pieces of CVD graphene (grown on Cu) were transferred onto a Nafion N212 film as reported previously17. Statistics of the currents collected over large areas . We have also found that grain boundaries in CVD graphene were often accompanied by local corrugations .Extended Data Fig. 51. Even in the absence of gross defects , which sometimes are prevalent in CVD graphene films17, nanoscale pinholes can result in isolated hotspots with proton currents17 up to 1 nA. For higher-quality CVD graphene without such defects, proton conductivity is likely to be dominated by grain boundaries. Even in the last case, considerable variability in proton permeability is expected because of different grain sizes, depending on growth conditions, so that graphene films with smaller grains and thus higher density of grain boundaries would exhibit higher proton conductivity, in agreement with the previous report7.The experiments described in this section provide important insights into the large variability in proton permeability reported in the literature for CVD graphene films52 implemented in the Vienna ab-initio Simulation Package53 to model pseudopotentials of protons, and C and H atoms. The exchange-correlation potential was taken into account by considering the generalized gradient approximation within the Perdew–Burke–Ernzerhof form54. The weak van der Waals forces between graphene and proton were also included by using the DFT-D2 method of ref. 55. For geometry optimizations, a kinetic energy cutoff of 500 eV was used for the plane-wave basis. The convergence criterion of the total force on each atom was reduced to 10−5 eV Å−1 and the convergence criterion for the energy was set at 10−6 eV. For calculating the proton barrier, we used the proton pseudopotential from the hydrogen atom and then removed an electron from the whole system.We used the projector augmented-wave methodh , which was sufficient to prevent proton–proton interactions between neighbouring supercells. The carbon cells were isolated with a vacuum gap larger than 10 Å, which ensured the absence of edge-to-edge interactions. The ripples were modelled by fixing the out-of-plane positions of carbon atoms so that the crystal forms a Gaussian profile of height E for proton permeation is calculated by subtracting the minimum energy from the maximum one. For the case of flat unstrained graphene, the energy barrier found using these approximations is about 1.37 eV, in good agreement with the earlier theory14. As various approaches used to calculate E yield a rather large spread in the predicted values18 and the exact value of the energy barrier for flat monolayer graphene remains debatable14, here we avoid this uncertainty by focusing on relative changes in E that are arising from strain and curvature. Finally, note that E is expected to vary across membranes becoming lower around wrinkles and ripples and higher in flatter and unstrained areas. As this strain is mostly random, it is reasonable to expect that in the first approximation the distribution of E is normal . As proton currents depend exponentially on E, their distribution should then be log-normal, which is consistent with our SECCM observations.We calculated the total energy of the proton–graphene system as a function of the position of the proton in the direction perpendicular to the centre of the hexagonal ring in the graphene crystal lattice (Extended Data Fig. Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-023-06247-6.


This Topic on the “Application of Graphene-Based Materials”, which consists of a total of twenty-six articles, including two review articles, written by research groups of experts in the field, considers the most recent research and trends on the synthesis and characterization of graphene-based materials, including nanohybrids, intended for a vast array of high-demanding technological applications, namely batteries/fuel cells, aerogels, laser technology, sensors, electronic/magnetic devices, catalysts, etc.One of the reviews included in the present Topic considers the most recent research of graphene-based materials, with the authors even calling it “graphene technology”, to be used in lasers . Namely,The unique characteristics of graphene-based materials make them ideal candidates to be considered for energy storage purposes and in the high-trending market of batteries/fuel cells. Guo et al.  considerDue to its pressure-sensitive properties, graphene (and its derivatives) has found interest in the development of sensors, and, due to its highly tunable electrical conductive properties, more specifically, piezoresistive sensors. Florencio and co-workers  have preOne of the most interesting uses of graphene-based materials in the field of materials science is in the development of ultralight aerogels for different applications, from enhanced wave absorption to liquid adsorption. In this sense, Mei et al.  considerOwing to their highly interesting transport properties, namely high and tunable electrical conductivity and magnetic characteristics, graphene-based materials have generated a great deal of interest in applications where electron charge transport may be of crucial importance, as in electronics. For instance, the group of Roshchupkin  investigIn addition to their highly desirable characteristics for charge transport, graphene-based materials also display theoretically high mechanical characteristics, such as high strength, while keeping a significant flexibility. As a consequence, especially in the field of materials science, a great number of research groups have focused their interest in using graphene or its derivatives as nanoreinforcements, alone or in combination with other (nano)reinforcements, in different types of matrices, especially polymer-based. An example of this use for graphene can be seen in the work of Lim and co-workers , which c2, and reduced graphene oxide. The nanocomposite showed an extremely high level of photocatalytic activity through hydrogen production by water splitting, far exceeding that of undoped TiO2 and reduced graphene oxide, hence showing promising application as hydrogen evolution catalyst.A high interest has been dedicated to the possible use of graphene-based materials as part of a (nano)catalyst system. An example of this use is the work of Zhao and colleagues , which hAlongside all the abovementioned possibilities of graphene-based materials, there are others that, although less typical, are also being considered by researchers, presenting another example of the versatility of graphene. Teshigawara et al.  proposedOwing to its particular flat-like surface, together with its high specific area, graphene materials have been considered as interlayers in the development of several devices. An example of this can be seen in the work of Badokas and co-workers , in whicLess seen, but also considered, are the possible applications of graphene related to food. In this Topic, the study of Peng et al.  dealt wi


Impedance spectroscopy confirms that theorganic semiconductor is depleted, and the energy band diagram resultsin two electron blocking interfaces. The resulting rectifying natureof the Gr/C60 interface could be exploited in organic hot electrontransistors and vertical organic permeable-base transistors.Among the familyof 2D materials, graphene is the idealcandidateas top or interlayer electrode for hybrid van der Waals heterostructuresmade of organic thin films and 2D materials due to its high conductivityand mobility and its inherent ability of forming neat interfaces withoutdiffusing in the adjacent organic layer. Understanding the chargeinjection mechanism at graphene/organic semiconductor interfaces istherefore crucial to develop organic electronic devices. In particular,Gr/C60 interfaces are promising building blocks for future n-typevertical organic transistors exploiting graphene as tunneling baseelectrode in a two back-to-back Gr/C60 Schottky diode configuration.This work delves into the charge transport mechanism across Au/C60/Grvertical heterostructures fabricated on Si/SiO Infact, graphene is typically implemented as a gateable bottom electrodeinto barristors.12 However, more complex multilayer architectures could exploit theunique properties of graphene, i.e., optical transparency,13 flexibility,14 andthe ability to conform to three-dimensional and/or rough surfaces.15 For instance, graphene could be implementedas the base electrode in organic hot electron transistors, where ultrathinorganic layers are required, or replace the metallic base electrodein vertical organic permeable-base transistors.17 This would enable flexible vertical organic transistors operatingat high frequencies18 that are suitablefor applications such as wearable electronics with communication functions,or RF tags. Flexible vertical transistors could also be verticallyintegrated in OLEDs,16 enabling high-resolutionorganic displays with enhanced contrast. Within this framework, understandingthe charge transport mechanisms occurring at the interface betweengraphene and organic semiconductors (OSC) is crucial for the developmentof new graphene-based optoelectronic devices.20Graphene is the ideal candidate as topor interlayer electrodefor hybrid van der Waals heterostructures made of organic thin filmsand 2D materials due to its high conductivity and mobility and itsinherent ability of forming neat interfaces without diffusing in theadjacent organic layer, in contrast to commonly used metal electrodes.21 In this case, however, the graphene sheet is transferredon top of a thermally evaporated thin film of small molecules, i.e.,the n-type organic semiconductor C60, and subsequently patterned intothe top electrode. The fabrication processes combines techniques commonlyused in the semiconductor industry, and therefore it can be