Small secreted proteins (SSPs) are less than 250 amino acids in length and are actively transported out of cells through conventional protein secretion pathways or unconventional protein secretion pathways. In plants, SSPs have been found to play important roles in various processes, including plant growth and development, plant response to abiotic and biotic stresses, and beneficial plant–microbe interactions. Over the past 10 years, substantial progress has been made in the identification and functional characterization of SSPs in several plant species relevant to agriculture, bioenergy, and horticulture. Yet, there are potentially a lot of SSPs that have not been discovered in plant genomes, which is largely due to limitations of existing computational algorithms. Recent advances in genomics, transcriptomics, and proteomics research, as well as the development of new computational algorithms based on machine learning, provide unprecedented capabilities for genome-wide discovery of novel SSPs in plants. In this review, we summarize known SSPs and their functions in various plant species. Then we provide an update on the computational and experimental approaches that can be used to discover new SSPs. Finally, we discuss strategies for elucidating the biological functions of SSPs in plants. In plants, SSPs have been shown to play important roles in various biological processes such as growth, development, reproduction, resistance to abiotic and biotic stresses, and beneficial plant–microbe interactions5. In general, 30,000–40,000 protein-encoding genes have been reported in individual plant genomes6. Yet hundreds to thousands of SSPs are potentially overlooked in a single plant genome7 for two reasons: (1) the SSP space is occupied by many proteins with a length of less than 100 aa8 and (2) 50% of the discovered secreted proteins in plants do not have a known signal peptide9, both of which create difficulties in SSP annotation using traditional computational approaches12.Plant small secreted proteins (SSPs) are less than 250 amino acids (aa) in length and can be actively transported out of plant cellsIn recent years, the increasing volume of genomics data and the continuously evolving machine learning algorithms have boosted the effectiveness of computationally predicting SSPs. Meanwhile, advances in functional genomics research have accelerated the experimental validation of predicted SSPs and the elucidation of their functional roles. As a result, SSP-focused research has become an emerging area with great potential for growth, as reflected by the rapidly increasing number of publications on SSPs in various organisms, including animals, microbes, and plants. Here with a focus on plant SSPs, we first summarize the current understanding of SSP biosynthesis and secretion. We then discuss the structures and functions of representative SSPs that are well characterized in various plant species, including model species, food crops, bioenergy feedstocks, and horticultural plants. We also highlight computational tools, experimental approaches, and their combinations used to identify novel SSPs. Finally, we discuss the strategies that have been or can be used to explore the functions of SSPs.13. SSPs derived from nonfunctional precursors can be further classified into three subcategories based on features of their mature forms. SSPs belonging to the first subcategory typically consist of less than 20 aa in their mature forms which have few or no cysteine (Cys) residues and contain one to several types of post-translational modifications (PTM), such as tyrosine (Tyr) sulfation, proline (Pro) hydroxylation or Pro glycosylation. Therefore, these SSPs are named PTM SSPs. Several well-studied PTM SSPs in Arabidopsis thaliana are involved in plant growth and development, including CLAVATA 3 (CLV3), C-TERMINALLY ENCODED PEPTIDE 1 (CEP1), PLANT PEPTIDE CONTAINING SULFATED TYROSINE 1 (PSY1), and ROOT MERISTEM GROWTH FACTOR 1 (RGF1)15. The second subcategory features SSPs with mature peptides that contain an even number (often ranging from 2 to 16) of Cys residues. These Cys residues are essential for forming the disulfide bonds in the active mature SSPs. Most of the known Cys-rich SSPs are involved in plant–microbe interactions, such as PLANT DEFENSINs (PDFs), nonspecific LIPID TRANSFER PROTEINS (nsLTPs), and KNOTTINs. Meanwhile, several Cys-rich SSPs have been found to regulate plant development, such as S-LOCUS CYSTEINE-RICH PROTEIN/S-LOCUS PROTEIN11 (SCR/SP11) and LUREs15. The third subcategory contains non-Cys-rich/non-PTM SSPs, which often lack the NSS in their precursor forms and contain Cys, Pro, Tyr, glycine (Gly), lysine (Lys), or other amino acids with dominant roles in conferring the activity of the mature SSPs. SSPs within this subcategory have been primarily found to participate in plant defense responses, with SYSTEMINS (SYS), GRIM REAPER PEPTIDE (GRIp), and PLANT ELICITOR PEPTIDES (PEPs) being the representative examples11.In plants, SSPs have been found to be produced via multiple alternative pathways, as illustrated in Fig. A. thaliana, Zea mays, Oryza sativa, and Vigna unguiculata, the Glycine max SUBTILASE PEPTIDE (Gm-SUBPEP), and the Solanum lycopersicum CYSTEINE-RICH SECRETORY PROTEINS, ANTIGEN5, and PATHOGENESIS-RELATED 1 PROTEINS derived peptide 1 (CAPE1)11.In the past decade, a growing number of plant SSPs has been found derived from functional protein precursors, such as INCEPTINs from 17. Some known examples of such SSPs include the uORF2-encoded sucrose control peptide (SC-PEPTIDE) that is required for sufficient sucrose-induced repression of translation in A. thaliana18, the miPEP171b that regulates root development in Medicago truncatula19, and ENOD40s that are involved in sucrose use in nitrogen-fixing nodules in G. max20.In addition to being processed from larger protein precursors, plant SSPs can be directly encoded by small open reading frames (sORFs), which can sometimes locate upstream of the main ORFs , within presumed non-coding RNAs , or within primary transcripts of miRNAs. These SSPs are denoted as “short peptides encoded by sORFs”, “sPEPs”, or “nonprecursor-derived peptides”23. The majority of plant SSPs with an NSS are secreted via the conventional protein secretion (CPS) pathway  and further sorted through the Golgi or the trans-Golgi network (TGN). Modifications, such as glycosylation that are required for SSP maturation, occur when SSPs travel through the Golgi. Finally, the mature SSPs are delivered to the apoplast via secretory vesicles or granules24.Our knowledge of plant SSP secretion largely overlaps with our understanding of protein trafficking and secretion, which follows several different mechanisms23 while traveling to the extracellular space, usually upon pathogen attack or the exposure to other biotic or abiotic stress conditions24. The simplest UPS route directly transports these proteins from the ER to the plasma membrane (PM). Alternative UPS routes utilize vesicular carriers, including the secretory multivesicular body (MVB) and vacuole, that can fuse with the PM to release their contents into the apoplast/extracellular space22.However, some NSS-containing SSPs bypass the CPS pathway. They