Soluble PD-L1 (sPD-L1) has been associated with worse prognosis in numerous solid tumors. We determined sPD-L1 levels before and during nivolumab treatment in two prospective clinical trials of metastatic clear cell renal cell carcinoma (RCC) and melanoma patients, and investigated its relationship to clinical factors, biomarkers, and outcome.Using a new Single Molecule Array assay, serum sPD-L1 level were determined in RCC  and melanoma  prior to, and at two time points on treatment. Gene expression data was obtained from biopsies taken prior to, and at day 28 on treatment. Results were integrated with clinical variables, tumor PD-L1 status from immuno-histochemistry, and genomic mutation status.In RCC patients, sPD-L1 levels were higher in patients with progressive disease as their best response. For both RCC and melanoma patients, progressive or stable disease was associated with an increase in sPD-L1 on nivolumab therapy, whereas mean sPD-L1 levels did not change or declined in patients with objective responses. By categorizing RCC patients into transcriptomic molecular subtypes, we identified a subgroup where the associations between sPD-L1 and progressive disease were particularly evident. In baseline biopsies, we identified six biological processes that were associated with sPD-L1 level in both RCC and melanoma: higher sPD-L1 is associated with lower tumor expression of the Hallmark gene sets ‘hypoxia’, ‘fatty acid metabolism’, ‘glycolysis’, ‘MTORC1 signaling’ and ‘androgen response’, and with higher expression of ‘KRAS signaling_Down’.Baseline and on-therapy sPD-L1 levels in RCC have the potential to predict progressive disease on PD-1 inhibitor nivolumab. In a hypothesis-generating analysis of tumor gene expression, high baseline sPD-L1 is associated with a tumor metabolic state reflecting potentially targetable processes in both melanoma and RCC. In both trials, we observed associations between change in sPD-L1 on treatment and outcome metrics. sPD-L1 levels may further refine a nivolumab-refractory subtype of RCC within transcriptionally based subtypes of RCC. An ideal biomarker would be accessible in the periphery, relevant across multiple tumor types, and provide information to guide initial selection, combination and sequencing of therapies. Regulatory approvals for the PD-1 family of therapeutics have outpaced the development of clinically useful biomarkers for their use. Finding biomarkers for immunotherapies has proven to be particularly challenging, in part due to the dynamic nature of the tumor microenvironment and its relationship to the tumor. While sampling tumors for PD-L1 expression, tumor mutational burden (TMB) and inflammation have identified associations with response to PD-1 blockade therapy in multiple cancers including melanoma, renal cell carcinoma (RCC) has remained an outlier with respect to their utility.The PD-1 ligand (PD-L1) is a coinhibitory molecule expressed on immune cells  as well as some non-hematologic cells, such as the placenta. Tumor cells can also express PD-L1 through oncogene activation or induction by interferon-gamma.11Since PD-L1 may be expressed dynamically by both tumor cells and immune cells in the tumor microenvironment, soluble PD-L1 (sPD-L1) may be a more accessible and relevant surrogate for the total expression of PD-L1 by tumors (reviewed in Ref. 13). PD-L1 is a transmembrane protein and primarily expressed on the surface of cells, but multiple forms of sPD-L1 have been described: cleaved, secreted splice variants and exosomal PD-L1.15There is a clear need for liquid biomarkers that are broadly relevant to immunotherapy. We have developed an ultrasensitive capture assay to detect sPD-L1 using the Quanterix Single Molecule Array (SIMOA) technology. In this study, we quantified sPD-L1 in prospectively collected serum samples from patients in two biomarker-directed clinical trials of PD-1 monotherapy: advanced RCC (CheckMate 009) and melanoma (CheckMate 038 part 1). Using sPD-L1 levels at baseline and two on-treatment timepoints, we could also determine the dynamics within each patient. Somatic mutation status and gene expression data from pretreatment and on-treatment biopsies were available for a subset of patients in both trials. This study identifies clinical and biological factors associated with sPD-L1 levels and provides a comprehensive evaluation of the association between sPD-L1 metrics and therapeutic outcomes. We find that sPD-L1 is a dynamic marker of early PD on nivolumab in patients with either kidney cancer or melanoma.CheckMate 009 (NCT01358721) was an open-label, parallel, four-group, phase 1b study of nivolumab in advanced renal cancer . Part 1 of CheckMate 038  was an open-label, single arm, two group phase 1 study of nivolumab in advanced melanoma (Bristol Myers Squibb). Study design, methods, and baseline clinical and demographic features have been previously described.Tumor burden change (maximum reduction or minimum increase in index lesions) and Best Overall Response (BOR) were determined by Response Evaluation Criteria in Solid Tumors V.1.1. For analyses that require a binary definition of response , response status was defined to concur with previously published studies for CheckMate 009A previous ELISA assay (anti-human PD-L1 mAb 29E.12B1/capture and biotinylated anti-PD-L1 mAb 29E.2A3 (Biolegend)/detector) had a lower limit of detection sensitivity of 100 pg/mL of recombinant PD-L1.10.1136/jitc-2021-003527.supp1Supplementary dataPaired fresh frozen biopsies from metastatic lesions at baseline and study day 29 were used to evaluate tumor-associated lymphocytes, PD-L1 status, somatic genome sequence, and gene expression. IHC assessment of tumor-associated lymphocytes  and PD-L1 expression on the tumor cell surface (Dako PD-L1 IHC 28–8 pharmDx) have been described previously.16RNA was labeled by WT-Pico Ovation  and profiled using the HG-U219 array on the GeneTitan platform . Robust multi-array average expression values were determined for 18,562 loci (BrainArray V.10). Affymetrix data were evaluable for 72 patients in CheckMate 009  and 65 patients in CheckMate 038-P1 . Gene signature scores were calculated for the ‘Angiogenesis’, ‘T-effector’ and ‘Myeloid Inflammation’ gene sets described in the IMmotion150 trial publication (5), the Tumor Inflammation Signature (33), and ‘cytolytic’ gene set,26Association of discrete factors with response was evaluated using Fisher’s exact test. Hazard for survival was estimated from Cox proportional hazard models. HRs compare the highest tertile to the lowest tertile , the above median group to the below median group  or nominal patients whose sPDL1 values differ by IQR . Association of discrete factors with sPD-L1 level was evaluated using the Kruskal-Wallis rank sum test, the receiver operating characteristic (ROC) and the area under curve (AUC). Association of numeric factors with sPD-L1 level was evaluated using Pearson, Spearman and Kendall correlation.Gene expression data and annotation are in ArrayExpress . Analyses performed in R V.3.6.3 are available on github.com/rossmacp/sPDL1_ Publication).This study uses samples collected prospectively in two biomarker-focused clinical trials of nivolumab monotherapy. CheckMate 009 enrolled first-line (1L) and vascular endothelial growth factor receptor (VEGFR) inhibitor (VEGFi)-experienced (2+L) patients with advanced RCC, while CheckMate 038-part 1 enrolled several types of advanced melanoma and included a cohort that had previously been treated with ipilimumab. Both studies specified characterization of serum cytokine levels and tumor immune infiltration as primary outcomes. To this end, samples of sera were obtained at multiple time points on treatment, and the data available from pretreatment and on-treatment tumor biopsies includes IHC for PD-L1, gene expression and somatic mutation status.We applied our ultrasensitive SIMOA sPD-L1 assay (Methods) with sera samples obtained from patients enrolled in CheckMate 009/RCC (n=91) and CheckMate 038-P1 (n=78). sPD-L1 levels were determined at baseline (prior to initiation of nivolumab), at day 29, and at day 43 for CheckMate 038-P1 or Day 63 for CheckMate 009 . Over 90We evaluated association between baseline sPD-L1 and clinical characteristics of the patient populations . In Chec10.1136/jitc-2021-003527.supp2Supplementary dataIn CheckMate 038-P1/melanoma, we observed no significant association between sPD-L1 level and the time on therapy . We saw We evaluated association between the sPD-L1 level at each timepoint and the patient’s BOR . In CheckMate 009/RCC, median sPD-L1 was higher at all timepoints in patients with PD relative to SD or CRPR . At baseWe also evaluated association between sPD-L1 level and progression-free survival (PFS) or overall survival (OS). Hazard for PFS was increased in the highest tertile in CheckMate 009/RCC (p=0.06 on treatment at day 63), but there was no statistically significant difference in hazard for PFS or OS at any time point in either trial . HRs werGene expression data from baseline biopsies was available for 59 patients in CheckMate 009,In CheckMate 009/RCC, baseline sPD-L1 level had a negative association with the Angiogenesis transcriptional score, and positive association with presence of resting mast cells