upscaledto wafer level. The charge injection mechanisms at the interfaces,i.e., Gr/C60 and Au/C60, are investigated by temperature-dependent I–V measurements and impedance spectroscopy.The current–voltage characteristic is modeled by the doubleSchottky barrier (DSB) model at room and high temperature (above 300K) and by Fowler–Nordheim (FN) tunneling at low temperature(below 100 K). The energy barrier height at the Gr/C60 and Au/C60interfaces is extracted from the DSB and from the FN tunneling models,while the static dielectric constant of C60 is determined by impedancespectroscopy. The study concludes with the energy band diagram ofthe heterostructure explaining the charge injection at the two interfaces.The fabrication techniques presentedin this work are similar towhat previously reported for vertical VdW heterostructures made ofthe p-type polymer P3HT and CVD grown graphene.Vertical Stacks, with diameters spanning from 5 to 50 μm and C60 film thicknessof 80 nm, and (ii) 34 Graphene Bridges to characterizethe in-plane resistance of graphene after transfer on C60. Vertical Stack, fabricated followingthe protocol reported in the Supporting Information, togetherwith the electrical scheme implemented for the measurements, whilethe schematic of the Graphene Bridge and the correspondingelectrical scheme are shown in the Supporting Information . Vertical Stack having a diameterof 10 μm. From the AFM height image one can extract the actualdiameter of the graphene electrode , while theheight profile shows the thickness of the bottom electrodes (35 nm)and of C60 (80 nm). Refer to the Supporting Information for the AFM height image of a representative Graphene Bridge device . 2 (335 nm), Ti/Au (5 nm/30 nm), and C60 (80 nm). Theresolution of the instrument does not allow to observe the grapheneelectrode on top of the stack. 2/Gr) shows the characteristic G (1582 cm–1) and 2D (2674 cm–1) peaks, as well as the D (1340cm–1) peak, with a weak amplitude, possibly resultingfrom fabrication-induced defects. The C60 film (SiO2/C60),the C60 film covered by graphene (SiO2/C60/Gr), and thefull stack (SiO2/Au/C60/Gr) Raman spectra are virtuallyidentical and display the characteristic Raman-active vibrations ofC60,22 i.e., Hg (1) at 264 cm–1, Hg (2) at 431 cm–1,Ag (1) at 492 cm–1, Hg (3)at 709 cm–1, Hg (4) at 774 cm–1, Hg (5) at 1099 cm–1, Hg (6) at 1244 cm–1, Ag (2) at 1463 cm–1, and Hg (8) at 1568 cm–1. The typical Raman scattering of Si,23 i.e., the first-order optical mode (520 cm–1)and second-order scattering band (940–980 cm–1), due to the Si substrate, is observed in all spectra. The resultsof the AFM, SEM, and Raman analysis show that the methods used tofabricate the vertical VdW devices are compatible with graphene andC60 and do not degrade these materials.This study was performed onone chip that includes two distinctgroups of devices: (i) 119 Au/C60/Gr ormation S1. Figurormation S1. Vertiormation S1. Vertiormation S1. VertiI–V characteristics measured in air and a vacuum and by studyingthe scaling relationship between the system resistance and capacitanceand the device area, where the device resistance and capacitance areobtained from impedance measurements under vacuum. Oxygen and moistureare known to affect the electrical properties of C60 and graphene.29 In particular, oxygen and moisture typically act as electron trapcenters for C60, reducing the electrical conductivity of the film,29 while they typically p-dope graphene on SiO2,26 as shown in the Supporting Information for the Graphene Bridges devices  and asdemonstrated on graphene field effect transistors . In order to desorb oxygen and water from C60 andfrom the graphene surface, and therefore ensure the consistency andreproducibility of measurements done in different systems, all measurementsare done in a vacuum after annealing . I–V traces offive devices per area measured under vacuum (∼10–6 mbar) at room temperature (293 K) after annealing for 12 h at 110°C. For the purpose of clarity, the figure does not display the I–V data in the range from −5to +5 V, where the current is below the sensitivity of the instrument.The inset of J–V tracesof all devices overlap and, thus, that the transport characteristicis not affected by the device area. The small variability between J–Vs is ascribed to the device inhomogeneitiesdue to the fabrication. After annealing, the J–V characteristics become very similar, while a larger variabilityis observed for the J–V tracestaken in air and shown in Figure S5. Interestingly,the stacks become less conductive in a vacuum after annealing , against what one would expect ifthe charge transport were bulk limited by C60 due to oxygen and moisturedesorption. This observation suggests that the transport is not bulk-limitedbut injection-limited and that the oxygen and moisture have an impacton the energetics of the interfaces. All J–Vs display the same nonlinear and asymmetric S-shaped characteristic:the current initially increases slowly with increasing voltage andthen rapidly increases at higher voltages; the same occurs for negativevoltages, but the magnitude of the current is higher. Similar trendsare typically described by various analytical models for the chargeinjection at the metal/semiconductor interface, i.e., thermionic emission(TE),30 the modified thermionic emission(MTE) developed for graphene/semiconductor interfaces,32 direct tunneling, and Fowler–Nordheim (FN) tunneling.30 However, in most cases the charge injectionat the metal/OSC follows a hybrid process,33 which includes tunneling and thermionic emission34 with deviations from the standard theory due to defects,surface inhomogeneity, and image-charge barrier lowering, resultingin a bias-dependent barrier height.35 This hybridprocess can be described by a nonideal Schottky diode model with idealityfactor n,30 where thereverse current is I = SA**T2 exp(−Φ)/kT),and where S is the contact area, T is the absolute temperature, A** is the reducedeffective Richardson constant, k is the Boltzmannconstant, and Φ = Φ0 ± (1 – 1/n)qV is the voltage-dependent energy barrierwith nominal barrier height Φ0 and ideality factor n and where q is the elementary charge.The model can be extended to a double barrier system, where differentpotential barrier heights are formed at two interfaces in series.This model is called the double Schottky barrier (DSB) model and isdescribed by35VerticalStacks of this work, IS1,2 = S1,2A**T2 exp are the reverse saturation currents, and Φ1,2 = Φ01,02 ± qV are the voltage-dependentenergy barriers at the Gr/C60 and Au/C60 interfaces, respectively.In this model, the current is limited by the reverse currents. When V > 0, the Gr/C60 diode (SB1) is forward biasedand the Au/C60 diode (SB2) is reversed biased. Therefore,the measured current is mostly given by the reverse current of SB2, i.e., IS2. On the contrary, when V < 0, the currentis limited by SB1, i.e., IS1. The DSB model is applied to the I–Vs in S1 = π(d1/2)2 for the graphene top electrode and S2 = π(d2/2)2 for the Au bottom electrode, where d1 and d2 are the diameter of thecontact area and d2 is 2 μm largerthan d1, while the reduced effective Richardsonconstant for both interfaces is set to A** = 100A m–2 K–1. It is worth observingthat A** is extracted from temperature-dependentmeasurements, and it varies in the range 101–103 A m–2 K–1 depending onthe device and voltage , as typically reportedfor metal/OSC interfaces.36 The variation of theenergy barriers extracted with different A** fromthe aforementioned range is less than 0.1 eV , and it does not affect the conclusionsof this work. Figure S9). 01,02 and ideality factors n1.2 of the Gr/C60 and Au/C60 interfaces, respectively. Thenormal distributions are given by Φ01 = 0.58 ±0.01 eV, Φ02 = 0.65 ± 0.02 eV, n1 = 1.033 ± 0.002, and n2 = 1.036 ± 0.003. The potential barrier height of the Au/C60interface is similar to previously reported value for C60 field-effecttransistors with Au electrodes.37 Impedancespectroscopy reveals that the Vertical Stacks exhibitthe typical nonideal capacitor characteristics. R and capacitance C of the Vertical Stacks obtained fromimpedance spectroscopy by fitting the modulus and phase with a nonidealcapacitor model, i.e., an R||C circuit. Refer tothe Supporting Information for detailson the fit . The resistancedepends on the applied bias, as expected from the I–V characteristics, while the capacitanceis bias-independent, therefore suggesting that the C60 is fully depleted38 and that the voltage drops linearly over thewhole structure. As a consequence, the electrostatic doping of graphene predicted by the MTE32 can be discarded, and the position of the EF of the graphene electrode is determined solely by thechemical doping of graphene. It is known that C60 adsorbed on graphenetypically results in p-doping.39 This isdemonstrated by a comparison between field-effect measurements ona set of Gr channels before and after deposition of C60 . The charge neutrality point of thegraphene field transistors shifts to positive gate biases (ca. 20V) when a thin film of C60 is deposited on top of graphene, resultingin an average p-doping of about 1.4 × 1012 cm–2 . S, where S is the area of the top electrode, whilethe capacitance scales as S  and ϵ0 is the vacuum permittivity.This value is in agreement with previous works.41 The results of the DSB analysis, supported by the impedance measurements,suggest that the vertical charge transport in the Au/C60/Gr is limitedby charge injection. Further insight into the energy barrier and chargeinjection mechanisms at the Gr/C60 and Au/C60 interfaces is obtainedby temperature-dependent measurements.The effects of the environmentand of the devicearea on the chargetransport are investigated by comparing the J–V characteristics as a function of temperature of a representative50 μm device, in