follow unconventional protein secretion (UPS) routes Fig. 22,23 whi21, cannot be processed by the CPS. These proteins have been proposed to be secreted through the excyst-positive organelle (EXPO)—a double-membrane organelle whose formation is Golgi- and TGN-independent. The EXPOs can fuse with the PM to secrete LSPs , which represent a large proportion of the plant secretomeA. thaliana is considered to be better annotated and characterized than other plant species, we focus on known SSP families found in A. thaliana. Also, we discuss SSPs that have been identified from several important plant species, including Z. mays, O. sativa, S. lycopersicum, M. truncatula, and Populus trichocarpa. A large number of SSPs have been computationally predicted in plants, as demonstrated in public databases, including OrysPSSP5, PlantSSP25, and MtSSPdb3. For instance, according to the database PlantSSP25, there are 2451, 5373, and 3216 predicted SSPs, which are less than 200 aa in length with NSS, in A. thaliana, O. sativa, and P. trichocarpa, respectively. These predicted SSPs account for 6.9%, 8.0%, and 7.1% of all the annotated proteins (including splice variants) in the A. thaliana (version TAIR10), O. sativa (version MSU6.1), and P. trichocarpa (JGI v2) genome, respectively. More recently, with the release of the reannotated M. truncatula genome, 4439 genes  were predicted to encode SSPs that are less than 230 aa with NSS but not transmembrane regions3. Although interest in decoding genomes for potential SSPs has been growing substantially in recent years, only a limited number of SSPs have been experimentally characterized, which are distributed among approximately 50 gene families13, with their representative members listed in Table Because the genome of model herbaceous plant 26. Some of the known SSPs in plants have well-defined 3D structure, as demonstrated in Fig. 27. The β-turn-like conformation, for example, which is a feature of CEP1, is associated with biological activity28. On the other hand, enzymatic maturation processes produce bioactive Cys-rich SSPs with correct oxidative folding under oxidative conditions byProtein function is dependent on a well-defined and folded three-dimensional 3D) structure and intrinsically disordered regions (IDRs), which are not likely to form a defined 3D structureD structu29. SCR/SP11 contains an α/β sandwich motif connected by L1 loop that serve as binding site for specific receptors30. LTP has four α-helices, three loops, and four disulfide bridges with eight conserved cysteines4. EPF includes one loop and three disulfide bonds, which contains two antiparallel β-strands connected by a 14-residue loop31. However, it has been estimated that 10% of secreted proteins are intrinsically disordered proteins (IDPs), with >70% of their length being IDRs26. For example, LTP1 from A. thaliana contains a defined 3D structural domain ain Fig.  and withain Fig.  but LEA4red Fig. .Fig. 4Ex32. In terms of meristem maintenance, CLE14 and CLE40 expression has been observed in A. thaliana root meristematic zone and found to play roles in controlling meristematic activity as well as cell number34. Although CLE43 does not affect root apical meristem growth in A. thaliana35, its homologs, BnCLE43a and BnCLE43b, were found in Brassica napus could repress A. thaliana root growth when synthetic peptides were added to the culture medium36. In A. thaliana, both CLE9 and CLE10 control xylem differentiation through regulation of the cytokinin signal pathway37, and CLE41 can drive vascular cell division38. In contrast, PtrCLE20 identified in vascular cambium cells of P. trichocarpa was shown to restrain cell division, resulting in an inhibition of lateral growth of the stem39. Besides the impact on vegetative tissues or organs, SSPs can affect flower development. For example, CLV1 acts with CLV3 to avoid enlarged meristems and extra floral organs in A. thaliana40. The pollen-specific SlPRALF gene that encodes a 129 aa preproprotein was recognized to negatively regulate pollen tube elongation in S. lycopersicum41.Some of the known SSPs are associated with multiple aspects of plant growth and development. During these processes, most SSPs act as signaling molecules that are involved in cell-to-cell communication by binding membrane receptors and coordinating responses with plant hormones42. Induced SSPs have been observed in many stress responses in plants, including some SSPs recognized as hormone-like molecules43. SSPs act quickly and synergistically at low concentrations in reaction to different stresses44.To sense and respond to various stresses, plants have evolved complex signaling and defense mechanismsS. lycopersicum was the first wound response signaling peptide46. When plants are attacked by herbivores or pathogens, a series of defense signals and pathways can be induced by SYSTEMIN through its interaction with SYSTEMIN RECEPTOR 1, which includes stimulation of PROTEASE INHIBITOR production, as well as enhancement of ethylene and jasmonic acid biosynthesis48.SSPs are involved in a variety of biotic stresses responses in diverse plant species. For example, an SSP called SYSTEMIN identified in O. sativa suspension cells cultured with bacterial peptidoglycan and fungal chitin, increased the abundance of phenylalanine ammonia-lyase 1 (PAL1) and activated mitogen-activated protein kinases (MAPKs), which are known to be associated with plant immunity49. Two pathogen-responsive SSPs, TaSSP6 and TaSSP7, are responsible for resistance to Septoria tritici blotch, a severe foliar disease caused by the fungal pathogen Zymoseptoria tritici in Triticum aestivum50. In Z. mays, Zip1 was demonstrated to trigger plant immunity by activating salicylic acid defense signaling51.Plant SSPs can initiate immune responses and increase resistance to pathogens. For example, an SSP called IRP, which was identified from the proteomic analysis of A. thaliana, is induced under dehydration, which triggers ABA biosynthesis in leaves to prevent water loss by regulating stomatal closure52. In A. thaliana roots, AtRALFL8 encoding a SSP can be induced not only by nematode infection but also by drought stress, leading to cell wall remodeling53. To determine extracellular proteins that respond to heat stress, a quantitative proteomic analysis was conducted by collecting proteins from heat-tolerant Sorghum bicolor cell suspension culture medium, resulting in the identification of an SSP named germin protein, which was highly induced at the protein level54. Another example is the small peptide AtPep3 encoded by AtPROPEP3, which has been shown to play an important role in salinity stress tolerance in A. thaliana55.SSPs are also involved in responses to abiotic stresses. For example, CLE25, found in 58. However, studies on the identification of plant SSPs as effector proteins that affect microbes have been very limited2. Plants can adapt to a low availability of nutrients by altering root system architecture, with some can form symbiotic associations with rhizobia and mycorrhizal fungi60. In legumes, SSPs can affect root development and rhizobial–legume symbiosis62. CLE family members have been characterized in different species, such as CLE12 and CLE13 in