p<0.05, . We alsoIn CheckMate 038-P1/melanoma, higher baseline sPD-L1 level had negative association with the ‘Myeloid Inflammation’ score p=0.046, . We saw Six Hallmark gene sets were enriched with the same direction in GSEA results from both RCC and melanoma: high baseline sPD-L1 is associated with lower expression of genes from ‘Hypoxia’, ‘Fatty Acid Metabolism’, ‘Glycolysis’, ‘MTORC1 signaling’ and ‘Androgen Response’, and with higher expression of genes from ‘KRAS signaling_Down’. A further eight Hallmark gene sets were enriched but with the opposite direction in melanoma and RCC . These eIn CheckMate 009/RCC and CheckMate 038-P1/melanoma, serum samples were evaluated at two on-treatment timepoints, allowing investigation of the relationship between change in sPD-L1 and outcome. These analyses of paired samples excluded any cases where sPD-L1 values exceeded the ULOQ. It should be noted that patients with PD are under-represented at the later on-treatment timepoint, reducing our ability to detect association .In CheckMate 009/RCC, most patients showed an increase in sPD-L1 on therapy at day 29 and at day 63 . There was an association between the increase in sPD-L1 and BOR. The increase of sPD-L1 was least in CRPR, both at day 29 (median change +79 pg/mL) and at day 43 (median change +70 pg/mL) . At day We also evaluated the association between change in sPD-L1 and survival, and observed that increase of sPD-L1 on therapy is related to worse survival outcome both in CheckMate 009/RCC and in CheckMate 038-P1/melanoma . This reHaving observed an association between increase of sPD-L1 on therapy and poor clinical outcomes, in both CheckMate 009/RCC and CheckMate 038-P1/melanoma, we wished to further characterize the biological basis of the increase. We first compared the change in sPD-L1 at Day 29 to the change in Cibersort immune cell populations in pretreatment vs day 29 biopsies . We did We then analyzed correlation between our scores for published transcriptional gene sets, derived in pretreatment biopsies, and the change in sPD-L1 at day 29 of therapy . We founWe also analyzed correlation between the Cibersort immune cell estimates in pretreatment biopsies and the change in sPD-L1 at day 29 of therapy . In ChecFinally, we observed that in CheckMate 009/RCC patients with ccrcc1 subtype tumors had the highest median change in sPD-L1 at day 29 . We thenWe investigated possible associations to sPD-L1 levels in two prospective trials of nivolumab treatment, and found an association with some clinical characteristics, as well as association with PD and worse survival outcomes in both trials. This study is the first to report an association between serum sPD-L1 levels and clinical outcomes on nivolumab before and during treatment of metastatic ccRCC and metastatic melanoma. Furthermore, the association of PD with change in sPDL1 on treatment is the first biomarker to agree between melanoma and RCC.Our findings are consistent with sPD-L1 being a marker of aggressive disease in both RCC and melanoma,28Our analysis of gene expression in pretreatment biopsies from RCC found a clear association between low baseline sPD-L1 and higher expression of an ‘Angiogenesis’ signature that predicts a positive response to sunitinib in the ImMotion 150 trial.Interestingly, on nivolumab therapy, an increase in sPD-L1 is associated with progression in both RCC and melanoma, suggesting a potential immunologic mechanism of early resistance to PD-1 blockade in both tumor types. sPD-L1 is a noninvasive means of monitoring the early trajectory of the disease on treatment. While the association between the sPD-L1 increase at day 29 and lack of response (PD or SD) was significant in both trials, day 29 is not an optimized time point. Analysis of a full time series could refine the performance of sPDL1 as an indicator of PD. In the CheckMate 009/RCC study, prior investigations focused on exploring predictors of response to nivolumab failed to find a clinically useful predictive biomarker, which may have been due in part to the study having a low response rate relative to other nivolumab clinical trials in kidney cancer.


We report μm scale, few-layergraphene structures formed at moderate temperatures (600–700°C) and supported directly on an interfacial dielectric formedby oxidizing Si layers at the graphene/substrate interface. We showthat the thickness of this underlying dielectric support can be tailoredfurther by an additional Si intercalation of the graphene prior tooxidation. This produces quasi-freestanding, patterned graphene ondielectric SiO While isolation of graphite layersby mechanical exfoliation led the field in characterizing the materialproperties,5 andsemiconductor7 substrates or high-temperatureannealing of SiC10 has gained the most traction for producing high-qualitygraphene films. A large number of routes for further processing arenow available, such as photolithography,12 electron beam lithography,14 scanning probe lithography/etching,16 and direct laser lithography.19 However, these methods each havetheir own disadvantages, e.g., growth on a metal substrate requiresthe graphene to be transferred and patterning induces defects/contaminantsthat reduce device efficacy.21Chemical vapor deposition (CVD) on metal23 Graphene is then formed by annealing in the presence of carbon,and the metal film is subsequently removed chemically, leaving thegraphene in direct contact with the dielectric material. Althoughthis method shows great potential, metal contamination remains a majorissue.24 An alternative approach for removingmetal from the graphene has been demonstrated,25 as has a method for adding a dielectric layer under thegraphene after growth.26 Both modify thegraphene–substrate interaction, which is known to impact theelectronic properties of graphene.30 Although there is no single methodthat suits all device applications, there is a desire for transfer-freemethods that produce graphene free of contaminants and with controlof the substrate interaction, directly on dielectric surfaces. Inthis work, we demonstrate transfer-free, patterned graphene structureson SiC, with optional decoupling by forming SiO2 at thegraphene–semiconductor interface.A promising transfer-freemethod utilizes a transition-metal catalyst(Cu or Ni) deposited directly onto an oxide layer on a Si wafer.232 Thin films of Fe or Ru (1–2nm) on 6H-SiC(0001) were thermally activated by annealing to temperaturesof 600–700 °C for a short duration. This triggered transition-metalsilicide formation at the interface and the associated liberationof carbon reconstructing into graphitic (sp2) layers onthe surface. Following the growth, all samples were subsequently annealedto higher temperatures (T > 700 °C) to diffusethe metal into the bulk of the underlying SiC substrate.32 This left the graphene layers supported directly on a thin filmof Si.In our previous work, few-layer grapheneon transition-metal silicidewas prepared according to the metal-mediated approach as describedelsewhere.To demonstrate the possibility of patterning graphenewe followedthe above approach, but now with predefined metallic regions (priorto graphene growth) in regular arrays of squares or circles by meansof a simple shadow mask. The metals Fe and Ru were deposited underultrahigh vacuum (UHV) onto chemically and thermally cleaned 6H-SiCsubstrates through solid masks made of a Mo foil with openings of50 and 500 μm that were placed in proximity (<0.3 mm) tothe sample surface.32 hybridized carbon is observed at 2708.4 cm–1  a symmetric peak from the C–Si bonds inSiC appears at 1.1 eV lower binding energy.8 The spatially resolved Raman and EF-PEEM thus demonstrate that grapheneforms only within the metalized regions.The spatially resolved C 1s corelevel intensity from a similarlyprepared sample is shown in S1 and S2.These twelve spots have a |k| = 2.50 Å–1, i.e., within ±2% of what is expected for pristine graphenelayers36 and are thus interpreted as twopredominant graphene rotational domains, G1 and G2. Additional spots(M) are also observed that likely originate from an underlying bcc(110)lattice constrained by the hexagonal 6H-SiC(0001) surface. Similarfeatures have been reported for Fe thin films on hexagonal surfaces38 and are removed at a later stage.32The crystalline qualityof the graphene formed is demonstratedfrom the small spot (1.5 μm) low-energy electron diffraction(μ-LEED) pattern in 32 The spatial distributionof C 1s core level signal from this system is resolved in In our earlier work, thermalized thin films of Ru on 6H-SiC havebeen shown to produce graphene of a similar quality to those mediatedby thin films of Fe.41 rather thanby the abruptness of the patterning.The lateral resolution of the patterning can be ascertainedfromthe sharpness of the boundary between the graphene region and theSiC substrate, as shown in the low-energy electron microscopy (LEEM)image in 44 and other 2D materials.45When annealed for a longerduration, the patterned geometry andthe photoemission signal from the graphene in each growth region arewell preserved, as shown in The chemical stabilityof the patterned graphenewas tested by exposing both systems to air for 30 min. In 48 this small energy increase hints at a change in thepotential at the graphene