linear and logarithmic scale, from 50 to 285K in steps of 5 K ; I–V characteristics for a representative 50μm device as a function of temperature, from 300 and 380 K insteps of 5 K; I–V characteristic ofa representative 50 μm in the high-temperature range between300 and 380 K. In this range, the charge injection is dominated bythermionic emission, and the DSB model can fit all I–Vs. The inset of 01, Φ02 and ideality factors n1, n2 as a function of temperature,extracted from the DSB fit for the Gr/C60 and Au/C60 interfaces, respectively.The ideality factor of both interfaces decreases with increasing temperature,indicating that the device approaches the ideal TE injection modelat higher temperatures, with values around n1 = 1.026 and n2 = 1.031. Simultaneously,the potential barrier heights decrease with temperature. This shouldnot come as a surprise, as it is known that barrier inhomogeneitycan lead to temperature-dependent energy barriers.43 Below 100 K, the J–Vs areapproximately temperature-independent and well described by the FNtunneling mechanism under the WKB (Wentzel–Kramers–Brillouin)approximation in the formula30m is the effectivemass of the electron in the semiconductor and ℏ is the reducedPlank constant. Here, the free electron mass is considered. The insetof J–V traceof a representative 50 μm device and the corresponding FN fit,while J/V2 vs 1/V plot at high bias  for 5, 10, 15, 20, 25, 30, and 50 μm representativedevices at 50 K. The J–Vsare very similar, and the energy barrier of the two interfaces canbe derived from the slope of the ln J/V2 vs 1/V plot at |V|> 8 V, resulting in Φ01 = 0.54 ± 0.07 eVandΦ02 = 0.60 ± 0.05 eV, which are similar to thoseobtained from the DSB model fit at high temperature. Refer to the Supporting Information  for the I–V traces in the range from −10to 10 V. It is worth observing that the asymmetry of the J–Vs characteristics changes from high tolow temperatures. In particular, the rectification ratio at ±9V, that is RR = |(J(+9 V)/J(−9 V)|, is ca. 1.14 at 50 K and 0.13 at 380 K.Although it is hard to explain quantitatively the phenomenon, oneshould observe that the injection mechanism changes from nonidealTE at high temperatures to FN tunneling at low temperatures, whichare described by different models with different prefactors. The latterare known to deviate significantly from theoretical values in nonidealand/or metal/OSC systems.36 A transition from FNto direct tunneling would only be possible with a thinner semiconductor.The C60 thickness for transition between FN tunneling and direct tunnelingat room temperatures can be approximated by t = ΦB/E, where E is the electricfield.30 Assuming an energy barrier of0.5 eV, which corresponds roughly to the measured value for the Gr/C60interface, and an electric field of E = 10 V/80 nm= 1.25 MV/cm, this results in a C60 thickness of ∼4 nm. Few-nanometerthin vertical stacks can be theoretically achieved using the architectureand fabrication process described in this work, where graphene isused as the top electrode. In fact, this fabrication process allowsto avoid the typical metal atoms intercalation and diffusion observedfor metal electrodes evaporated on organic films.1 The study of ultrathin stacks could provide insights intothe quantum charge transport across OSC/Gr VdW vertical heterostructures,besides potentially enabling FN tunneling at room temperature andtherefore making possible the fabrication of organic flexible memories.The latter, which exploit FN tunneling to perform the write and eraseoperations, could be developed by stacking multiple C60/Gr interfaces.Temperature-dependentelectrical measurements arenecessary todistinguish the different charge injection mechanisms contributingto the electrical current in the devices and possibly explain thenonideal thermionic emission observed at room temperature. Low- andhigh-temperature-dependent electrical measurements are done in twodifferent systems as described in the EF,Gr = ELUMO – Φ01 = −4.7 eV, whichis possibly shifted with respect to the Dirac point due to p-dopinginduced by C60 and/or to graphene defects, and (ii) the Au work functionis ca. W = ELUMO –Φ02 = −4.8 eV, as typically observed for Ausurface with organic adsorbates, due to the pillow effect and/or interfacestates, which results in an interface dipole and possibly Fermi levelpinning at the Au/OSC interface.45 It is worthobserving that because the transport is injection limited, the thermalannealing has an observable effect on the energetics of the barrier:oxygen and moisture desorption affect the surface states, and thuspossibly the Fermi level pinning, resulting in more or less conductingdevices, as evinced by the I–V characteristics before and after annealing .This work describes the field and thermalinduced charge transportmechanisms in Au/C60/Gr VdW vertical heterostructures in the 50–380K temperature range. Devices having various nominal diameters, whichrange from 5 to 50 μm, show the same electron transport characteristics.Thus, the fabrication of smaller devices is only limited by the lithographyresolution and the fabrication process presented in this work.r = 3.8. The electrical transport measurementsacross the vertical heterostructure at high temperature (above 300K) are well described by the DSB model, which gives Φ01 = 0.58 ± 0.01 eV, Φ02 = 0.65 ± 0.02 eV, n1 = 1.033 ± 0.002, and n2 = 1.036 ± 0.003 from the measurements at room temperature(293 K) at the Gr/C60 and Au/C60 interfaces, respectively. At lowtemperature (50 K), the measurements are well described by FN tunneling,which gives Φ01 = 0.54 ± 0.07 eV and Φ02 = 0.60 ± 0.05 eV for the Gr/C60 and Au/C60 interfaces.The energy barriers extracted from the two models are very similar.These findings reveal that the charge transport is injection-limitedin the temperature range from 50 to 380 K. The current is dominatedby TE at high temperature (above 200 K) and limited by FN tunnelingat low temperature (below 100 K). The charge transport at intermediatetemperature (from room temperature down to 100 K) is possibly describedby a hybrid process where thermally excited charge carriers can tunnelthrough the potential barriers into the LUMO level of C60. From theelectrical measurements, direct tunneling is predicted for thin C60layers of maximum ∼4 nm.Impedance analysis shows that C60 is fully depleted and thus thatthe voltage drops linearly over the entire structure. The static dielectricconstant of C60 extracted from the geometrical capacitance is ϵFinally, this study shows thatCVD graphene can be used as a topelectrode in C60 thin film vertical devices. The fabrication processcan potentially be applied to other multilayer hybrid van der Waalsheterostructures where the charge transport across neat Gr/OSC interfacesdefine the functionality of the devices. For instance, tunneling mechanismscould be exploited in high-frequency devices such as organic hot electrontransistors, permeable-base transistors, and organic flexible memories.48C60(99.9%) powder was purchased from Sigma-Aldrichand evaporated without further treatments. CVD graphene was grownon copper foils using an in-house automated setup and following thegrowth protocol which can be found elsewhere.2 (335nm) substrate by photolithography and under ambientconditions, as described in the Supporting Information. The chip includes two distinct groups of devices: (i) 119 Au/C60/Gr Vertical Stacks . The chip overview is given in Table S3. In both Vertical Stacks and Graphene Bridges, the C60 thin film is interposedbetween a bottom gold and a top graphene circular electrodes. In the Graphene Bridge architecture, graphene is laterally contactedin order to measure its resistance . The chip includes deviceshaving graphene electrodes of various nominal diameter, i.e., 5, 10,15, 20, 25, 30, and 50 μm, while the Au bottom electrodes are2 μm larger. In short, Au electrodes were prepatterned and depositedby e-beam physical vapor deposition (EBPVD) and lift-off. Then, theC60 thin film was thermally evaporated  and patterned by lift-off. Finally, the graphenesheet was wet transferred on the chip and patterned into the top electrodecircular shape by reactive ion etching (RIE).Devices were fabricated on a Si(525 μm)/SiO–6 mbar)in the dark, using the Keithley 4200 semiconductor parameter analyzer.The I–V characteristics ofthe Vertical Stacks were measured in the −10to +10 V voltage range, with sweep rate of ca. 1 V/s, steps of 50mV, and internal averaging of 20 ms. The Au electrode was connectedto ground. The graphene resistance was measured in GrapheneBridge devices by sweeping the voltage in the −50to +50 mV voltage range, with sweep rate of ca. 20 mV/s, steps of1 mV, and internal averaging of 20 ms.The electrical measurementswere performed under various conditions, i.e., in air, at room temperaturein the dark, and under vacuum , under vacuum (∼10–6 mbar) andin the dark. The electronics consisted of an AdWin Gold II ADC-DACand a Femto DDPCA-300 current-to-voltage converter. MATLAB scriptswere used for the data acquisition. The I–V characteristics of the Vertical Stacks were measured in the −10 to +10 V voltage range, with sweeprate of ca. 150 mV/s, steps of 10 mV, and with internal averagingof 60 ms. For the charge transport analysis, the backward and forward I–V sweeps for positive and negativebiases were considered, respectively. The full I–V sweeps (forward and backward) for representative devicesmeasured at room temperature (293 K) and at low temperature (50 K)can be found in Figure S12.The temperature-dependent –6 mbar), andthe oscillator level was set to 100 mV in the in the 40 Hz–1MHz frequency range; 201 data points were acquired. The open/shortcompensation method was applied to the measurements after the dataacquisition and following the Agilent impedance measurement handbook.49 Devices for the open/short compensation wereembedded on the chip for this scope.An Agilent4294a precision impedance analyzer was used to measurethe impedance of three representative devices per area. Python scriptswere used to control the instrument. The measurement was performedin the dark, under vacuum (∼10–1). Raman spectra were collected witha 532 nm excitation wavelength under ambient conditions. The laserpower and integration time of 0.1 mW and 120 s were set for the device,while graphene spectrum on SiO2 was acquired using a laserpower and integration time of 1 mW and 60 s.A WITec Alpha 300R confocal Ramanmicroscope was used with a LD 100× objective  and a 300 mm lens-based spectrometer  and then through ion-induceddeposition . The cross section was then cut in a 30kV gallium ion beam at an ion current of 47 nA. After cutting, thecross section was polished in sequential steps, decreasing the ioncurrent down to a minimum of 790 pA.50 for the FN modeling and for the extraction ofthe graphene resistance, (ii) lmfit51 modelfor the DSB modeling, and (iii) impedance.py52 for the impedance spectroscopy analysis.Python scripts weredeveloped for the modeling, fitting and visualization of the data.The main libraries that were implemented are (i) scipy curve_fit