M. truncatula, CLE-RS  1/2/3 in Lotus japonicus, and RIC (rhizobium-induced CLE) in G. max. These SSPs appear to be involved in the negative systemic autoregulation of the nodulation pathway and inhibit newly formed nodules in roots63. Conversely, in M. truncatula, CEP1 was found to modulate lateral root formation and increase the number and size of nodules60. When L. japonicus was inoculated with the arbuscular mycorrhizal (AM) fungus Rhizophagus irregularis, in comparison with formation of nodules in L. japonicus, alternate CLE genes, including LjCLE19 and LjCLE20, were upregulated in roots, indicating that different signaling pathways are involved in AM and root nodule symbiosis64. In addition, a recent study reported that SSPs produced by P. trichocarpa were induced when co-culture with ectomycorrhizal mycorrhizal (EM) fungus Laccaria bicolor and several P. trichocarpa SSPs could enter fungal hyphae when they were exposed to L. bicolor2, suggesting plant SSPs may mediate ectomycorrhizal symbiosis as well.SSPs play important roles in cross-kingdom interactions. It is widely accepted that SSPs generated from plant-associated microorganisms  can be used as effector proteins to promote plant microbial colonization65. In the recent decade, progress in the development of computational methods for gene prediction has contributed to the identification of numerous sORFs in plants. For example, sORF finder is a tool for identifying putative small sORFs between 10 and 100 amino acids based on significant selective constraints, which works well for predicting sORFs in plant genomes66. Small Peptide Alignment Discovery Application is a homology-based program which can accurately identify and annotate genes in a given family, including sORFs in plants67. One caveat of these in silico sORF prediction tools is that the predicted sORFs may be pseudogenes. To address this issue, transcript expression data generated by transcriptome sequencing (RNA-seq) can be used for identifying functional sORFs, as demonstrated in SSP discovery in P. trichocarpa10. Transcript sequences obtained from RNA-seq data can be either protein coding sequences (CDS) or non-coding RNAs69. Finally, using DeepCPP, a new deep neural network-based tool, aims to predict short sequences with coding potential70.In general, there are two main steps to computationally predict SSPs in plant genomes, i.e., predicting small proteins encoded by sORFs and subsequently evaluating their ability to be secreted. A large number of sORFs can be found by locating in-frame start and stop codons in the plant genomes. However, annotations of sORFs have been largely overlooked because such short sequences were initially classified as random nonsense occurrences71. However, since an NSS is common in several types of membrane proteins, membrane spanning proteins with both predicted signal peptide and at least one transmembrane region should be excluded72. MEMSAT-SVM73 can be used for transmembrane helix topology prediction, and SPOCTOPUS74 is designed for predicting both signal peptide and transmembrane topology. Because the existence of certain numbers of NSS-containing proteins follow UPS routes, SecretomeP has been constructed and is a ML algorithm to predict unconventionally secreted proteins75. In addition, the number of Cys residues and their arrangement have been used to predict Cys-rich SSPs without signal peptide76. In some studies, an additional criterion, such as the lack of endoplasmic reticulum-retention motif, is taken into consideration for secretion prediction. Several authors recommend that small proteins containing C-terminal KDEL or HDEL motifs should be excluded as non-SSPs77. Protein secretion mediated by conventional  or unconventional  mechanisms can be evaluated using various tools for predicting multiple protein subcellular localizations, such as LocTree3 (refs. 81), CELLO82, YLoc83, DeepLoc84, and TargetP85. Also, ML-based methods have been developed recently for predicting both conventional and unconventional secretion, e.g., ApoplastP86, BUSCA87, and Plant-mSubP88. A pipeline integrating the best methods for computational prediction of SSPs is proposed in “Integrative approaches for discovery of SSPs”.The potential for secretion of small proteins has been determined using tools based on specific algorithms, in particular many use newly developed machine learning (ML) approaches Table . To predA. thaliana by liquid chromatography-mass spectrometry (LC-MS) analysis89. The feasibility of this system was tested initially by detecting a known small secreted peptide CLE44 in the medium using transgenic A. thaliana overexpressing the CLE44 gene. Computational prediction of SSP secretion can also be verified through MS analysis of extracellular proteins. For example, protein MS has been successfully used to identify plant immune response proteins that are secreted into apoplastic space in A. thaliana leaves90. Proteomic analyses of secretomes have identified secreted proteins in O. sativa91, Hippophae rhamnoides92, S. bicolor54, Solanum chacoense93, and S. lycopersicum94. Such global analyses of plant secretomes could facilitate the discovery of SSPs. However, proteins containing IDRs of sufficient length tend to be more susceptible to degradation, resulting in lower protein abundance26. This may cause a problem for studying plant SSPs that contain a large portion of IDRs using proteomics approaches because MS has lower sensitivity than transcriptome sequencing. To increase the sensitivity of detecting SSPs in plants, it is necessary to enrich for IDRs containing proteins and low molecular weight proteins in protein extract using gel filters95 or ultrafiltration devices97.The putative SSPs predicted using computational approaches described in “Computational approaches for discovery of SSPs” need to be verified using experimental approaches to provide protein-level evidence. To address this issue, protein mass spectrometry (MS) data can be used to determine (1) whether the predicted SSPs are truly expressed proteins in extracellular localization and (2) whether the predicted SSP sequences are full length or partial fragments of longer protein sequences. For instance, a novel 15 aa secreted peptide named CEP1 encoded by AT1G47485 was effectively identified in 98, and the gene fusion constructs can be tested for secretion of reporter-tagged SSPs using agroinfiltration-based transient gene expression99 or stable transformation in plants. The secretion of SSPs has been tested using the yeast expression system as well2.Besides plant secretome proteomics, molecular approaches can be used to test SSP secretion. For example, the CDS of SSPs can be fused with reporter genes, such as green fluorescent protein100 based on self-training HMM models and transcriptomic data. Next, NSS-containing small proteins that are transported via CSP pathways are predicted with ML-based tools, such as SignalP 5.0. At this stage small proteins containing transmembrane regions, which are unlikely to be secreted, should be identified and eliminated from downstream analysis. Given that some NSS-containing proteins follow USP pathways, additional ML-based software, such as SecretomeP, may be applied simultaneously. In