interface. Furthermore, the intensity ofsecondary electrons (SEs) near the low-energy cutoff increases byroughly 1 order of magnitude. This can be explained by the longerinelastic mean-free path of photoelectrons associated with the widerband gap of SiO2.49 Togetherwith the higher background intensity seen from the LEED  and near-edge X-ray absorption fine structure (NEXAFS)measurements were performed both inside and outside of the graphenegrowth regions. Note that to perform spatially resolved, high-resolutionspectroscopy like this, particularly the NEXAFS, samples of metal-mediatedgraphene were produced with a patterning scale of 5 mm to compensatefor the larger spot size of the photoexcitation.To further explore the possibility of electricallydecoupling thegraphene, insulating SiO2 as previously demonstrated for CVD graphene grownon transition-metalsubstrates.26 In the first step, patternedgraphene was subjected to Si atoms at a flux of 0.15 Å/min for40 min while being heated to 450 °C. K-edge and the Si 2p and C 1s core levels for Fe- and Ru-mediatedgraphene samples. During deposition, the intensities and shapes ofthe 1s → π* excitations  are attenuatedstrongly. New and prominent peaks (Si2) appear at lower binding energiesrelative to the surface Si–C and silicide (Si1) in the Si 2pregion .52With Op signal 4c of Reg56 Inside the pattern (Region I), the graphene does not show any signsof oxidation: the π* resonances of the NEXAFS appear to be unchanged,and the energies, shapes, and intensities of the graphene core levelsare well preserved. In 5/2 signal from the Ru-mediated graphene system can no longer be distinguishedat this stage. With the presence of SiO2 verified fromthe Si 2p signal, the robustness of the graphene peaks suggests thatthe graphene is now supported directly on top of the SiO2.As expected,no signatures of graphene can be observed in the regionpreviously shadowed by the mask (Region II). The NEXAFS shows no π*resonance, and the only C 1s signals present are those correspondingto the C–C and C–Si bonds of the SiC surface.42 layer can easily be formed throughstepwise intercalation of Si and O2, in principle yieldingoxides with precise thicknesses by controlling the dosage of eachof the two constituents. Hence graphene–dielectric–semiconductorheterostructures with tailored and tunable oxide thicknesses can beproduced. This simplistic approach is suitable for producing someof the building blocks for graphene-based device applications thatrely on a semiconducting substrate/body, such as graphene-based field-effecttransistors (GFETs)58 and radiation sensors.59 Our results thus demonstrate the principle andfeasibility of transfer-free growth of graphene on dielectric, whichmay open up avenues for integrating the techniques presented intothe established framework of semiconductor device processing.The demonstrated concepts oftransfer-free and patterned grapheneformation directly on dielectric thin films is an exciting developmentthat allows structured graphene to be defined in a simple and straightforwardmanner with minimal extra processing required. Transition metals Feand Ru can be used interchangeably to predefine the growth regions,and at moderate temperatures (600–700 °C), both will yieldhigh-quality graphene that is robust against subsequent exposure toair. An underlying SiO


Therefore,we add herein a new dimension for controlling the formation of theTICT state, in addition to the solvent polarity and acceptor strengthparameters. These findings are not limited to the studied dyes, andwe expect that numerous organic carboxylic acids dyes show similarproperties.Organic dyes haveshown high efficiencies in solar cells, whichis mainly attributed to the push–pull strategy present in suchdyes upon attaching to the semiconductor surfaces. We deeply studiedthe fundamental photophysical properties of cyanoacrylic dyes, mostlythe L1 dye, and found unique emission properties that depend on manyfactors such as the solvent polarity and the concentration of thedye and could present a complete emission picture about this familyof dyes. The L1 dye shows an intramolecular charge transfer (ICT)emission state at low concentrations and shows a twisted intramolecular charge transfer (TICT) emissionstate in specific solvents upon increasing the concentration to themicromolar scale. Moreover, the associated emission lifetimes of theICT and TICT states of the L1 dye depend on solvent basicity, highlightingthe role of hydrogen bond formation on controlling such states. Densityfunctional theory calculations are performed to gain insight intothe photophysical properties of the dye and revealed that H-bondingbetween the carboxylic groups triggers the dimerization at low concentrations.Using femtosecond transient absorption, we assigned the rate of TICTformation to be in the range (160–650 fs) This dye wasdesigned as a photosensitizer in DSSCs and comprises a triphenylamineas a primary donor and the cyanoacrylic acid (CyA) as a primary acceptorand anchor group see 1b. Remar20The L1 dye (5-[4-(diphenylamino)phenyl]thiophene-2-cyanoacrylicacid (CAS 762269-56-7) was obtained from Dyenamo AB. However, thesynthesis of L1 was described earlier.Absorption andemission spectra were performed at a right angle in a 1 cm cuvetteby using a Varian Cary 5000 and an Horiba Jobin Yvon Fluorolog, respectively.Emission measurements were automatically corrected for wavelength-dependentinstrument sensitivity.21 Briefly, the sample was excited with a picosecond diode laser  at 404.6 nm (77.1 ps pulses), giving an instrumentresponse function of ca. 100 ps.The TCSPC setuphas been described in detail previously.21 Briefly, excitationof the sample with ultrafast laser pulses was performed by using afrequency-doubled Ti:Sa oscillator (Coherent Mira) output (400 nm).Fluorescence at a right angle to the excitation was passed througha Bruker SPEC 250IS spectrograph and onto the streak camera (Hamamatsustreak camera and blanking unit C5680 in combination with a SynchroscanUnit M5675). The charge-coupled device (CCD) camera (Hamamatsu Orca-ERC4742-95) was used in binning mode (2 × 2 pixels) to give a 512× 512 pixel matrix.The streak camera setup hasbeen described earlier.22 Briefly, the ca. 100 fs (1 kHz) output pulsesfrom a Coherent Legend amplifier were split, and one part was frequencydoubled for 400 nm excitation. Another part of the output was sentinto a moving CaF2 plate to produce white light as theprobe beam. After passing through the sample and a spectrograph, thelight was detected from ∼390 nm to up to 700 nm by a 512 pixelphotodiode array.A detaileddescription of thetransient absorption setup can be found in a previous publication.0) and first excited state (S1), and the absorption and emission spectra were calculatedwith the time-dependent DFT method.23 Thesecalculations were performed in acetonitrile, described implicitlyby using the polarized continuum model (PCM), with the Gaussian 16program.24 Density functional theory (DFT)calculations were performed with the 6-31G(d) basis set and the CAM-B3LYPfunctional.25 This functional is chosenas it takes long-range interactions into account, which is importantto describe ICT states.26 Relaxed potentialenergy scans of the dihedral angles ϕ1, ϕ2, and ϕ3 of L1  analysis wasperformed to quantify the degree of intramolecular charge transferin the two states. Intermolecular interactions and its impact on theabsorption spectra of L1 were investigated by using the (L1)2 dimer as a model. The S0 geometry of the (L1)2 dimer was optimized in the gas phase starting from various initialbinding conformations, and the interaction energies of all stablestructures (no imaginary frequencies) are calculated29 without (E) and with (ECP) correction for basis set superposition error (BSSE) by using thecounterpoise procedure of Boys and Bernardi.30Quantum chemicalcalculationsare performed to gain insight into the change of the absorption andemission spectra of L1 in response to its charge  and molecular aggregation (monomer vs dimer). Thegeometry of L1 and its deprotonated and various protonated forms wasoptimized in the ground of 7.3 D and by 30°, 26°, and 0° for ϕ1, ϕ2, and ϕ3, respectively. Incomparison, L1 is more polar (μ = 12 D) and more planar  in the S1 state. NBO analysis revealscharges of 0.17 and 0.28 for the triphenylamine moiety in the S0 and S1 states, respectively. This indicates thatICT occurs to a greater extent in the excited state, which is consistentwith the larger polarity of the S1 vs S0 state.This ICT is responsible for the observed trigonal planar rather thantriagonal-pyramidal geometry of the triphenylamine moiety . Sucha high association constant is matching with the low concentrationutilized for such observations.32 Thesespectral changes are not only limited to the L1 dye but are also observedin other cyanoacrylic dyes with different molecular weights such asthe D131 and L0 dyes .The new spectral bands that appear upon increasingthe L1 concentrationare assigned here to the dimers formed between L1 molecules throughthe CyA groups according to the following simple equation:Figure S4). We have excluded the possibility of L1 deprotonation atlow concentrationsby the possible traces of water present in aprotic MeCN by measuringthe absorption spectra of L1 