E. coli BSI.Several randomized controlled trials (RCT) have shown that short-course (∼7 days) antibiotic treatment is non-inferior to longer antibiotic courses (∼14 days) in patients with uncomplicated bloodstream infection (BSI) with mostly susceptible Gram-negative bacteria. Here, we evaluate short-course therapy in ceftriaxone-resistant E. coli BSI at 14 United States hospitals between November 2020 and April 2021, each patient with ceftriaxone-R E. coli BSI, and the next consecutive patient with a ceftriaxone-S E. coli BSI was included. Patients who received 5-8 days (“short”) or 9-21 days (“long”) of antibiotics were included in this analysis. Patients who died before day 9 were excluded. Primary outcome was a Desirability of Outcome Ranking  based on disposition at day 30 after collection of the index blood culture. Ceftriaxone susceptibility was centrally determined using broth microdilution for all bacterial isolates.In a prospective cohort of 300 patients with Desirability of outcome ranking (DOOR) categoriesOf 300 patients in the original cohort, 227 were included; 44 patients  received short , and 183 patients  received long duration . Age , sex , and Charlson comorbidity index  were similar between groups. Notably, almost all patients  with solid organ or stem cell transplant were in the long duration group. The median Pitt bacteremia score was 2 (IQR 1-3) in the short duration group vs. 1 (IQR 0-3) in the long duration group (Wilcoxon Rank Sum p=0.07). DOOR outcomes were similar in both groups . Numerically more patients in the ceftriaxone-resistant group on short treatment were in category 3; 4/20 (20%) vs 5/87 (6%) in the long duration group. These 4 patients all had unsuccessful discharge combined with renal failure (n=2), and/or lack of clinical response (n=3).Desirability of outcome ranking (DOOR) analysesShown are the percentages of patients in each group with a specific DOOR category outcome.E. coli BSI. Further studies are needed to determine whether short-course therapy is appropriate for ceftriaxone-R E. coli BSI.Short duration of therapy was less frequently used than long duration of therapy in this prospective cohort of Yohei Doi, MD, PHD, bioMerieux: Advisor/Consultant|FujiFilm: Advisor/Consultant|Gilead: Advisor/Consultant|Gilead: Honoraria|GSK: Advisor/Consultant|Meiji Seika Pharma: Advisor/Consultant|Moderna: Advisor/Consultant|Moderna: Honoraria|MSD: Advisor/Consultant|MSD: Honoraria|Shionogi: Advisor/Consultant|Shionogi: Grant/Research Support|Shionogi: Honoraria Owen Albin, MD, Charles River Laboratories: Advisor/Consultant|Shionogi: Advisor/Consultant Elie Saade, MD, MPH, FIDSA, Envision Pharma: Speaker, Presenter|Johnson and Johnson: Speaker, Travel, Lodging|Protein Sciences Corp: Grant/Research Support|Sanofi Pasteur: Speaker, Travel and Lodging Loren G. Miller, MD MPH, ContraFect: Grant/Research Support|GSK: Grant/Research Support|Medline: Grant/Research Support|Merck: Grant/Research Support|Paratek: Grant/Research Support Michael J. Satlin, MD, AbbVie: IDMC member|Biomerieux: Grant/Research Support|Merck: Grant/Research Support|Shionogi: Advisor/Consultant|SNIPRBiome: Grant/Research Support Martin Krsak, MD, MSc, FASAM, AbbVie: Grant/Research Support|Melinta: Honoraria W. Charles Huskins, MD, MSc, ADMA Biologics: Advisor/Consultant|Bristol Myers Squibb: Stocks/Bonds|Pfizer: Advisor/Consultant|Pfizer: Stocks/Bonds|Zimmer Biomet: Stocks/Bonds Robin Patel, MD, Abbott Laboratories: Advisor/Consultant|Adaptive Phage Therapeutics: Grant/Research Support|Adaptive Phage Therapeutics: Mayo Clinic has a royalty-bearing know-how agreement and equity in Adaptive Phage Therapeutics.|BIOFIRE: Grant/Research Support|CARB-X: Advisor/Consultant|ContraFect: Grant/Research Support|Day Zero Diagnostics: Advisor/Consultant|HealthTrackRx: Advisor/Consultant|Mammoth Biosciences: Advisor/Consultant|Netflix: Advisor/Consultant|Oxford Nanopore Technologies: Advisor/Consultant|PhAST: Advisor/Consultant|See details: Patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic|See details: continued, patent on an anti-biofilm substance issued|TenNor Therapeutics Limited: Grant/Research Support|Torus Biosystems: Advisor/Consultant|Trellis Bioscience, Inc.: Advisor/Consultant Vance G. Fowler, MD, MHS, Amphliphi Biosciences, Integrated Biotherapeutics; C3J, Armata, Valanbio; Akagera, Aridis, Roche, Astra Zeneca: Advisor/Consultant|Genentech, Regeneron, Deep Blue, Basilea, Janssen;: Grant/Research Support|Infectious Diseases Society of America: Honoraria|MedImmune, Allergan, Pfizer, Advanced Liquid Logics, Theravance, Novartis, Merck; Medical Biosurfaces; Locus; Affinergy; Contrafect; Karius;: Grant/Research Support|Novartis, Debiopharm, Genentech, Achaogen, Affinium, Medicines Co., MedImmune, Bayer, Basilea, Affinergy, Janssen, Contrafect, Regeneron, Destiny,: Advisor/Consultant|Sepsis diagnostic: Patent pending|UpToDate: Royalties|Valanbio and ArcBio: Stock Options David van Duin, MD, PhD, Entasis: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Advisor/Consultant|Pfizer: Honoraria|Qpex: Advisor/Consultant|Roche: Advisor/Consultant|Shionogi: Advisor/Consultant|Shionogi: Grant/Research Support|Union: Advisor/Consultant|Utility: Advisor/Consultant


This paper introduces a new type of gypsum-based humidity-control material. The material combines gypsum–silica gel humidity-control material with 20% sepiolite powder activated by calcium chloride. Both experimental and simulation studies were conducted to assess its humidity-control performance. The experimental results indicate that gypsum-based humidity-control material has the property of absorbing moisture in high-humidity environments and releasing moisture in low-humidity environments. Moreover, both environmental temperature and relative humidity (RH) have an impact on the material’s humidity-control performance. At a relative humidity of 97.4%, the maximum equilibrium moisture content of the material is 0.225 g/g, which is 1.4 times that of the gypsum–silica gel humidity-control material and 4.5 times that of pure gypsum material. The simulation results indicate that gypsum-based humidity-control material effectively mitigates indoor relative humidity fluctuations and maintains indoor air relative humidity within a narrow range. Furthermore, the material has the potential to reduce building energy consumption. This is especially evident under climate conditions with large temperature and relative humidity differences between day and night, such as in Beijing, Paris, and Atlanta. The maximum potential energy-saving rate in Beijing can reach up to 19.31%. The indoor environment plays a crucial role in determining individuals’ physical and mental well-being, a relationship that is primarily affected by indoor environmental parameters ,2,3. RelAs a passive energy-saving technology for regulating indoor humidity, humidity-control materials stand out among numerous passive technologies. The concept of humidity-control materials was initially proposed by Nishito and Miyano in Japan in the 1940s . It refeIn recent years, the utilization of humidity-control materials for regulating indoor relative humidity has yielded promising results ,14,15. ZCurrently, various types of humidity-control materials have been developed and classified as biomass, organic, inorganic, and composite materials . BiomassTo enhance the humidity-control performance of gypsum, numerous researchers have chosen gypsum as the matrix and incorporated other materials to develop gypsum-based composite materials ,27. JianIn conclusion, gypsum is a traditional building material with humidity-control properties, but it has limitations in terms of moisture absorption and desorption performance. The current focus of research lies on composite humidity-control materials ,33, but The study used gypsum material and calcium chloride from Sinopharm Chemical Reagent Co., Ltd., Shanghai, China. Silica gel was obtained from Henan Pubang Environmental Protection Materials Co., Ltd., Henan, China. Sepiolite powder was provided by Aladdin Biochemical Technology Co., Ltd., Shanghai, China. The preparation process of gypsum-based humidity-control material is described as follows.The sepiolite powder was placed in an air-drying oven  to dry at a temperature of 90 °C until the change in weight did not exceed 0.1% over three consecutive days. Subsequently, a 3 mol/L calcium chloride solution was formulated and blended with the dried sepiolite powder at a mass ratio of 8:2 with the aid of an electronic balance . The mixture was