addition, the secretion ability of proteins without an NSS are inferred by subcellular localization prediction tools —an inhibitor of vacuolar-type ATPase (V-ATPase), which blocks post-Golgi trafficking and has been used in examining the transportation pathway of VHA-a3 (refs. 107). Additionally, small molecules that can interact with trafficking-related organelles or vesicles have been used to screen for their potential application in elucidating protein secretion pathways108. The power of these trafficking inhibitors, however, becomes limited when it comes to examining the movement of SSPs between plants and microbes. An alternative approach could be based on fluorescently tagged SSP, which was discussed above and appears to be more useful for examining the cross-kingdom movement of plant SSPs.Small-molecule reagents have been used to dissect protein trafficking routes. A widely used example is the fungal toxin brefeldin A (BFA). Given that BFA can disrupt the retrograde traffic from the Golgi to the ER, it serves as a powerful tool for distinguishing Golgi-dependent and -independent protein trafficking109 fused different vacuolar sorting signals to the C terminus of CLV3 and redirected the destination of CLV3 from apoplast to the vacuole. The authors concluded that apoplastic localization is essential for CLV3 to activate the CLV signaling pathway in A. thaliana.In addition, a learn-by-design approach based on rewriting the transport pathway can be informative for evaluating if secretion is required for SSP function. Targeted redirection has been achieved by fusing SSPs to alternative sorting signals. For example, Rojo et al.111, are among the most powerful tools to reveal phenotypes associated with genes of interest. These techniques work equally well for studying the function of SSP-encoding genes. For example, CLV3—the meristem development regulator, when constitutively overexpressed in transgenic A. thaliana112 demonstrated the correlation between the level of CLV3 protein and the accumulation of the meristem cells. In addition, A. thaliana in which the expression of CLV3 was suppressed by RNAi was created by Chuang and Meyerowitz113 for studying the associated phenotypic changes in floral development. Similarly, RNAi-induced suppression of the PtCLV3 ortholog PttCLE47 were employed by Kucukoglu et al.114 to investigate its role in cambial development and secondary xylem formation in hybrid aspen (Populus tremula × P. tremuloides).Reverse genetics techniques, by imparting loss- or gain-of-function mutations via ectopic expression, virus-induced gene silencing, and RNA interference (RNAi)118. Its development is based on an immune system naturally found in bacteria and archaea, the CRISPR/Cas9 system has been widely used for creating gene knockouts by creating double-strand breaks, which are then repaired by error-prone the non-homologous end joining in plants and therefore often lead to indel mutations in the target gene. The efficacy of CRISPR/Cas9-mediated gene knockout has been demonstrated in a number of herbaceous and woody plant species122. In the last few years, the adaptation of CRISPR into a recruiting platform and the discover of Cas9 variants have made CRISPR/Cas a more versatile tool. For example, transcriptional activation and suppression of single and multiple genes can now be conferred by the CRISPR/deactivated Cas9 (dCas9)-based transcriptional regulation system124. All of these tools can be used in tuning the expression of SSPs for revealing their targets and examining their biological impacts.Besides traditional techniques, the recent revolution in gene editing tools, particularly the invention of the CRISPR/Cas and related technologies, provides new opportunities for efficient gene knockout, gene knockin, gene activation, and gene suppression in plantsA. thaliana, have been relying on creating targeted mutants or performing mutational screen to achieve this goal. Taking receptors of CLV3 in A. thaliana for instance: CLV1, which is a leucine-rich repeat receptor-like kinase, was verified via phenotypic analysis of single or double mutants125. Meanwhile, CORYNE (CRN) which is a membrane-associated protein kinase, and TOADSTOOL2 (TOAD2) which is a receptor-like kinase, were identified by screening the population created with ethyl methanesulfonate mutagenesis127.As discussed above , many plant SSPs act as signaling molecules and have the ability to affect the expression of other genes. Therefore, identifying the receptors and other downstream targets of an SSP of interest is the ultimate step towards deciphering SSPs’ biological function. A number of early studies, particularly those done in 128. In particular, the capability of Y2H-based approaches has been extended from one-by-one clonal identification to proteome-wide mapping of PPIs, with the recent development of matrix-based Y2H methods coupled with next-generation sequencing (NGS) technology129. Compared with mutational screen, Y2H-NGS approaches make it possible to identify novel interaction partners of SSPs even within an organism whose genome has not been fully annotated yet.Besides mutational screens, PPI data can provide valuable evidence in identifying novel partners that interact with SSPs during signal transduction. Several in vitro and in vivo PPI detection approaches, such as affinity purification (AP), tandem affinity purification, and yeast two-hybrid (Y2H), have been commonly used132  using liquid chromatography138.High-throughput analytical approaches that couple selective enrichment, fractionation/isolation, and phenotype screening followed by MS-based identification provide an established framework to screen plant tissues for biologically relevant SSPs132 Fig. . This cl142. Alternatively, cell-free screening has been employed to evaluate the effect of SSPs to better describe the thermodynamic, kinetic, or structural basis for molecular interactions with other cellular constituents143. Cell-free screening can be employed to identify SSPs with the abilities to scavenge free radicals, chelate metals, or bind to certain macromolecular targets that regulate various biological processes such as epigenetic processes and cell proliferation145.Either as crude extract mixtures, enrichments, or isolated fractions, SSPs can be evaluated for their bioactivity against cell-based or cell-free biosystems. Cell-based screening can be used to assess simple effects on cell viability, morphology, and proliferation, or to elucidate the mechanism of action. Common phenotypes profiled in cell-based systems are growth promotion/restriction or antimicrobial activityde novo search strategies146. De novo sequencing algorithms derive peptide sequences using only fragment ion information from the tandem mass spectra, are generally optimized to run without the restriction of cleavage enzymes  and work in an unbiased manner as they do not necessarily require any input based on prior knowledge of the sample147.Following the detection of fractions with relevant bioactivity, molecule libraries can be further interrogated via high-throughput LC-MS/MS to sequence unknown SSPs. Some of the current challenges in accurate and sensitive identification of SSPs with MS include