in the presence of water and in EtOH(pure protic solvents) see S4. FigurFigure S5). The additionof the dioctylamine base is expected to deprotonate the L1, whichinhibits the formation of the dimers, giving an absorption spectrumsimilar to the monomer form of L1 . In addition, measuring the L0Br dye (a derivativeof L0 with Br instead of CN) yields similar absorption behavior tothat of L0 . These evidencespreclude the role of the CN group in the dimerization process itself.Interestingly, the equilibrium between monomers and dimers of L1can be shifted as well by only adding organic bases 3b and ac2L1a–2L1c) are less stable than those with planarorientation of the interacting pair (2L1d–2L1g), indicating that dimerization is attributed to H-bondingrather than hydrophobic association of the aromatic groups. The moststable structure (2L1g) is stabilized by two (O–H···O=C)H-bonds between the carboxylic groups and display an interaction energy ECP = −20.7 kcal/mol. Structure 2L1f is 6.3 kcal/mol less stable than 2L1g, confirmingthat dimerization is derived by the carboxylic rather than the cyanogroup.The structures of the various stable conformers of (2L1) calculatedwith CAM-B3LYP/6-31G(d) in the gas phase are given in 2L1g) wasalso optimized in acetonitrile, and its absorption spectra were calculated(see max relative to thisof the isolated monomer (429 vs 415 nm), confirming that the observedincrease in λmax with increasing the concentrationof L1 and the polarity of the environment, we excluded the formation ofexciplex or excimers.With regard to the emission data of L1, we assign the emissionat 570 nm to the ICT state, in which the charge is transferred fromthe triphenylamine to the CyA moiety as shown previously by TD-DFT.3. Apparently, a highly stablecomplex species can be formed between formamide and L1 dye . This reflects the tendency of thecyanoacrylic group to interact with the solvent molecules throughhydrogen bonding.38 Despite, the absence of monomer–dimerequilibria of L1 in formamide, the formamide complex species showas well an emission–temperature relationship reflecting thepresence of an actively excited state process, as shown in We have also measured the L1 dye in awide range of solvents withdifferent properties to correlate between the monomer–dimerequilibrium and the solvent effect on the ICT and TICT states.  dye see S7. This  dye see S7. This 3, dioxane,tetrahydrofuran, toluene, and benzene), no changes in absorption andemission bands were observed upon changes in concentration; however,L1 is expected to be in dimeric form . The absorption spectrum of L1 in CHCl3 is slightlychanged after adding the carboxylic acid but significantly changedupon adding the organic base, which confirms the presence of the L1molecules in the dimer form in nonpolar solvents. Thus, On the other hand, in nonpolar solvents +, and (L1–H+)− speciesare reported in max = 349nm. In line with experiment, the RCNH+ and R2SH+ protonated forms show red-shifted absorption spectra. However, thelower basicity of the R2S vs RCN group and the fact thatthe R2SH+ structure is 24 kcal/mol less stablethan RCNH+ indicate that the latter is the protonationform of L1 in the presence of strong acids such as HCl and TFA. Similarto experiment, calculations predicts a blue-shifted absorption ofthe deprotonated species (λmax = 366 nm) relativeto the neutral molecule. The fact that calculations overestimate andunderestimate λmax of the protonated and deprotonatedspecies, respectively, is likely due to the implicit description ofthe solvent. Charge transfer from and toward the solvent moleculessurrounding the protonated and deprotonated species would improvethe agreement with the experiment. Calculations predict an emissionspectrum of L1 with λmax = 555 nm, in a very goodagreement with the experimental value (570 nm). In comparison, theRCNH+ protonated form displays emission spectra with λmax = 645 nm, while the acetate anion possesses λmax = 505 nm. The ϕ1, ϕ2,and ϕ3 dihedral angles for the RCNH+ protonatedform in the S0 state are  andare  in the S1 state. As canbe seen, the calculations provide more accurate results for the protonatedform than the pure L1 dimers . This indicates that the TICT stateof the L1 dimer will be more stable than the ICT state of the L1 monomer.As stated previously, adding organic bases or acidsto solubleL1 shows similar effects to the monomer–dimer equilibrium invarious solvents. To investigate the impact of strong acids and baseson the absorption and emission spectra of L1, we calculated the absorptionand emission spectra of the protonated and deprotonated forms of L1in MeCN. We consider the S and two N atoms as possible protonationsites in L1. The geometry of these three protonated forms and thegeometry of the deprotonated molecule (carboxylate ion) were optimizedin the Smers see 4; thus, 39 of the solvent in 41 Clearly, the large scale motions of L1, in either ICT or TICT, dependon the H-bond interactions in the excited state. Similar solvent effectshave been detected previously but a carboxylic acid dye.32 As can be seen, only at high concentrations(dimers) and in sufficiently polar solvents, TICT is enabled as afaster deactivation channel. In nonpolar solvents, such as benzene,the L1 is expected to be in the dimeric form; however, the lifetimemeasurements are independent of concentration, and the dimers in thesenonpolar solvents show long-lived ICT emission. To check the suppressionof TICT state in L1, we measured the embedded form of L1 in the PMMAmatrix (poly(methyl methacrylate)), and as expected long-lived emissionspecies with lifetime of ca. 3.5 ns (81%) and 1.2 ns (16%) were measured.The minor 1.2 ns component is likely to represent L1 in a slightlydifferent environment, possibly interacting with specific groups ofthe PMMA.39 Comparing the lifetime emissionof L1 embedded in PMMA and in CH3Cl confirms the inabilityof dimers in nonpolar solvents to populate efficiently the TICT state.The 3.5 ns component is assumed to be close to the radiative lifetimeof L1 and a sign of a complete inhibition of the TICT formation. Similarly,the TICT formation could be completely prevented in frozen formamideby lowering the temperature to 77 K (see The time-resolved emission data were measured with a streak cameraand time-correlated single photon counting (TCSPC) to further characterizethe two emission bands. The ICT and the TICT bands were found to besolvent-dependent, showing emission lifetimes of 0.5–3.0 nsfor the ICT state and ca. 50–200 ps for the TICT state 2. The em77 K see 5b. These42 and 175 ps for the decay of the TICT state.To monitor the spectral changesof emission for L1, the transientemission of L1 in DMSO is shown herein, as it shows the most strikingspectral changes with variation of concentration. At low concentration(monomer case), the main emission centered at 550 nm is assigned primarilyto the ICT state of monomers 7, top. HFigure S10). The larger formation lifetime in D131 than in L1 can be assignedto the larger molecular size of D131. Similar correlations betweenthe dye molecule size and such large-scale motions have been discussedpreviously.15Femtosecond transient absorption spectroscopy (TA) was used tocharacterize the transition between the initially excited ICT stateand the TICT state according to the scheme shown in The observations from absorption and fluorescencespectroscopyas well as from DFT calculations are summarized in 14 indicatingthat the TICT state should have long-lived emission that the ICT state.This apparent contradiction can be understood via the degree of freedomthat the molecules have in solution and not on semiconductor surfacesor in the single crystals. In either way, it is clear now that furtherincrease of the acceptor strength of the cyanoacrylic group by dimerizationin polar solvents or by attaching it to a semiconductor surface willfacilitate the population of the TICT state, leading to red emissionin polar solvents and minimize the charge recombination in solar cells.It is worth mentioning to compare between the nature of TICT forL1 in solution and on mesoporous surfaces. We previously interpretedthat presence of the TICT state in the L1 on semiconductor surfaceshinders the charge recombination process,14 Thus,our study contributes to both fundamental and applicable understandingsfor such organic dyes.We have studied the photophysical properties of cyanoacrylic dyesin solution taking the L1 dye as model for this class of organic dyesutilized primarily in solar cells as photosensitizers. Our study revealedthe presence of monomer/dimer equilibrium with high association constant.The dimerization has been confirmed experimentally and theoreticallyto be through the carboxylic acid group. The formation of the L1 dimermodifies the strength of the acceptor group and thereby shifts theenergy level of the two lowest excited states (ICT and TICT) in polarsolvents such that TICT is stabilized sufficiently to become the lowestand fluorescent state. This opens possibilities for tuning the emissionacross the visible spectrum solely by changes in dye’s concentration.Also, we could correlate the high performance of cyanoacrylic dyesin solar cells due to the population of the TICT state through increasingthe acceptor strength of the cyanoacrylic dye.