subsequently homogenized using a glass rod until it attained a dry and friable consistency to obtain sepiolite power activated by calcium chloride.Firstly, the silica gel was crushed using a crusher  and sieved through a mesh to obtain 3 mm particle-size silica gel. Then, gypsum and silica gel were separately weighed in a mass ratio of 6:4 using an electronic balance . After thoroughly mixing the materials in a beaker, the desired amount of distilled water was added and stirred well. Finally, the well-mixed composite slurry was poured into a precast mold with dimensions of 50 × 50 × 5 mm and allowed to solidify. It was then cured for 24 h at a temperature of 50 ± 2 °C and a relative humidity of 40 ± 5%. This resulted in the formation of the gypsum–silica gel humidity-control material. The detailed preparation procedure can be found in reference .The uncured gypsum–silica gel humidity-control material slurry was mixed with activated sepiolite powder in a mass ratio of 8:2. The mixture was poured into a beaker and the desired amount of distilled water was added, then stirred thoroughly to achieve uniformity. The well-mixed composite slurry was poured into a precast mold with dimensions of 50 × 50 × 5 mm and allowed to solidify. It was then cured for 24 h at a temperature of 50 ± 2 °C and a relative humidity of 40 ± 5%. This resulted in the formation of the gypsum-based humidity-control material.The raw materials used in the sample preparation process, as well as the samples employed during the experimental procedure, are illustrated in The material composition parameters are shown in Humidity-control performanceTo test the humidity-control performance of the gypsum-based humidity-control material, two experimental schemes were designed. First, the gypsum-based humidity-control material was used to dehumidify and humidify high-humidity (85%) and low-humidity (25%) environments consecutively. This continuous humidity-control test was repeated three times. Second, the gypsum-based humidity-control material was used to dehumidify the high-humidity environment (85%) and immediately humidify the low-humidity environment (25%). This intermittent humidity-control test was repeated three times.The experimental setup design schematic diagram illustrated in 2.The impact of the environment on humidity-control performanceTo test the effect of environmental temperature on the humidity-control performance of gypsum-based humidity-control material, the programmable temp&humi chamber  was utilized. A constant relative humidity of 80% and 20%, respectively, was maintained for the experiment. The materials were placed in an air-drying oven to dry at a temperature of 80 °C until the change in weight did not exceed 0.1% over three consecutive days. The dry materials were placed in the chamber with a constant relative humidity of 80% to absorb moisture. In contrast, the materials that had reached the maximum equilibrium moisture absorption at a relative humidity of 97.4% were placed in the chamber with a constant relative humidity of 20% to desorb moisture. The chamber was set to 13 °C, 23 °C, and 33 °C, respectively.To test the effect of environmental relative humidity on the humidity-control performance of gypsum-based humidity-control material, the internal temperature of the programmable temp&humi chamber was kept at 23 °C. The dry materials were placed in the chamber to absorb moisture, and the relative humidity inside the chamber was controlled at a constant level of 50%, 60%, 70%, and 80%, respectively. The materials that had reached the maximum equilibrium moisture absorption at a relative humidity of 97.4% were placed in the chamber to desorb moisture. Inside the chamber, the relative humidity was controlled at constant levels of 20%, 30%, 40%, and 50%, respectively.3.Isothermal moisture adsorption–desorption curveIn accordance with the Chinese standard GB/T 20312-2006 , the iso0 is the dry mass of material (g), m is the mass of the material at moisture equilibrium (g).The equilibrium moisture content u during the process of moisture adsorption and desorption of the above material can be calculated using Formula (1),1 is the moisture content of the material after adsorption or before desorption (g/g), u2 is the moisture content of the material before adsorption or after desorption (g/g).The moisture content U during the process of moisture adsorption and desorption of the above material can be calculated using Formula (2),The actual image showcasing the experimental process of using the programmable temp&humi chamber is illustrated in To test the humidity-control effect of gypsum-based humidity-control material applied in the building, EnergyPlus software (EnergyPlus 9.6.0) was used. The study focused on investigating the impact of material thickness and material laying area on the indoor air parameter changes in a room under summer climate conditions in Xiamen. The simulation period spanned from 1 August to 7 August.To test the energy-saving effect of gypsum-based humidity-control material applied in buildings, EnergyPlus software was used. The study focused on investigating the impact of the laying and non-laying of material on building energy consumption under various climatic conditions. Four cities worldwide characterized by typical urban climates were selected for analysis. These cities include Beijing, China , Paris, France (temperate oceanic climate), Atlanta, United States , and Xiamen, China .For accurate and typical results, the BESTEST base case building shown in  from theThe detailed physical property parameters of each layer in the BESTEST base case building are presented in The simulation settings and boundary conditions are shown in 2 . Case B studied the impact of gypsum-based humidity-control material laying area on its regulating humidity effectiveness. The material laying area was 63.6 m2  and 159.6 m2 , and the material thickness was 0.03 m. Finally, Case C acted as the reference group where no gypsum-based humidity-control material was applied in the room.The results of the continuous dehumidification and humidification tests of the gypsum-based humidity-control material are shown in The results of the intermittent dehumidification and humidification tests of the gypsum-based humidity-control material are shown in To evaluate and compare the humidity-control performance of pure gypsum, gypsum–silica gel humidity-control material, and gypsum-based humidity-control material, an isothermal moisture absorption and desorption test was conducted. The ExpDec1 model in Origin software (Origin 2017) was used to fit the isothermal equilibrium moisture content curve, the formula is as follows,After conducting a simulated study on the impact of different thicknesses of materials laid on the interior of rooms under Xiamen’s summer climate conditions. These results are illustrated in 2, which is significantly better than the energy consumption of 0.01 m and 0.02 m. Compared with laying thicknesses of 0.01 m and 0.02 m, energy efficiency has been improved by 7.25% and 3.17%, respectively. Considering economic factors, we choose 0.03 m as the laying thickness for subsequent simulations.Based on the simulation results, the optimal thickness value of the material cannot be determined solely by changes in indoor air parameters. However, a specific thickness value needs to be determined in subsequent simulations. 2 area, the room with a 159.6 m2 area exhibits a smaller amplitude of moisture content fluctuation.Then, a simulated study was conducted on the impact of different areas of materials laid on the interior of rooms on the indoor air parameters under Xiamen’s summer climate conditions. These results are illustrated in Through the analysis of experimental results, it was found that intermittent dehumidification and humidification have shown more beneficial long-term performance for the material compared to continuous dehumidification and humidification. Moreover, although high temperature can promote the desorption process of gypsum-based humidity-control material, its desorption capacity is still limited under continuously high-humidity conditions. In contrast to temperature, relative humidity has a more significant impact on the material’s humidity-control performance.The simulation results also confirmed the findings. In climates characterized by sustained high temperature and humidity, such as Xiamen, outdoor high temperature increases the accumulated heat load on the material. Additionally, outdoor high humidity hinders the desorption process, resulting in suboptimal discharge of internal moisture. Conversely, in regions with greater fluctuations in temperature and relative humidity throughout the year, such as Beijing, Paris, and Atlanta, the material exhibits excellent energy-saving performance.To better elucidate this finding, Xiamen was taken as an example to categorize the impact of gypsum-based humidity-control material on annual building energy consumption according to the seasons: spring, summer, autumn, and winter. The results are presented in To improve the humidity-control performance of traditional building materials and augment their efficacy in regulating indoor relative humidity, this study incorporated sepiolite powder activated by calcium chloride into gypsum–silica gel humidity-control material to prepare a new type of gypsum-based humidity-control material. Through experimental and simulation studies, the following main conclusions were drawn:(1) Gypsum-based humidity-control material exhibits the ability to absorb moisture in high-humidity environments and desorb moisture in low-humidity environments. However, the material’s humidity-control capacity decreases over time during continuous dehumidification or humidification. Therefore, intermittent dehumidification and humidification are more conducive to maintaining relative humidity stability for extended periods of time.