lack of SSP representation in protein databases, inadequate understanding of SSP maturation mechanisms, and partial knowledge of their PTM. Thus, the characterization of SSPs by LC-MS/MS can benefit from the use of In the past several years, there has been increasing evidence that SSPs play important roles during plant growth, development and response to biotic and abiotic stresses, and consequently a growing appreciation of the biological significance of plant SSPs. A sheer number of SSPs have been predicted in diverse lineages of organisms, and the intercellular or inter-organismal movement of SSPs infers that SSPs are likely a significant and common mode of signaling among organisms. It is now known that SSPs are synthesized and secreted via diverse pathways in plants. Currently, however, the number of characterized SSPs in plants is low. The majority of SSPs encoded in plant genomes are overlooked and remain unannotated. Roadblocks that prevent progress in the study of SSPs include (1) a lack of reliable methods for isolating SSPs for experimental characterization, (2) a lack of capabilities for real-time monitoring the intercellular or inter-organismal movement of SSPs, (3) a lack of structural data for SSPs, and (4) a lack of computational tools for predicting non-conventional secretion of SSPs.Recent advances in high-throughput molecular screening approaches and bioinformatics offer exciting opportunities for the discovery and characterization of SSPs. For example, the rapid accumulation of omics data, including genomics, transcriptomics, and proteomics, provide rich databases for discovering plant SSPs, including those derived from larger protein precursors and directly encoded by sORFs. Meanwhile, advanced ML tools have evolved to predict the secretion pathways, including both CPS and UPS that SSPs follow. Such computational prediction on secretion can be verified experimentally, for example, via bioimaging of fluorescent reporter-tagged protein candidates. In addition, advanced plant biotechnologies, particularly, CRISPR/Cas-based genome-editing systems and transcriptional regulation systems  allow for efficient gene knockout, activation, and suppression, and therefore analysis of the biological roles of SSPs, and identification of their partners by combining with PPI and NGS data. The discovery and functional role of SSPs in plant growth and development will continue to expand in the near future.


In this review paper, we summarized the recent progress of using graphene as a sensing platform for environmental applications. Especially, we highlight the electrical and optical sensing devices developed based on graphene and its derivatives. We discussed the role of graphene in these devices, the sensing mechanisms, and the advantages and disadvantages of specific devices. The approaches to improve the sensitivity and selectivity are also discussed. Simple and reliable sensors for trace species detection are highly desirable in a spectrum of applications ranging from medical diagnosis, environmental monitoring, industrial and agricultural processes control, and lab-on-a-chip. In the past two decades, various nanomaterials have been explored for sensing applications, including nanoparticles, nanowires, nanotubes, and nanosheets ,3,4,5,6.In this review, we highlight the versatility and robustness of graphene as a sensing platform, with emphasis on environmental chemical sensing applications in both liquid and air media. In particular, we focus on two types of sensors: electrical and optical sensors. Electrical sensors based on conductivity changes benefit from graphene’s exceptional carrier transport properties, allowing for improved sensing capabilities. Optical sensors take advantage of graphene’s unique optical properties and show great promise for future applications. The differences between optical and electrical sensors are vast, and it is outside the scope of this review to enumerate them. Instead, we highlight graphene’s versatility and offer practical considerations for sensor designing. In the following, we demonstrate how graphene has been employed in assessing pH and humidity levels, and the presence and concentration of various gaseous and liquid molecules, under different sensing mechanisms.2-hybridized carbon atoms arranged in a honeycomb lattice with a thickness of only 0.34 nm . . 110]. T2/Si, however with the addition of graphene those signals were clearly observed  and graphene, both the Raman scattering cross section and the incident and scattering photons get enhanced, together making a graphene-mediated surface-enhanced Raman scattering substrate, or G-SERS.−5 M) and compared it to the tape placed only on water without the dye  and took a Raman spectrum which showed no discernible CuPc peaks. However, when placing the G-SERS tape under the laser spot on the cauliflower clear CuPc peaks are observed, The G-SERS tape is also remarkably versatile, as it can also be used with both liquid and solid samples. To demonstrate that analysis of trace amounts of analytes with the G-SERS tape works on any surface with arbitrary morphology, the authors submerged a cauliflower head into a copper phthalocyanine (CuPc) solution , they offer the advantage of being non-contact and are promising for multiplexing in the case of optical-fiber sensors and G-SERS.There are several aspects that make graphene an ideal sensing platform. A major one is graphene’s unique linear band structure around the K point that makes it sensitive to perturbations caused by adsorbed molecules; here we reviewed how these changes can be probed electrically and optically. The atomically thin nature of graphene allows the possible miniaturization of devices, so that more sensors could be packed in the same area. Additionally, we also detailed general steps towards performance improvements in terms of selectivity and sensitivity through the addition of surface modifiers that (1) preferentially bind to the target molecule and (2) increase graphene’s sensitivity to external perturbations, respectively. Further research on surface modifiers is likely to solidify graphene as a sensing platform.The future of graphene sensors is promising but some challenges need to be overcome. While there has been significant effort on realizing proof-of-concept devices, the transition from laboratory to market primarily hinges on the performance of these sensors. Although high selectivity and sensitivity can be achieved in laboratory settings, it is not clear how these devices will fare in real-world scenarios. It is rare to have contaminant-free samples when dealing with environmental applications and the effect of contamination might hinder sensor readings. Although we have reviewed that graphene-based sensors do not always need to come single crystal graphene samples and lower grades are usually sufficient, the biggest hurdle for widespread adoption of this new technology still rests on the availability of graphene, both in terms of quality and cost. We also anticipate the integration of wireless technology to graphene sensors will significantly expand the adoption of these devices in the age of the Internet-of-Things for their real-time measurement capabilities.