Pancreatic cancer is a highly lethal gastrointestinal malignancy. Most patients are already in the middle to advanced stages of pancreatic cancer at the time of diagnosis and cannot be treated completely. As a single-atom planar two-dimensional crystal, graphene’s unusual electronic structure, specific electronic properties and excellent electron transport capacity make it uniquely advantageous in the field of electrochemical sensing. In this mini-review, we summarize the potential application of graphene in pancreatic cancer detection. K-Ras gene, CEA and MicroRNA are important in the early diagnosis of pancreatic cancer. Pancreatic cancer is a malignant tumor of the gastrointestinal tract with a high mortality rate. Currently, the diagnosis and treatment of pancreatic cancer are difficult . Since tA suitable tumor marker should be highly specific, sensitive and easy to detect. However, numerous clinical studies have shown that it is very difficult to find an ideal tumor marker with 100% specificity and sensitivity and whose level correlates with tumor size, stage and prognosis . In the Graphene is a new type of carbon nanomaterial discovered in 2004. With its ideal flat two-dimensional structure, unique electronic, thermal, optical and mechanical properties, it has excellent prospects for high-tech applications in electronics, mechanics, medicine and aerospace. After carbon nanotubes, it is an emerging carbon nanomaterial with great theoretical and application prospects after carbon nanotubes. As a single-atom planar two-dimensional crystal, graphene’s unusual electronic structure, specific electronic properties and excellent electron transport capacity make it uniquely advantageous in the field of high-sensitivity detection . GraphenIn this mini-review, we summarize the potential application of graphene in pancreatic cancer detection. K-Ras gene, CEA and MicroRNA are important in the early diagnosis of pancreatic cancer. Therefore, this mini-review was divided into three sections. Each section first described the value of the clinical application of the analyte. Then, we described how the electrochemical sensor can achieve sensitive detection with the assistance of graphene.A large number of studies have shown that the mutation rate of K-Ras gene in pancreatic cancer patients can reach more than 90%, and the product of K-Ras gene expression is K-Ras protein with GTPase activity . The K-RGraphene quantum dots (GQDs) were used for electrochemiluminescence (ECL) detection of K-Ras genes . To imprRecent studies have found that aberrant expression of microRNA, a highly conserved class of endogenous non-coding RNA molecules of 18–25 nucleotides in length, is also associated with pancreatic cancer . It is wCarcino-embryonic antigen (CEA), which is widely present in digestive system cancers of endodermal origin, is also present in the digestive tract of normal embryos . CEA is 2 (CS-Fc-TiO2) composite membranes onto GCE. Then, AuNPs and graphene nanohybrids were self-assembled onto the CS-Fc-TiO2 composite membrane modified electrode. This combination utilizes the strong interaction between AuNPs and carcinoembryonic antibody (anti-CEA) to further immobilize anti-CEA on the modified electrode surface, resulting in a CEA immunosensor. Due to the high surface free energy, strong adsorption affinity, good adaptability and conductivity of AuNPs, they provide more binding sites and a more suitable microenvironment for the immobilization of biomolecules. The synergistic effect of graphene and AuNPs leads to high conductivity and sensitivity, with linear detection range of 0.01–80 ng/ml for CEA and detection limit of 3.4 pg/ml (S/N = 3). The sensor showed excellent selectivity for CEA by detecting some possible interferents. The relative deviations of the results for six plasma samples were less than 10% compared with those of the commonly used clinical ELISA method. The good agreement between the two methods was obtained, and the simplicity and rapidity of the electrochemical assay showed great potential for its clinical application and for the detection of low levels of protein. 2SnZnS4 (CZTS) as the antibody marker material, with a wide linear range of 0.5 pg/ml to 20 ng/ml and a detection limit of 0.16 pg/ml.2+)-dependent DNA enzyme-assisted signal amplification and graphene quantum dot ionic liquid-ion (GQDs-IL-NF) composite membrane for highly sensitive determination of CEA. The CEA-containing nucleic acid aptamer and the hairpin DNA of the DNAzyme chain recognize the target and form a CEA-nucleic acid aptamer complex in the presence of CEA. In the presence of Pb2+, a DNAzyme-assisted signal amplification reaction was performed to produce large amounts of ssDNA. Adsorption of ssDNA onto GQDs-IL-NF-modified GCEs by π-π stacking. As a result, methylene blue-labeled substrate DNA (MB-substrate) is immobilized on the electrode and generates an electrochemical signal. Under optimal conditions, the biosensor shows a linear range of 0.5 fg/ml to 0.5 ng/ml with a detection limit of 0.34 fg/ml.Graphene, a novel material with a monolayer, two-dimensional carbon nanostructure, has a great specific surface area and excellent electronic, chemical, and mechanical properties. It also has excellent biocompatibility, which makes it extremely useful in all bioelectrical analyses. In the detection of pancreatic cancer, graphene-based biosensors can show excellent sensitivity and selectivity for both proteins (cancer markers) and DNA, making it an ideal material for the construction of efficient, fast, and sensitive detection biosensors. However, there are still some factors affecting the application of graphene in biosensors that need further detailed study. These issues include 1) the effect of the oxygen-containing functional group fraction in graphene on its electrochemical properties; 2) how to prepare graphene with high electrical conductivity and good solution dispersion; 3) the effect of heteroatom doping on the electrochemical properties and stability of graphene; 4) the connection mode and interaction between biomolecules and graphene in sensors; 5) the biocompatibility of graphene in different biosensing applications issues. These studies related to graphene-based materials will open new directions in the field of biosensor research.


The present paper discusses the climatic effects of humidity and temperature on cochlear implant functioning and the quality of the electrical sound signal. MATLAB Simulink simulations were prepared, offering insights into signal behavior under such climatic parameter changes. A simulation setup of the cochlear implant was developed, where a source type selection was used to change between a voice recording and a “chirp” sound. In addition, a DC blocking filter was applied to the input signal. A simulation code, with the application of the climatic influence via the air attenuation function, was developed. Thereby, the attenuation of temperature and humidity in the sound atmospheric circulation of the input signal, at T = 0 °C and RH = 0% and at T = 36 °C and RH = 40% was graphically represented. The results of the electrical pulse generator for each of the eight channels, with the IIR filter, Gaussian noise, temperature variation, humidity influence, and control of denoise block activity, were thus obtained.  Hearing is an important component of human beings’ quality of life, at any age. It is well known that hearing capacity decreases with age or due to some professions. Hearing loss may ultimately lead to deafness. The decrease of hearing capability towards deafness, and its inherent social complications, can be a major source of discomfort. However, many babies are born or develop during early childhood (ages 1–3 years) with profound hearing impairments. As babies learn through speech recognition, the fact that they cannot hear may lead to the mispronunciation of words and difficulties in learning language. These challenges may result in major setbacks in their life and in human interaction, with respect to other children their age. Without proper treatment, they may require special assistance within society. Numerous solutions for resolving this issue, some of which are more or less efficient, have been proposed. Among the best solutions so far, with excellent hopes for positive development in terms of technical performances, is the cochlear implant ,6,7,8,9.The hearing aid, an external device which amplifies the signal, has a retail price between USD 1000 and USD 6000 each, and is available via companies such as Bernafon, Oticon, Phonak, Resound, Signia (formerly Siemens), Starkey, Unitron, and Widex . On the In 2019, the global market value for hearing aids was USD 8.99 billion (with a CAGR of 8.2%) and USD 1.67 billion for cochlear implants (with a CAGR of 10.6%) . The majThe objective of this paper was to study humidity and temperature effects on the quality of sound within cochlear implants via a MATLAB Simulink complete simulation approach. Both humidity and temperature sensors work together to provide a correct and complete response to the sound signal influence of climatic changes. The aim of this work is a theoretical one, of pure precise modeling, as a first step in the validation of our novelty approach. The complex validation process will be made available in a subsequent paper when we will take measurements and the experimental data will be properly analyzed and compared with the simulation data.It is very important to investigate the quality of the environment from the point of view of the sensor response individualization and correctness of the information. In this project, we aimed, on one hand, to study and monitor the environment in the vicinity of the implant. Among the parameters of interest were temperature and humidity. On the other hand, our objective was to individualize the behavior of the cochlear implant for each patient. The latter is an important task in order to properly identify the individual treatment required by each patient. It is said that we have patients, not diseases. Every patient with this implanted device displays a different comportment with respect to individual living and working conditions. As the patient with the cochlear implant will have a dynamic life, including a changing environment, humidity and temperature information from their surroundings will be of crucial importance to the proper functioning of their cochlear implant. This information will be fed into the system. More specifically, the humidity sensor will help in calibrating the loudspeaker of the implant, which receives the information from the exterior and then sends it to the internal unit.Cochlear implants (CIs) are implantable auditory prostheses designed to restore access to sound in deaf individuals via direct electrical stimulation of the auditory nerve. Each CI consists of a speech processor with a microphone worn outside the ear, which processes sounds and then transmits the processed signal via a transmitting coil to a receiver under the skin. This receiver converts the signal into electric current, which is then sent to the cochlear implant electrode array implanted in the cochlea. The microphone transmits processed information via the transmitter coil through the skin, to an internal receiver in the cranial bone that converts this signal to electrical pulse trains to be delivered to the electrodes implanted in the cochlea.Cochlear implants have their own dynamics towards performance, being subject to changes month by month and always offering better, more efficient variants .Used as the main component in implantable stimulators, the second-generation integrated circuit for the Active Books stimulation microsystem in neuro-prostheses, has already been realized. The microprocessor used is composed of two sensors, one temperature and one humidity .The humidity sensor output varies linearly with relative humidity (RH) with a normalized sensitivity of 0.04% RH over the range of 20–90% RH. The temperature sensor has a nonlinearity of 0.4% over the range of 20–90 °C and a resolution of 0.12 °C. The stimulator is the first of its kind to include two integrated temperature and humidity sensors.The idea, presented in this paper, of using a single temperature and humidity sensor in the IC was developed during an activity carried out at the University of Cambridge, which was published in specialized journals . This avThe relationship between different weather variables, such as temperature and humidity, can be quite confusing. Temperature and humidity are connected either directly or indirectly. For the purpose of analyzing the results, it is of the essence to understand their mutual dependence.3.Humidity is the amount of water vapor, the gaseous state of water, in the air, and it is usually invisible. The maximum amount of water vapor in the air depends on air temperature. Absolute humidity (AH) is the water content in the air, i.e., the mass of water vapor included in a particular volume