(2) The moisture absorption content of the gypsum-based humidity-control material is minimally influenced by changes in environmental temperatures, while its moisture desorption content is noticeably affected. On the other hand, variations in relative humidity impact both the moisture adsorption and desorption content of the material. The larger the discrepancy between environmental relative humidity and the internal moisture content of the material, the greater the effectiveness of the material’s humidity-control performance.(3) Addition of calcium-chloride-activated sepiolite powder significantly enhances the adsorption and desorption abilities of the gypsum–silica gel humidity-control material. At a relative humidity of 97.4%, the equilibrium moisture content of the gypsum-based humidity-control material can reach a maximum of 0.225 g/g. It is 1.4 times higher than that of gypsum–silica gel material, and 4.5 times than that of pure gypsum materials.(4) Gypsum-based humidity-control material can mitigate the influence of exterior and interior humidity loads on indoor relative humidity. The material can reduce fluctuations in indoor relative humidity and maintain it within a narrow range, providing a more stable indoor environment.(5) Gypsum-based humidity-control material has the potential to reduce building energy consumption. Simulation results show that compared with regions with high temperatures and high humidity throughout the year, this material is more suitable for areas with large diurnal temperature differences and differences in relative humidity.The uniqueness of this study lies in the successful preparation of a novel gypsum-based humidity-control material. It provides a new approach for low-cost and practical humidity-control building materials in the field of architecture. However, there are still several limitations to be considered. This study explores the practical application of gypsum-based humidity-control materials through simulation research methods. Further work requires long-term monitoring and analysis in actual architectural environments to evaluate their actual moisture regulation performance. Additionally, during the preparation process of gypsum-based composite materials, the silica gel and activated sepiolite powder as additives significantly enhance the moisture absorption and desorption properties of the materials. However, considering that silica gel itself belongs to a “strong absorption and weak desorption” material, it leads to relatively poor desorption performance of gypsum-based materials. The next focus of research will concentrate on exploring modification methods to improve the moisture desorption performance of the materials. Simultaneously, it aims to achieve cost reduction objectives and ensure meet energy-saving requirements in continuous high-temperature and high-humidity environments.


This study was performed on a population of 300 graphene field effect transistors. The output characteristic of the transistors revealed that a C60 thin film adsorbate increased the graphene hole density by (1.65 ± 0.36) × 1012 cm−2, whereas a Pentacene thin film increased the graphene electron density by (0.55 ± 0.54) × 1012 cm−2. Hence, C60 induced a graphene Fermi energy downshift of about 100 meV, while Pentacene induced a Fermi energy upshift of about 120 meV. In both cases, the increase in charge carriers was accompanied by a reduced charge mobility, which resulted in a larger graphene sheet resistance of about 3 kΩ at the Dirac point. Interestingly, the contact resistance, which varied in the range 200 Ω–1 kΩ, was not significantly affected by the deposition of the organic molecules.Graphene is an excellent 2D material for vertical organic transistors electrodes due to its weak electrostatic screening and field-tunable work function, in addition to its high conductivity, flexibility and optical transparency. Nevertheless, the interaction between graphene and other carbon-based materials, including small organic molecules, can affect the graphene electrical properties and therefore, the device performances. This work investigates the effects of thermally evaporated C60 ( In fact, the van der Waals interactions of carbon materials, including small organic molecules, e.g., C60-Fullerene and Pentacene, have an important influence on the electrical properties of graphene and therefore, on the device performances. While the growth mechanisms and orientation of C60 and Pentacene molecules on graphene have been widely studied [Hybrid van der Waals heterostructures made of Graphene (Gr) and Organic Semiconductors (OSC) are being widely investigated for their potential applications in sensors ,2, solar studied ,15,16,17n- and p-type organic semiconductors [This work investigates the effect of C60 and Pentacene adsorbates on the electrical properties of large-area graphene grown by Chemical Vapor Deposition (CVD). C60 and Pentacene molecules are commonly used as nductors ,19,20 thW of 5 μm and five different channel lengths L of 5, 10, 20, 50 and 100 μm. The two sets include 30 GFETs per channel length and were fabricated on two separate chips (3). The remaining graphene sheet was transferred on the pre-patterned Ti/Au electrodes (5 nm/50 nm) on a Si/SiO2 (525 μm/300 nm) substrate and patterned into geometrically defined channels by e-beam lithography. Then, the molecules were thermally evaporated, without using any physical mask nor photolithographic patterning, resulting in a uniform coverage of the whole chip. L = 50 μm and W = 5 μm. The output and transfer characteristics of the GFETs were measured in vacuum before and after depositing the molecules, after 24 h of vacuum exposure to assure complete desorption of the moisture and water. 2O and/or resist residues [This study was performed on two sets of 150 Graphene Field Effect Transistors (GFETs) with a fixed channel width te chips . The detresidues ,27,28,292 substrates were about 10 nm and 5 nm, as shown in the 2 and graphene. The AFM profile of 2 and graphene, as was previously reported [2 [2 and on the graphene channel. The presence of the graphene channel under the organic thin films was further confirmed using Raman spectroscopy. 2 substrate) showed the characteristic G (1587 cm−1) and 2D (2681 cm−1) peaks, as well as the D (1340 cm−1) peak [−1) and second-order scattering band (940–980 cm−1) of the Si substrate [1g at 264 cm−1, H2g at 430 cm−1, A1g at 491 cm−1, H3g at 707 cm−1, H4g at 772 cm−1, H5g at 1099 cm−1, H6g at 1242 cm−1, A2g at 1462 cm−1 and H8g at 1568 cm−1, as well as the characteristic Raman peaks of CVD graphene (G at 1587 cm−1 and 2D at 2681 cm−1) observed before the deposition of C60. −1 were assigned to the Ag bands, while the peak at 1595 cm−1 was assigned to the B3g band. The 2D peak (2687 cm−1) of the CVD graphene could be clearly distinguished, whereas the G peak overlapped with the B3g band of Pentacene. The AFM surface morphology combined with Raman chemical analysis confirmed the presence of the geometrically well-defined Gr/C60 and Gr/Pentacene hybrid heterostructures.reported . The avereported . The disreported . Here, treported ). The AForted [2 , whereasorted [2 ,16. Figu−1) peak , with a s the D 10 cm−1 peubstrate , i.e., HDSI vs. GSV) of pristine GFETs and coated GFETs measured under vacuum and at room temperature. The standard deviations are indicated by the shaded areas. Refer to the Experimental Methods section for details on the data filtering and population selection process and to the DSI vs. DSV) and transfer characteristic (DSI vs. GSV) of graphene field effect transistors [GSV range  × 1012 cm−2, against the residual doping of pristine graphene with n0 = (0.20 ± 0.65) × 1012 cm−2 (Chip 1). For the Pentacene molecules, the graphene was electron-doped with an electron density of n0 = (0.55 ± 0.54) × 1012 cm−2, against the residual hole doping of graphene before the deposition with n0 = (0.09 ± 0.48) × 1012 cm−2 (Chip 2). Such a charge transfer could not be anticipated a priori from the HOMO and LUMO energy levels of the individual molecules relative to the graphene Fermi level only, as illustrated for C60 and Pentacene in DSI vs. GSV traces. n0 was accompanied by a decrease, from n0 which was accompanied by a decrease, from GSV range.nsistors . The traGS range , while ang level ,25,26,27acitance ,38, is ge ϵr=3.9  and t=30graphene , i.e., Δurements . The fiety reads ,(2)μ=LgDS=50 mV . The holSR increased by about 200 Ω and shifted to a more positive CR shifted with SR and remained close to the Dirac point, suggesting that the charge carrier injection mechanism at the Au/Gr interface was not significantly affected by the molecules. Assuming that the charge injection mostly occurred at the edge between the metal electrodes and Gr (W = 5 μm), the gate dependent contact resistivity n- and p-type organic semiconductors [ne GFETs a,b showegraphene ,45, weregraphene . On the mobility , assuminon model ,13. Thisnductors ,10,11,1212 cm−2, whereas the deposition of Pentacene results in an increased residual graphene electron density of (0.55 ± 0.54) × 1012 cm−2. In both cases, the increase in the residual charge carriers was accompanied by a reduced charge mobility, possibly due to an increased charge-impurity scattering in graphene. The Fermi energy of graphene shifted to (−150 ± 15) meV after the deposition of C60, and it shifted to (+86 ± 35) meV after the deposition of Pentacene, while the charge carrier injection at the Au/Gr did not seem to be significantly affected. Overall, this work provides useful insight into the graphene in-plane charge transport and on the energetic of the Gr/C60 and Gr/Pentacene hybrid heterostructures, which could be exploited in more complex