Due to its exceptional physical properties, such as high electronic conductivity, good thermal stability, excellent mechanical strength, and chemical versatility, graphene has sparked a lot of interest in the scientific community for various applications. It has therefore been employed as an antibacterial agent, in photothermal therapy (PTT) and biosensors, in gene delivery systems, and in tissue engineering for regenerative purposes. Since it was first discovered in 1947, different graphene derivatives have been synthetized from pristine graphene. The most adaptable derivate is graphene oxide (GO). Owing to different functional groups, the amphiphilic structure of GO can interact with cells and exogenous or endogenous growth/differentiation factors, allowing cell adhesion, growth, and differentiation. When GO is used as a coating for scaffolds and nanomaterials, it has been found to enhance bone, chondrogenic, cardiac, neuronal, and skin regeneration. This review focuses on the applications of graphene-based materials, in particular GO, as a coating for scaffolds in bone and chondrogenic tissue engineering and summarizes the most recent findings. Moreover, novel developments on the immunomodulatory properties of GO are reported. When implanted into rabbit radial defects, a synergistic effect was observed, with a high bone amount and mineralized collagen deposition [Several recent papers have reported the potential of GO in enhancing osteogenesis in traditional osteogenic conditions. Radunovic and coworkers  improvedposition .2+, PO42−, Li+, and Mg+ , capable of starting stem cell differentiation from the surface of graphene derivatives [2+ and PO43−. Calcium phosphate graphene could intrinsically induce osteogenesis in vitro and trigger ectopic bone formation in vivo in the presence of bone marrow stromal cells (BMSCs), thereby revealing phosphate–GO-functionalized materials as intrinsically inductive scaffolds capable of revolutionizing bone regeneration [In recent years, the possibility of investigating GO-dependent enhancement of osteogenic differentiation in novel osteogenic conditions has started to be a focus. As an example, based on the rationale that chondrocytes release substances that improve osteogenic differentiation during endochondral ossification, Kim et al.  comparedivatives . In a reneration . Given the widely demonstrated ability of GO to speed up the osteogenic process in both traditional and nontraditional conditions, the next section focuses on the most important MSC adhesion molecular pathways affected by graphene.Several molecular studies on graphene-related osteoinductive capability have focused their attention on different pathways triggered in MSCs to enhance differentiation, such as phosphoinositide 3-kinases (PI3K)/protein kinase B (Akt)/glycogen synthase kinase (GSK)-3β/β-catenin , α5β1 anGO has also aroused interest in the field of odontogenesis and regenerative dentistry , as demoDi Carlo and coresearchers  establisEven though graphene-mediated MSC adhesion properties are essential for osteogenesis and odontogenesis, another crucial aspect to investigate is the immunomodulatory properties of graphene-based materials, which will be discussed in the next section.The term osteoimmunology refers to the existing link between the immune and the skeletal systems. Both immune cells and cytokines contribute to the regulation of bone homeostasis, and bone cells also influence immune cell functions. Therefore, the immune microenvironment is crucial in determining the speed and outcome of bone healing, repair, and regeneration . In the Another main issue that can induce immunity system activation and lead to implant failure in the presence of bone grafts is the potential release of small debris from scaffolds used in standard orthopedic procedures. Chang and co-researchers  analyzedCartilage damaged by trauma has a limited capacity to heal. Thus, the regeneration of articular cartilage remains a major challenge in orthopedics and tissue engineering. Currently, treatment of small articular cartilage injuries involves administration of nonsteroidal anti-inflammatory drugs (NSAIDs), analgesics, corticosteroid, and hyaluronic acid (HA) injections, viscosupplementation, articular chondroplasty, and artificial joint replacement . Larger As previously reported for osteogenesis, graphene is a good nanocarrier for several molecules. To induce and improve MSC osteogenesis, researchers typically use a medium supplemented with differentiation or growth factors. Graphene, due to its structure and ability, can soak up molecules dissolved in the medium and improve their entrance into the cells, thereby speeding up the process. The same approach can be applied to induce chondrogenesis in MSCs . With thAs mentioned earlier, TGF-β1 and TGF-β3 are two of the major chondrogenic differentiation factors and are frequently used alone or in combination with other differentiation molecules in the chondrogenic differentiation medium. During the development of growth plates, BMP signaling promotes the maturation of chondrocytes to facilitate ossification, whereas TGF-beta signaling inhibits hypertrophic differentiation to preserve adequate chondrocytes within the growth plate. Both TGF-beta signaling and BMP signaling are indispensable for the maintenance and repair of articular cartilage . At a moEven though the extraordinary properties of graphene, in particular GO, can induce chondrogenic differentiation and regeneration without the addition of differentiation factors, graphene can also be used as a nanocarrier for differentiation factors.Differentiation/growth factors  can be administered in situ to obtain rapid repair of local cartilage lesions. However, there are frequent issues to overcome, such as inactivation of these molecules in the site of action or the inability to retain factors at a local level. To overcome these limitations, a possible strategy could be to use carrier materials that are able to release these factors in the interested region. Nevertheless, this approach presents frequent problems, such as the large amount of early release of growth factors from these materials followed by little long-term release , which pSimilarly, rGO can be used as a nanocarrier for specific molecules to improve chondrogenic differentiation. Jiao and coworkers  investigThese findings suggest GO has good potential in the release of specific molecules, thus improving chondrogenic differentiation, although further investigations are needed to support this hypothesis. In addition, functionalization of the graphene surface with active molecules to enhance the chondrogenic capability of graphene is a new and challenging strategy.Graphene, and in particular its derivative GO, has triggered enormous interest in the scientific and industrial communities owing to its simple synthesis and versatility. Indeed, the graphene chemistry offers a plethora of opportunities for the design of multifunctional nanocomposites and devices with promising uses in tissue engineering. Among its several biomedical applications, GO has been particularly used for bone regeneration purposes as it has been shown to be capable of enhancing and ameliorating osteoconductive properties of materials in vitro and in vivo. Recently, properties of GO have also been successfully applied in the field of cartilage regeneration, achieving promising results in vitro. Very interestingly, graphene-based materials are emerging as attractive materials that are able to modulate inflammatory pathways in immune cells, thus promoting and accelerating tissue regeneration after implantation.