of air, expressed in g/mTemporal variation of signal strength, when exploring the results from our experiments in both summer and winter, made it evident that signal strength had both short-term  and long-term  variation. Interestingly, the variation was notably different in each period. Diurnal variation (day/night) was clearly apparent in summer, whereas seasonal variation was easier to detect in winter and between different seasons (summer/winter). These variations were not random, but were mainly cyclic, following a certain distinct pattern.This paper is organized into five sections. After the introduction, the paper presents the materials and methods. In the third section, the paper presents the results, while in fourth section the obtained results are discussed. Finally, the work is concluded in the fifth section. This section is intended to present the materials used in setting up our analysis and problem solving. We start by giving the main scientific arguments for our work, then we present the cochlear implant and make an important analysis of the electrical signal in the cochlear implant, and its behavior based on temperature and humidity, via MATLAB Simulink simulations. Previous works analyzed temperature effects on CMOS  Hall sensors  and prop® HFSS software, which is used for electro-magnetic simulations. Results were presented in papers [A precise three-dimensional model of a cochlear implant, together with extensive simulations, were previously performed in Ansoft Ansysn papers ,30,31, wHowever, the purpose of this paper was to model the electrical signal in the cochlear implant in a simulation based on discrete components (functioning blocks) in a Simulink environment, in remote powering mode, subject to various climatic changes. At this time, we also have the pleasure to introduce the unique idea of adding, for the very first time, temperature and humidity sensors in the circuit in order to compensate for these variations that greatly affect the quality of the sound signal, with arguments being given later on in this section. These temperature and humidity sensors  will give an idea of the electrical signal behavior with these climatic changes. This project aimed to improve the wellbeing of patients with cochlear implants who, for example, work outside, participate in outdoors activities, have a fever, etc. In these situations, the external medium changes in temperature and humidity. This influences the quality of the sound signal. The quality of the external sound is affected by temperature and humidity in the following ways. Hot air is less dense than the cold air and therefore the sound travels faster through the external medium. The attenuation of sound in air is also affected by humidity. The moist air (higher relative humidity) is less dense than dry air and, by consequence, like with the higher temperature, the sound travels more easily through that medium. Dry air absorbs more acoustical energy than the moist air.In essence, we have two media: the air from the exterior, where the sound propagates, and the internal medium, which should receive the undistorted information. Additionally, there is the synchronization of the sensors, one on the outside and the other on the inside, whose conditions do not change much. We are greatly interested in the effect of temperature and humidity on the correct functioning of the sensors, as well as their reliability. For example, there is an important difference between the level of humidity indoors and outdoors, as well as in different cities. The humidity and temperature also change with respect to the seasons, as well as from daytime to nighttime. There is likewise an increase in temperature in cities which have lakes . The quality of sound in air does not change with altitude directly, but does so through the agency of temperature, which, once again, tends to decrease if we go higher in altitude. The schematic diagram for a cochlear implant is illustrated in Some of the design goals of intracochlear electrodes are the insertion depth, coupling efficiency, and insertion trauma . It is kHerein, we will address issues such as the effect of temperature and humidity on the speed of sound associated to the quality of the signal sound, therefore understanding the impact on the reception of sound in the microphone of the cochlear implant, attenuation of the signal, and the decrease of sound quality.As we know, the speed of sound is affected by temperature and humidity; because it is less dense, sound passes through hot air faster than it passes through cold air. For this reason, temperature gradients cause refraction effects. Moreover, as sound propagates through the air, the air absorbs energy from the sound wave, attenuating (weakening) it. The effect is significant only at frequencies greater than 2 kHz, and increases with frequency. The attenuation of the sound in the air is affected by the relative humidity. Dry air absorbs far more acoustical energy than moist air. This is because moist air is less dense than dry air (water vapor weighs less than air) . The speed of sound in air varies depending on several factors, including humidity , and is Temperature will have an effect on microphone performance. Sensitivity levels can be directly affected by extreme environmental conditions. As the temperature approaches the maximum specifications of the microphone, its sensitivity specification will decrease. The owner will need to be aware of not only the operating temperature, but also the storage temperature of the microphones. If operated or stored in extreme conditions, the microphone can be adversely affected and will also require calibration more often .It is worth noting that the speed of sound changes with temperature, slightly with humidity, but not with air pressure (atmospheric pressure). Thus, it is only because of the decreasing air temperature, which decreases with altitude, that the speed of sound decreases.Changes in weather conditions affect radio signal strength. In terms of signal strength variation, temperature as a variable has a negative, linear effect on signal strength in general, while high relative humidity may have some effect, particularly when temperature is below 0 °C. The effect of weather conditions on response quality  were explored in several studies. The related variables used to measure radio signal strength, temperature, and humidity, were defined in . Some stAH (g/m3) can be defined, e.g., as a function of temperature and relative humidity as [t (°C) is the actual temperature, RH the actual relative humidity (%), m = 17.62, Tn = 243.12 °C, and A = 6.112 h Pa.The relationship between different weather variables, such as temperature and humidity, can be quite confusing. Temperature and humidity are connected to each other either directly or indirectly. For the purpose of analyzing the study results, it is of the essence to understand their mutual dependence. Absolute humidity idity as : (1)AHt,AH at various temperatures to be used as the input data in the module for adapting the frequency and the sound power, in order to obtain the necessary corrections for a normal standard sound.It is the basic formula used in the module for correcting atmospheric attenuation of sound, when traversing space through the air, from the emitting source to the patient’s ear. Equation (1) has the role of calculating AH, were calculated according to the above formula. The AH values which were obtained are AH  = 0.02 g/m3, AH  = 0.97 g/m3, AH  = 10.37 g/m3, and AH  = 14.7 g/m3.Formula validity. The temperature must be greater or equal to −40 °C, and less or equal to 100 °C. Several values for absolute humidity, In this section, the simulation of the cochlear implant using MATLAB Simulink is detailed, including system blocks, block parameters, some associated code, and the model hierarchy used to evaluate the electrical behavior of the cochlear implant. This tool allows us to rapidly and correctly investigate the device under discussion, as well as to assess the quality of the electrical radio signals.This paper discusses, for the first time in literature, the effect of humidity and temperature on the quality of processed sound. The calibration of sound was carried out on the real temperature and on the existing humidity in the sound emission space. Prior to this, these considerations were not taken into account when designing cochlear implants.The responses of the sensors to the change of temperature (temperature effect) and to the change of the environmental conditions regarding the humidity (effect of humidity) were highlighted by numerical simulation. These evidently marked the alteration of sound quality depending on the change of environmental conditions, namely the change of temperature and ambient humidity.The designed and developed conceptual blocks, such as the cochlear implant signal source block and cochlear implant signal from Workspace block, were both represented in MATLAB Simulink. The first concept, made to work like source type selection, was used to change between a voice recording and a “chirp” sound, and a DC blocking filter was applied at the input signal.In addition, the cochlear implant filter bank block was represented in the MATLAB Simulink so that signal processing of the input source would use two filter types: FIR (finite impulse response) and IIR (infinite impulse response). To increase the degree of confidentiality, the FIR filter was applied in a cascade to the eight frequency bands.Finally, the denoise stage block was schematically represented, together with stimulation pulse generator block.In the standard cochlear implant, an adequate frequency range can be set from 70–350 Hz up to 3500–8500 Hz, but as far as limits are considered 75 Hz is the lower limit and 8500 Hz is the upper limit. However, it is necessary to find the best frequency range for CI speech perception, thus, we found the best frequencies in the range considered optimal for very clear language transmission. Making an analysis almost exhaustive based on several frequencies in the simulations demonstrates that comb filtered speech  can be used in the modeling of CI speech perception. Thus, we carried out this study of comb filtered speech recognition in eight frequency ranges, chosen as reference intervals for the whole process. ® to perform multidomain modeling and simulation, because it can reuse models across environments to simulate how all parts of the system work together. With Simulink, we can do the following:Model our system across domains using specific tools and prebuilt blocks;Develop large-scale models through componentization with reusable system components and libraries;Combine our models into one system-level simulation even if they were not built in Simulink;Run massive simulations in parallel on a multicore desktop, computer cluster, or the cloud, without writing large amounts of code;Share simulations as standalone executables, web apps, and Functional Mockup Units (FMUs).Here, we briefly present Simulink software, including what it is in principle and what it can be used for. In general, engineers and scientists use SimulinkIndustry-specific applications can also be designed in Simulink using prebuilt blocks, so we do not have to create them ourselves. For example, aircraft propulsion systems can be designed with Aerospace Blockset™, or audio and video systems with Signal Processing tools, as in our case. As for the math behind the application Simulink, we will refer to the simulation applications for making graphics. Standalone executables can be complete simulation apps that use MATLAB graphics and UIs designed with the MATLAB App Designer. To provide browser-based access to a deployed simulation, it will create a web app and host it with the MATLAB Web App Server™. Standalone Functional Mockup Units (FMU) are binaries that adhere to the Functional Mockup Interface (FMI) standard and can be used in an external simulation environment.A standalone executable is a program that does not depend an Objective Caml installation to run. This facilitates the distribution of binary applications and robustness against runtime library changes across Objective Caml versions. ocamlrun. For example, imagine the file example.ml is as follows: The Objective Caml native compiler produces standalone executables by default. Without the custom option, however, the byte code compiler produces an executable which requires the byte code interpreter Let f (x) = x + 1;Print_int ;Print_newline (…);Then the following command produces the (approximately 8 k) file example.exe: Ocamlc -o example.exe example.mlThis file can be executed by the Objective Caml bytecode interpreter: $ ocamlrun example.exeThese are some of the subroutines defined as mathematical applications in the software used to run programs in Simulink.The purpose of the filter bank signal processing block was to decompose the input speech signal into eight overlapping subbands. There is more information