organic electronic devices. For instance, the energy barriers forming at the Gr/C60 and Gr/Pentacene interfaces and the weak electrostatic screening of graphene could be beneficial for forming n- and p-type channels in graphene-based vertical organic transistors.In summary, CVD graphene field effect transistors (GFETs) with a fixed channel width (5 µm) and different channel lengths  were fabricated and electrically characterized under vacuum. Subsequently, thin films of C60 and Pentacene were deposited on two distinct GFET chips by thermal evaporation and electrically characterized again under vacuum. The GFETs’ transfer characteristic revealed that the deposition of C60 on graphene results in an increased residual graphene hole density of (1.65 ± 0.36) × 102. Then, the foils were placed in Acetic Acid (CH3COOH) for 30 min, rinsed in de-ionized water (DIW) and Ethanol and dried with N2. The cleaned foils were pre-annealed at 1000 °C for 1 h in a H2 (20 sccm) and Ar (200 sccm) atmosphere in the CVD oven (approximately 1 mbar). Then, graphene grew for 35 min in a CH4 (0.05 sccm), H2 (20 sccm) and Ar (200 sccm) atmosphere under a pressure of about 120 mbar. After the CH4 flow was stopped, the CVD oven was left to cool down to room temperature (at approximately 1 mbar).Graphene was grown in-house by chemical vapor deposition (CVD) on copper foils  with a fully automated setup. The foils were ultrasonicated in Acetone, rinsed with Isopropyl Alcohol (IPA) and dried with N2 flow (30 sccm) for 2 min. The Cu substrate was etched away in a Ferric Chloride  bath for 1 h, and then transferred to de-ionized water (DIW). Subsequently, the remaining graphene/PMMA sheet was placed in hydrochloric acid (HCl 10%) for 5 min and transferred back to DIW. Finally, graphene could be transferred onto the target substrate and dried overnight in vacuum oven .The CVD graphene was transferred as previously reported ,46. To p2 (300 nm) substrates. The Au bottom contacts architecture . The remaining PMMA, protecting the graphene channels, was removed in Acetone (55 °C) for 1 h and IPA (55 °C) for 1 h.Two chips including 150 Graphene Field Effect Transistors (GFETs) were fabricated. Graphene sheets grown by CVD on Cu foils were transferred onto photolithography pre-patterned Ti (5 nm)/Au (50 nm) electrodes on Si (525 μm)/SiOitecture b was cho−6 mbar) without further treatments. The C60 thin film was deposited by thermal evaporation at about 0.2 Å/s from a molybdenum evaporation boat (Umicore). The Pentacene thin film was thermally evaporated at about 0.05 Å/s using a low-temperature-controlled source (about 120 °C) with an Al2O3 crucible (Creaphys). The evaporation rate was maintained by monitoring the quartz crystal microbalance of the evaporator. The temperature of the target substrate was not actively controlled during the evaporation.Fullerene-C60  powder was purchased from Sigma-Aldrich , while Pentacene powder  was purchased from Tokyo Chemical Industry . The two types of molecules were thermally evaporated under vacuum (approximately 10−6 mbar) and at room temperature. The samples were shortly exposed to ambient conditions during the transport from the evaporation chamber to the electrical prober vacuum chamber. They were kept in vacuum conditions (approximately 10−6 mbar) for at least 24 h before being characterized. The electronics comprised an AdWin Gold II ADC-DAC unit, a low-noise current-to-voltage converter  to measure the drain-to-source current (DSI), and a high-voltage amplifier  to provide the gate-to-source voltage (GSV). The drain-to-source voltage (DSV) was directly provided by the ADC-DAC. The automated probe station and the ADC-DAC were controlled via LabVIEW and Matlab scripts. In the drain-to-source voltage (DSV) sweep from −50 mV to +50 mV, the voltage step was set to 0.5 mV, the sweep rate to 50 mV/s and the gate-to-source voltage was set to 0 V. In the gate-to-source voltage (GSV) sweep from −50 V to +50 V, the voltage step was set to 0.1 V, the sweep rate to 10 V/s and the drain-to-source voltage (DSV) was set to 50 mV. The internal averaging was set to 20 ms for all the measurements. Only the backward sweep traces were considered for the analysis, refer to the The devices were electrically characterized under vacuum  in tapping mode. The AFM was equipped with a TESPA-V2 cantilever with a tip apex radius of 7 nm, with a resonant frequency of 320 kHz and a spring constant of 37 N/m. The AFM data were processed with Gwyddion (version 2.56) which was used to extract the single and average height profiles and export the images.−1) equipped with a TE-cooled charge-coupled device . One Raman spectrum for each device was collected (150 devices per chip). The laser power was set to 0.1 mW and 0.5 mW for the Gr/C60 and Gr/Pentacene heterostructures, respectively. In both cases, the integration time was set to 30 s. The average Raman spectra of graphene, Gr/C60 and Gr/Pentacene were obtained using all the Raman spectra acquired on each set of devices. Refer to Raman spectra were acquired in ambient conditions using a 532 nm excitation wavelength with a WITec Alpha 300R confocal Raman microscope mounting an 100× objective  and a 300 mm lens-based spectrometer (grating: 600 g mmL. The weights were set to Python scripts were used for the data selection, analysis and visualization. Raman spectra averaging and polynomial background subtraction was done using numpy . The resng scipy . The RC dent TLM .


ImportanceChat Generative Pre-Trained Transformer (ChatGPT) has shown promising performance in various fields, including medicine, business, and law, but its accuracy in specialty-specific medical questions, particularly in ophthalmology, is still uncertain.PurposeThis study evaluates the performance of two ChatGPT models (GPT-3.5 and GPT-4) and human professionals in answering ophthalmology questions from the StatPearls question bank, assessing their outcomes, and providing insights into the integration of artificial intelligence (AI) technology in ophthalmology.MethodsChatGPT's performance was evaluated using 467 ophthalmology questions from the StatPearls question bank. These questions were stratified into 11 subcategories, four difficulty levels, and three generalized anatomical categories. The answer accuracy of GPT-3.5, GPT-4, and human participants was assessed. Statistical analysis was conducted via the Kolmogorov-Smirnov test for normality, one-way analysis of variance (ANOVA) for the statistical significance of GPT-3 versus GPT-4 versus human performance, and repeated unpaired two-sample t-tests to compare the means of two groups.ResultsGPT-4 outperformed both GPT-3.5 and human professionals on ophthalmology StatPearls questions, except in the "Lens and Cataract" category. The performance differences were statistically significant overall, with GPT-4 achieving higher accuracy (73.2%) compared to GPT-3.5  and humans . There were variations in performance across difficulty levels (rated one to four), but GPT-4 consistently performed better than both GPT-3.5 and humans on level-two, -three, and -four questions. On questions of level-four difficulty, human performance significantly exceeded that of GPT-3.5 (p = 0.008).ConclusionThe study's findings demonstrate GPT-4's significant performance improvements over GPT-3.5 and human professionals on StatPearls ophthalmology questions. Our results highlight the potential of advanced conversational AI systems to be utilized as important tools in the education and practice of medicine. Chat Generative Pre-Trained Transformer (ChatGPT) is a natural language processing model that was developed by OpenAI and released in November 2022 . It has In the field of ophthalmology, artificial intelligence (AI) models like ChatGPT can play a crucial role in answering patient-specific management questions, providing quick insights on relevant criteria, and facilitating discussions on ocular conditions, treatments, and procedures. However, despite its success in the overall fields of medicine, business, and law, ChatGPT has been shown to have variable accuracy in answering specialty-specific medical questions ,6.OpenAI has developed two prominent iterations of the ChatGPT model, namely GPT-3.5 and GPT-4. The latest version, GPT-4, boasts improved efficiency and accuracy compared to its predecessor. Notable advancements include enhanced contextual understanding, improved language fluency, and an expanded knowledge base . HoweverThis study aims to evaluate the performance of GPT-4, GPT-3.5, and human professionals in answering ophthalmology questions sourced from the StatPearls question bank, a resource that provides practice questions commonly used by residents, fellows, and attendings to prepare for board exams and clinical practice . The prihttps://www.ncbi.nlm.nih.gov/books/NBK430685/). “Ophthalmology” was used as a search criterion to filter relevant StatPearls questions. The search yielded 548 entries or 1,096 questions. The results were sorted in alphabetical order and a random number generator was used to select each entry. The question was omitted if it was not directly relevant to ophthalmology. The questions were then pasted into ChatGPT, preceded by the statement, “Please choose the best answer and explain your reasoning:”ChatGPT's performance was evaluated utilizing StatPearls ophthalmology questions, which are peer-reviewed questions from a medical question bank designed to be at the level of ophthalmology residents, fellows, and attendings. Free StatPearls questions were accessed via the National Library of Medicine bookshelf  Exam Content Outline was referenced when creating ophthalmology subcategories in which to organize the questions . The queChatGPT responses were organized by GPT model, question difficulty on a scale of 1 to 4, ophthalmology