Patients with pulmonary sarcoidosis commonly present with a dry cough; a productive cough suggests a complicating airway infection or an alternative diagnosis such as tuberculosis or bronchiectasis.A 36-year-old European (Frisian) woman recently diagnosed with pulmonary sarcoidosis presented with debilitating exertional dyspnea and cough productive of glazy mucoid sputum. Several different attempts including video-assisted thoracoscopic biopsies failed to reach a second or alternative diagnosis including an infectious, autoimmune or collagen-vascular condition. She responded to steroids but with poor tolerance to this treatment, which could not be tapered. After she was started on anti-tumor necrosis factor alpha (TNF-α) therapy with infliximab, 200 mg at three-monthly intervals, she has been fine for well over a decade.In this patient with sarcoidosis who had a productive cough accompanied by fever, an extensive workup and prolonged follow-up, an alternative or second diagnosis could be ruled out; we therefore conclude that this highly unusual presentation is part of the clinical spectrum of sarcoidosis. Sarcoidosis is a chronic inflammatory condition characterized by granulomatous inflammation of unknown origin . Both puWe present the case history of a patient that meets the classical radiographic and histopathological pattern of sarcoidosis, complicated by a cough productive of glazy, mucoid sputum. Based on an extensive diagnostic workup, combined with a persistent beneficial response to anti-inflammatory treatment alone, without any antimicrobial or other treatment modalities, we propose that this unusual, unique presentation should be considered part of the spectrum of the symptomatology of sarcoidosis.Staphylococcus aureus, Acinetobacter baumannii, Calcoaceticus complex and Haemophilus influenzae; she had received targeted antimicrobial treatment without relief of her symptoms. Her chest X-ray and computed tomography (CT) scan showed mediastinal and bi-hilar lymphadenopathy, mainly suggestive for sarcoidosis stage 1 ; all other blood chemistry results including liver enzymes, electrolytes and renal function parameters were in the normal range. Arterial blood gas analysis showed pH 7.55, partial pressure of carbon dioxide 3.3 kPa, partial pressure of oxygen 9.9 kPa, oxygen saturation 97%, and bicarbonate ions 21 mmol/L; gas exchange for oxygen was impaired: the calculated alveolar-arterial oxygen difference was 6 kPa . Blood and sputum cultures and a multiplex polymerase chain reaction (PCR) test for common respiratory pathogens  and urine tests for Legionella pneumophila type 1 and S. pneumoniae were all negative: no bacterial, fungal, parasitic or viral pathogens were identified. Pulmonary function testing showed mild restriction. High-resolution CT scanning showed, besides mediastinal and bi-hilar lymphadenopathy, ground-glass attenuation predominantly in the upper lobes without bronchiectasis  woman was referred because of fever, dyspnea and a cough productive of shiny glazy mucoid sputum, accompanied by arthralgias. She was a lifetime non-smoker, had worked as a part-time teacher for hair dressing students but had no inhalational exposure to organic dust. Chest auscultation revealed coarse and fine crackles especially over the right anterior lung field, and sporadic scattered wheezes. Laboratory findings showed only mildly elevated C-reactive protein; no blood eosinophilia was found. At the first manifestation of her chest symptoms, sputum cultures grew Bronchoscopy with bronchoalveolar lavage showed lymphocytic inflammation; no mycobacterial, bacterial, fungal or viral pathogens were identified by culture or PCR. Video-assisted thoracoscopic biopsies of the right middle and upper lobes showed granulomas compatible with sarcoidosis but no other diagnostic clues Fig. . BiochemConsidering that her diagnosis—although with highly unusual presentation—best fit the earlier diagnosis of sarcoidosis , 4, we sThis patient with sarcoidosis—radiographically, stage 1—presented with a highly unusual debilitating syndrome with cough productive of mucoid glazy material, without any evidence of infection, accompanied by fever and transient arthralgias.Haemophilus influenzae or Pseudomonas spp; in the 14 years we followed her, she never had bowel symptoms, making Crohn’s disease unlikely. She never had symptoms suggesting paranasal sinusitis, and her cough and sputum production subsided without macrolide use; these observations make the diagnosis of diffuse panbronchiolitis unlikely, and we therefore propose that all of her symptoms are consistent with a highly unusual presentation of sarcoidosis.Sarcoidosis patients typically have a dry cough ; productThe workup included chemical and microbiological analysis of sputum and high-resolution CT, followed by bronchoscopic and video-assisted thoracoscopic biopsies, which were also cultured and subjected to PCR to detect a possible infectious origin. Taking all the evidence together, we conclude that infectious, metabolic, allergic, neoplastic and collagen-vascular disorders other than sarcoidosis could be ruled out.We found one previously reported case of sarcoidosis presenting with a productive cough—but complicating bronchiectasis was not ruled out . The susWe describe a highly unusual presentation of sarcoidosis, with a cough productive of glazy mucoid sputum, accompanied by fever and transient arthralgias, radiographically stage 1, without evidence of complicating infection, and followed by complete resolution of symptoms with TNF-alpha inhibitor (infliximab) therapy, a response that persisted for over 12 years, and a relapse of symptoms following each of two different attempts to taper her infliximab therapy. This highly unusual presentation should be considered in patients with sarcoidosis and productive cough, after airway infection and bronchiectasis have been ruled out.