contained in the lower frequencies of speech signals than in the higher frequencies. To get as much resolution as possible where the most information is contained, the subbands were spaced in such a way that the lower-frequency bands were narrower than the higher-frequency bands. The advanced CI system is capable of detecting a change in the background noise with no user intervention and changes the noise suppression parameters to previously determined (during training) optimal parameters for that particular background noise. A block diagram with a first-order low-pass filter, which is used at the end to smooth out any fluctuations, was proposed.mx(n), md(n), and my(n), respectively, where m denotes the window number. A priori and a posteriori SNRs  for the speech spectral estimation are given as follows: mξ(k) denotes the a priori SNR, mγ(k) denotes a posteriori SNR at the frequency bin k, dλ denotes the noise variance, and xλ denotes the clean speech variance. Frequency bin is a discretized frequency, which transforms continuous frequency into a discrete one. A priori SNR and a posteriori SNRs are obtained by using the “decision-directed” approach as: ddα is a smoothing parameter [minξ is a small number greater than 0.Let us consider an additive noise scenario, with clean, noise, and noisy received signals represented by arameter ,43, and SNR is defined as the ratio of signal power to the power of background noise. According to ,43, the In the present study, we used eight bands for the eight frequency ranges, from the lower limit of 70 Hz to the upper limit of 8500 Hz. The eight frequency ranges chosen were the following: 70–250 Hz, 70–350 Hz, 350–6500 Hz, 250–6500 Hz, 70–6500 Hz, 350–8500 Hz, 250–8500 Hz, and 70–8500 Hz. We used the model of 8-channel implants. The best results of comb filtered words frequency were recognized in the frequency range of 250–6500 Hz, with minimal recognition in the broadest frequency range.Since the discovery of multi-channel devices, research has demonstrated that hearing performance improves with increasing numbers of spectral channels ,45,46. HAt equidistance on the basilar membrane, distribution spectral bands, in accordance with normal tonotopical organization of the cochlea , was choThe cochlear implant block representation was effectuated in MATLAB Simulink, and contained an input source, cochlear speech processor, filter bank signal processing with designer filter bank, FIR and IIR filter bank response, an optional denoise stage, and electrical pulses with a pulse generation by 8 channels.Thereby, the cochlear implant signal source block, (represented in MATLAB Simulink) was introduced, where source type selection was used to change between a voice recording and a “chirp” sound, and again on the DC blocking filter, which was applied to the input signal. Evidently, a major focus on detailing software was associated with the block structure of the input signal source, when the FIR filter was applied in cascade to the 8 frequency bands .In the following, the most important functional blocks of the electrical model of the cochlear implant will be described. Among the most relevant was the cochlear implant signal from the Workspace block representation in MATLAB Simulink. In this description we will discuss the sampling of the input signal, which was done at a frequency of sampling set at the fixed value of fs = 22,050 Hz.Two more of the modules used included the cascade FIR bank block representation, with three successive cascaded high band/low band blocks, and the IIR filter bank block representation, with the IIR filter bank (with 8 outputs), the rectifier (with 8 inputs), and the supplementary block of 8 biquads applications.This section presents the simulation results and interprets them.The filter bank frequency specifications, with normalized band edges in the  interval, were as follows: channel 0: ; channel 1: ; channel 2: ; and channel 3: . In this example, the four low-frequency bands were equally spaced, while each of the four remaining high-frequency bands was twice the bandwidth of its lower-frequency neighbor. The filter bank frequency specifications, with normalized band edges in the  interval with twice the bandwidth, were as follows: channel 4: ; channel 5: ; channel 6: ; and channel 7: . In order to examine the frequency contents of the eight filter banks, we ran the model using the chirp source type in the input source block, as shown in Further on, we applied the FIR filter. In the following, we selected the speech input source for the simulation and ran the MATLAB simulation with various parameters, selecting from a range of filters, noise sources, and denoise functions. This section highlights the novelty of the investigation of climatic parameters (humidity and temperature) through the addition of such sensors in the discrete components circuit simulation. The sensors were simulated using constants integrated into the simulation environment, as can be seen in T = 36 °C) and relative humidity (RH = 40%). Further on, in The atmospheric attenuation of sound was computed for the input source and applied for different temperature and humidity values. For example, Details of the modified input source diagram, showing the temperature and humidity effects blocks, which were added in the multiplication stage as noise, are included in T = 0 °C and RH = 0%. Further, T = 36 °C and RH = 40%. In order to simulate the influence of humidity and temperature, an atmospheric attenuation of sound model was used. T = 36 °C and RH = 40% to T = 0 °C and RH = 0%. A more detailed analysis of these results will be carried out in the dedicated discussion section.T = 0 °C and RH = 0%, compared to three different temperatures and humidities, namely T = 20 °C and RH = 20% , PRR (packet reception ratio), SNR , and LQI .In An additional correction step can be applied using a denoise function that corrects the temperature and humidity influence on the system, as in At the beginning of the processing chain, where there is an external microphone, the sound waves arrive already affected by their way through the air and the distance from the source to the ear, which will then have to be processed electronically to reach the optimal standard values of the cochlear implant type used.A Simulink diagram of the complete simulation featuring the microphone input, the temperature and humidity sensor, as well as the additional filters and denoise blocks, is displayed in The simulation of a cochlear implant using MATLAB Simulink started by organizing a simulation setup of the cochlear implant, where a source type selection was used to change between a voice recording and a “chirp” sound. In addition, a DC blocking filter to the input signal was applied.In a natural sequence, simulation stages were presented in detail, among which the most important ones included the cochlear implant signal source block representation in MATLAB Simulink, the denoise stage block representation, and, finally, the stimulation pulse generator block. Thus, source type selection was used to change between a voice recording and a “chirp” sound, while a DC blocking filter was applied to the input signal. Special attention was paid to simulation code with the application of the temperature and humidity influence via the air attenuation function. T = 0 °C and RH = 0% and at T = 36 °C and RH = 40% was graphically represented. The atmospheric attenuation of sound was computed for the input source and applied for different temperature and humidity values. Moreover, the attenuation of temperature and humidity of the input signal at Propagation of sound close to the ground outdoors (at levels of 1–2 m) involves geometric spreading, air absorption, and interaction with the ground. The principle effect is owed to air absorption, which is manifested by proportion of sound energy that is converted to heat as a sound wave travels through the air.p at distance x from a position where the pressure is 0p is given by 0expp = p(−αx/2). In previous formulas, p was the pressure at temperature T (absolute temperature of the atmosphere in degrees Kelvin), and 0p was the reference atmospheric pressure (1 atm = 1.01325 × 105 Pa). The attenuation coefficient α, for air absorption, is dependent on frequency, humidity, temperature, and pressure.The resulting air absorption becomes significant at high frequencies and at long range, so air acts as a low-pass filter at long range. For a plane wave, the pressure Absolute humidity (AH) was an important factor in the diurnal variation and usually peaked in the afternoon. The diurnal variations were greatest in the summer (from 30% to 70%). It should be noted, that the use of (arithmetic) mean values of atmospheric absorption may lead to overestimates of attenuation when attempting to establish worst-case exposures for the purposes of environmental noise impact assessment.T = 0 °C and RH = 0% and at T = 36 °C and RH = 40% was graphically represented. The atmospheric attenuation of sound was computed for the input source and applied for different temperature and humidity values. Moreover, the attenuation of temperature and humidity of the input signal at T = 36 °C is the body temperature and RH = 40% is the average humidity of concert halls and of air-conditioned rooms. At the same time, they are considered as the average for reference values.These values of temperature and humidity were used because As an important observation, in the power graphs, as a function of normalized frequency (Power (dB) versus Normalized Frequency), power decreased rapidly until to a frequency of 0.6 (×π rad/sample), followed by a somewhat significant increase around a frequency value of 0.8 (×π rad/sample).Worth mentioning are also the results of the electrical pulse generator for each of the 8 channels with the IIR filter, Gaussian noise, temperature and humidity influence, and the denoise block active.Following the comparison, we can consider that for the first 4 channels (channels 0–3) we had a maximum fluctuation around the 1 s value (marked on the abscissa), and for the last 4 channels (channels 4–7) we had massive fluctuations for at least three values of time measured on the abscissa , as happened in channel 6 for the values 1.7 s, 2.9 s, and 4 s.To obtain the results in this project, a thorough understanding of MATLAB Simulink software was necessary. MATLAB Simulink was used to characterize the electrical behavior of the cochlear implant and to assess the audio signal and quantify the atmospheric perturbation impact on the signal quality. A simulation setup of the cochlear implant, where a source type selection was used to change between a voice recording and a “chirp” sound, was used. In addition, a DC blocking filter was applied to the input signal. Taking the initial intake data into account, the cochlear implant signal from the Workspace block representation in MATLAB Simulink, when the input sound was sampled, was included.T = 0 °C and RH = 0% and at T = 36 °C and RH = 40% was graphically represented. It can be easily seen that in the power graphs as a function of normalized frequency (Power (dB) versus Normalized Frequency), the power decreased rapidly until to frequency 0.6 (×π rad/sample), followed by a somewhat significant increase around the frequency value of 0.8 (×π rad/sample). Filter bank signal processing block was introduced, the role of which was to decompose the input speech signal into eight overlapping subbands.A simulation code with the application of the climatic influence, via the air attenuation function, was developed. Thereby, the attenuation of temperature and humidity in the sound atmospheric circulation of the input signal at The results of the electrical pulse generator for each of the 8 channels with an IIR filter, Gaussian noise, temperature variation, humidity influence, and by control of denoise block activity were thus obtained accurately. For the first 4 channels, we had a maximum fluctuation around 1 s and for the last 4 channels we had massive fluctuations for at least three values of time. For the sake of succinct presentation and article volume limitation, we have selected to present only two channels (channel 0 and channel 7) out of the eight. It can be said now that the novelty consists in the very idea of adding these sensors to a cochlear implant and that we obtained a modified signal, which can then be considered for future compensation. Electronic sound processing to change the parameters affected by air travel, from the sound source to the patient’s ear, is a technical novelty, as shown in this article. In the present, it was accepted and mastered in the serial production of cochlear implants by important players from the hearing aids industry , which now are announcing massive efforts in the future of the development of new cochlear implants.As for future directions, the effective production of the circuit with discrete components and its subsequent testing should be carried out.