subcategory, and generalized anatomical category. Performance of GPT-3.5, GPT-4, and humans in answering ophthalmology practice questions was measured as the proportion of correct answers. Our secondary outcomes were the proportion of questions GPT-3.5, GPT-4, and humans were able to answer correctly within different difficulty levels.The study demonstrated a power of 0.80. Each of the three groups underwent a set of 467 questions, resulting in a sample size of 1,401. The effect size of 0.083, calculated using the G*Power software , was employed as a parameter in the analysis.Statistical analysis was performed utilizing Microsoft Excel  and SPSS Statistics Software . The Kolmogorov-Smirnov test was used to test for normality. Due to the normal distribution of the data, a one-way analysis of variance (ANOVA) was used to test for the statistical significance of GPT-3 versus GPT-4 versus human performance. To compare the means of the two groups, repeated unpaired two-sample t-tests were used. P-values were 2-tailed where applicable, and a p-value of less than 0.05 was considered statistically significant.GPT-4 performed significantly better than both GPT-3.5  and humans  on 467 ophthalmology StatPearls questions. When comparing individual categories, GPT-4 performed superior to both GPT-3.5 and humans in all categories except “lens and cataract”, in which humans performed better . However, this was not a statistically significant difference, likely due to the small sample size of level-one questions (n = 7). GPT-3.5 and human professionals performed similarly on level two and three questions while humans significantly outperformed GPT-3.5 on level-four questions . GPT-4 performed superior to both GPT-3.5 and humans on level two, three, and four questions (p < 0.001). Despite the variability in performance exhibited by GPT-3.5 and GPT-4 across difficulty levels, human performance remained relatively consistent. Acknowledging that GPT is incapable of directly analyzing images referenced within questions, the inclusion of images in the question stem did not yield any statistically significant differences in the performance of GPT-3.5 and GPT-4.Advancements in artificial intelligence have had profound impacts on many industries, including healthcare. One significant application of AI in healthcare is the development of conversational AI models, such as ChatGPT, which have the potential to assist medical professionals in providing accurate and timely information.Recent studies have focused on examining ChatGPT's roles in clinical decision-making, generating differential diagnoses, and providing insights into treatment options -12. In aWhen evaluating the performance of the models in individual subspecialty categories, GPT-4 demonstrated superiority over both GPT-3.5 and humans in all categories except for the "lens and cataract" category. While this category did not contain an increased number of higher-order questions compared to the other categories, it is possible it may have posed specific challenges that affected the performance of GPT-4. Such difficulties could stem from the presence of specific enhancements in the field of lens and cataract that may not be updated or reflected in ChatGPT’s training. Alternatively, it is conceivable that ophthalmology residents and fellows are more familiar with cataracts and lens-related topics, as they constitute the fundamentals of clinical practice. Further investigation into the specific difficulties encountered within this category could provide valuable insights for future model enhancements.The differences in performance between the models and humans varied across difficulty levels Figure . When thThe findings of this study have significant implications for the field of ophthalmology and the development of conversational AI systems. The superior performance of GPT-4 over both GPT-3.5 and humans suggests substantial rapid advancements in AI-based question-answering systems. GPT-4, released in March 2023, was able to achieve or surpass human performance within four months of its predecessor's release in November 2022. Earlier studies have highlighted the performance distinction between GPT-4 and GPT-3.5 on the OKAP exam with inferior accuracy of GPT-3.5 ,17. SimiThese improvements may enhance the accessibility and accuracy of medical information for healthcare professionals and patients alike, thereby potentially improving patient care and outcomes. However, it is important to note that GPT-4 is currently less accessible than GPT-3.5. Members must pay a monthly fee to use GPT-4 and are limited to 25 messages over the course of three hours. Additionally, both GPT-3.5 and GPT-4 have a knowledge cutoff of September 2021, which may limit the accuracy of these models in providing responses within a field that is constantly evolving. At present, these factors may be considered a barrier to the use of ChatGPT in clinical practice and education, as GPT-3.5 was shown to have inferior reliability in answering questions of varying difficulty and ophthalmic content.The current study has some limitations. First, it cannot be conclusively stated that these questions are only answered by ophthalmology residents, fellows, and attendings, though there are many factors that contribute to the answering pool consisting of only these groups such as a financial subscription and inputting proper credentials into the StatPearls portal for the respective question banks. Second, the evaluation was focused solely on ophthalmology StatPearls questions, which may not fully capture the range of complexities encountered in clinical practice. Although StatPearls has the credibility for the education of residents and fellows in various medical specialties, better standardization may be necessary to differentiate clinical judgment from mere factual knowledge. It cannot be conclusively stated that StatPearls multiple-choice questions are a gold standard for demonstrating enhanced cognitive understanding of medical thought processes by AI. Further studies should include a broader set of specialty-specific medical questions to assess the generalizability of the observed performance differences. Additionally, the human participants in this study may not represent the entire population of healthcare professionals, and their performance may be influenced by individual variations in expertise and experience.The results of this study demonstrate the significant improvements in performance achieved by GPT-4 compared to GPT-3.5 and human professionals on ophthalmology questions sourced from a professional-level question bank. While GPT-4 outperformed both GPT-3.5 and humans in most categories and difficulty levels, the “lens and cataract” category presented a unique challenge for the model. These findings highlight the potential of advanced conversational AI systems in the medical domain and emphasize the need for further research and development to address specific challenges encountered in different medical specialties.We support the use of AI as an adjunct in education and medicine rather than a replacement for human professionals. The results of this study indicate the advanced ability of AI models to answer multiple-choice questions, but the model’s performance on these questions is not a direct indicator of clinical aptitude. While the rapid advancement of GPT-4’s ophthalmic question-answering ability may foreshadow an increasing incorporation of the AI model into medical practice, an emphasis should be placed on using AI systems both responsibly and cautiously.


Microbiology wet labs have been eliminated in many medical schools and infectious diseases (ID) fellows are training in a post-COVID era where hands-on experience is lacking. The IDSA recommends 120 hours of microbiology experience for fellows, but feasibility is limited in centers struggling to retain adequate staff, and technicians are limited in their ability to integrate clinical skills. We aimed to overcome these struggles by implementing a microbiology and mycology curriculum for ID fellows using a case-based approach within the microbiology lab .In a quasi-experimental study, eight ID fellows from Wayne State University were taught in interactive, 1-hour sessions delivered monthly in the lab over 11 months using existing samples. Planning included a needs assessment, review of in training scores to identify weak spots, and pre-tests to assess baseline knowledge . Sessions topics are shown in Table 1. All sessions were delivered by an ID faculty to ensure homogeneity. Prior to each session, specimens were procured and objectives were outlined and linked to core content areas. An example of the objectives and core content for the hyaline mold session is shown in Table 2. A post-test occurred after session 9. Primary outcome was comparison of de-identified pre and post test scores by Wilcoxon signed-rank test for paired non-parametric data. Fellows experience and feedback for improvement were also collected.Sessions were performed as described and included hands on activities and a summary handout . Pre versus post test scores showed significant median improvement . Feedback on the sessions was overwhelmingly positive, with suggestions for encore sessions and request to make a similar parasitology curriculum (Table 4). Sessions became so popular that pharmacists and other trainees began attending. Although not an intended outcome, it was noted that after posting handouts to twitter, fellowship following increased by 250%.A monthly longitudinal microbiology and mycology curriculum was well received by ID fellows and objectively increased their knowledge. This is the first study attempting to objectively quantify knowledge gained using a hands-on microbiology lab curriculum to teach ID fellows.All Authors: No reported disclosures