Electrically conductive, highly flexible graphene membranes hold great promise for harvesting energy from ambient vibrations. For this study, we built numerous three-dimensional graphene ripples, with each featuring a different amount of compression, and performed molecular dynamics simulations at elevated temperatures. These ripples have a convex cosine shape, then spontaneously invert their curvature to concave. The average time between inversion events increases with compression. We use this to determine how the energy barrier height depends on strain. A typical convex-to-concave curvature inversion process begins when the ripple’s maximum shifts sideways from the normal central position toward the fixed outer edge. The ripple’s maximum does not simply move downward toward its concave position. When the ripple’s maximum moves toward the outer edge, the opposite side of the ripple is pulled inward and downward, and it passes through the fixed outer edge first. The ripple’s maximum then quickly flips to the opposite side via snap-through buckling. This trajectory, along with local bond flexing, significantly lowers the energy barrier for inversion. The large-scale coherent movement of ripple atoms during curvature inversion is unique to two-dimensional materials. We demonstrate how this motion can induce an electrical current in a nearby circuit. Recent developments in low power-consuming circuit designs have reduced input power to nanowatts in active mode and picowatts in standby mode. In addition, some applications operate with an ultra-low duty cycle, which further lowers the overall power requirement . These bMicroelectromechanical systems (MEMS) are an attractive approach to energy harvesting. For example, a 14 nm thick silicon nitride cantilever is extremely flexible and will vibrate under the slightest influence. The kinetic energy of the cantilever can be converted into stored electrical charge using an electrical circuit with a rectifier and a capacitor. Materials thinner than silicon nitride would be better, as the flexural rigidity decreases with thickness to the third power. The ultimate thinness is found with two-dimensional (2D) materials and graphene is the most durable of these. A graphene membrane can be ten times thinner than silicon nitride and, therefore, 1000 times more flexible ,10. In aWhen graphene is suspended, the membrane can be held under tension or compression. When taut, the vibrational modes produced are the well-studied drumhead vibrations. For graphene, these modes have very high frequencies . One potWhen graphene was first suspended in the early 2000s ,26,27,28Some dynamic properties of ripples have been studied using scanning probe microscopy (SPM). However, the shape transformation details of a ripple during curvature inversion cannot be imaged using SPM, as the process takes place over too large an area and too short a time for SPM. Molecular dynamics simulations (MDS), on the other hand, are an ideal method for investigating the evolution of ripple inversion. In this study, we used MDS to quantify the dynamics of graphene ripples as they invert their curvature. To achieve this, we first determined the energy required to compress and stretch graphene. Second, we used the strain–energy relationship to build a double-well potential for a particular ripple, then investigated the average inversion rate as a function of strain. This allowed us to report the energy barrier as a function of compressive strain. Finally, we derived a detailed picture of the shape transformations the ripple undergoes during the curvature inversion process through cross-sectional analysis.We first created a flat circular lattice of about 7000 carbon atoms arranged in a honeycomb structure. The potential energy of the lattice was found for a number of different bond lengths in LAMMPS using the AIREBO C-C potential at zero Kelvin. Atomic pairs were set to interact within three standard deviations of their equilibrium distance ,41. The We constructed three-dimensional (3D) ripples starting from the flat circular lattice and using a bond length smaller than 0.140 nm. Next, inside a radius of 7.5 nm, a third dimension was added to the carbon atoms using the following cosine function:This formula comes from a simple geometric analysis and computes the strain using the diameter and smooth arc length of the cosine ripple. After forming the ripple, we retain a 1.5 nm wide graphene annulus around the ripple at zero height. The annulus is always fixed in place, its position defines the The zero Kelvin potential energy of a −0.7% strained ripple is the double-well potential, as shown in ry (DFT) . Note thurvature .Next, we constructed numerous 15 nm diameter ripples, each featuring a different strain, using the method described above. After ripple construction, the ripple temperature was set to 3000 K and maintained at that temperature using a Nosé–Hoover thermostat. The equilibrium bond length changed from 0.140 nm at zero K to 0.143 nm at 3000 K. The equations of motion were integrated using a time step of 1 fs. The system was equilibrated for 0.5 ns starting from the initial cosine shape. The subsequent trajectory from a production run of 40 ns was used for analysis in this study.The cross-sectional profile of a typical equilibrated cosine-like shaped ripple is shown in We tracked the central height of the ripple in time. One such example is shown in We narrowed the strain values to those that yield bistable ripples that invert their curvature on a time scale accessible for this study. We then created 10 more ripples with similar but varying strains and ran 40 ns MDS for each. For all these simulations, we found the average time between curvature inversions, then plotted this time versus the calculated strain found using Equation (2), as shown in rs’ rate :(4)〈t〉∝eThe best fit to the average time between flips yields Using the energy barrier results shown in To study the shape transformations, we first identified all the inversion events in a particular ripple simulation by plotting the central height over time, as shown in 2) are shown for each function in time, as the ripple inverts. Early on, the goodness-of-fit for cosine is close to one, while sine is close to zero, as shown in Next, we analyzed the shape of the ripple in time. This was carried out by using regression analysis on the cross-sectional datasets taken in both the x- and y-directions. For convenience, we redrew The primary path for the ripple curvature inversion process as determined by MDS is illustrated in For comparison, we calculated the energy barrier from elastic theory ,47,48. TThe timescale for the curvature inversion process is remarkably short, at about 20–30 ps. During this time, the ripple height changes by 1.6 nm, which is significantly larger than the bond length. This yields an average speed of about 700 m/s. It is also noteworthy that the carbon atoms are moving together. This type of collective movement is like snap-through buckling ,49,50,51We can utilize the MDS data to predict the current produced by the thermal movement of the graphene. We imagine forming a parallel plate capacitor with a time-varying capacitance given by We studied the dynamics of graphene ripples using molecular dynamics simulations (MDS). The ripples are made by compressing flat graphene, then allowing the graphene to relax into the third dimension. For a range of strain values, the ripples are bistable and invert their curvature on a timeframe accessible with MDS. The transition rate for barrier crossing was found to be exponential in strain. Using the average transition rate, along with Kramers’ formula, we determined the height of the barrier in the double-well potential as a function of strain. The energy barrier is much lower than what one would expect if the ripples uniformly flattened before crossing. Using cosine and sine regression analysis on cross-sections of the ripple, we showed that the ripple distorts its shape to allow only part of the ripple to pass through the fixed frame at a time. Finally, we used the movement of the graphene to create a variable capacitor, which then induced a current to flow in a nearby circuit, thereby quantifying the energy harvesting promise of this system.