Numerous device structures have been proposed for perfect absorption in monolayer graphene under single-sided illumination, all of which requires the critical coupling condition, i.e., the balance between the loss of graphene and the leakage rate of the device. However, due to the difficulty of the precise control of the quality of synthesized graphene and unwanted doping in graphene transferred to the substrate, the loss of graphene is rather unpredictable, so that the perfect absorption is quite difficult to achieve in practice. To solve this problem, we designed a novel perfect absorber structure with a loss adaptive leakage rate control function enabled by the quasi-bound states in the continuum (BIC) and numerically demonstrated its performance. Our designed device is based on a slab-waveguide grating supporting both the quasi-BIC and the guided-mode resonance (GMR); the quasi-BIC with an adjustable leakage rate controlled by an incident angle is responsible for absorption, while the GMR works as an internal mirror. Since the proposed device scheme can have an arbitrarily small leakage rate, it can be used to implement a perfect absorber for any kind of ultrathin absorbing media. Due to the simple structure avoiding an external reflector, the device is easy to fabricate. Undoped monolayer graphene exhibits uniform light absorption efficiency of ~ 2.3% over a wideband wavelength range from visible to terahertz. Considering its atomically ultrathin thickness of ~ 0.34 nm, the absorption efficiency is relatively high value. However, for practical high-performance photodetectors, the absorption should be greatly enhanced by applying various resonant structures such as gratings or photonic crystals8, prism couplers10, and Fabry–Perot cavities12. From a standpoint of absorption efficiency enhancement, perfect absorption under single-sided illumination is an ultimate solution. Over the past decade, three types of perfect absorber schemes have been proposed: a single-mode/mirror scheme16, a dual-mode  scheme18, and a triple-mode scheme19. The single-mode/mirror scheme requires a rather complicate fabrication process due to Bragg reflector or suffers from unwanted loss due to metal reflector. Although the dual-mode scheme avoids the use of mirror, it is prohibitively restrictive to simultaneously satisfy the frequency degeneracy and the critical coupling conditions of dual modes. The triple-mode scheme relieves design complexity compared to the dual-mode scheme but requires somewhat complicate fabrication process due to an added slab structure. Recently, our group proposed another mirror-less perfect absorber scheme based on an asymmetric single resonator such as a slab-waveguide grating (SWG) by adopting a one-port mimicking concept20. In this scheme, two indirectly coupled degenerate guided-mode resonance (GMR) modes are used to achieve a virtual one-port system, in which only one mode experiences loss and the other functions as an internal reflector in conjunction with the Fabry–Perot (F-P) like background scattering. This scheme does not require any structural symmetry, and its performance shows greatly enhanced fabrication error tolerance in comparison to the previously proposed dual-mode scheme of ref.17.Graphene has attracted strong interests in developing high-speed photodetectors due to its high carrier mobility10. Besides, the substrate can cause unwanted doping of graphene, which also changes the loss rate. So, the critical coupling condition for perfect absorption is quite difficult to satisfy in practice. This is the fundamental problem of all the previously proposed perfect absorber schemes. In this work, to solve this problem, we newly propose a perfect absorber scheme with a controllable leakage rate based on a quasi-bound states in the continuum (BIC).In the perfect absorber schemes, the critical coupling condition, i.e., balance between loss and leakage (or decay) rates is a common and essential requirement. The leakage rates of the relevant resonant modes in all the forementioned perfect absorber schemes are determined by structural parameters and thus, can hardly be adjusted after fabrication. On the other hand, the loss rate of graphene is somewhat unpredictable since the quality and the thickness of synthesized graphene is quite difficult to control preciselyQ-factor) even though it exists within the light cone of the surrounding medium36. In practice, the BIC can be realized as a quasi-BIC whose finite Q-factor is adjusted by breaking structural symmetries32 or through parameter tuning36. Recently, quasi-BICs in various periodic structures  or an isolated nanoparticle36 have attracted substantial attention as a platform for enhancement of light-matter interaction due to their ultrahigh Q-factor.The BIC is a special eigenstate that remains localized and has an infinite quality factor  is placed on the ridge side of the SWG. This is because the quasi-BIC is mostly confined in the ridge region. In the designed device, for small value of asymmetry parameters, which is determined by an incidence angle, quadratic dependence of the Q-factor on the asymmetry parameter is confirmed. To investigate the reflection and absorption spectra, and field profiles of various resonant modes in the proposed absorber, we used the rigorous coupled wave analysis (RCWA) method37. The incidence angle dependence of quasi-BIC is also analyzed by using the coupled mode theory (CMT)38.An interesting feature of the quasi-BICs in the periodic structures formed by breaking structural symmetries with oblique incidence of light is that their 2), where the ridge (grating) and the sublayer (slab) possess the same index, and monolayer graphene placed just above the SWG. Refractive indices of Si and SiO2 are 3.40 and 1.45, respectively. For the permittivity of graphene, Kubo formulation39 was used with parameters of a graphene thickness of 0.34 nm, Fermi velocity of 106 m/s, and mobility of 0.5 m2/Vs. Figure g) of graphene for different Fermi-levels  over the wavelength range of s-polarized) wave obliquely incident from the air with an incidence angle of FF) is defined as wGrat/Period. The optimal design parameters are as follows: Period = 0.85 dGrat = 0.367 dSlab = 0.052 FF = 0.55, and A > 99.99%) in undoped (Ef = 0) monolayer graphene at The proposed absorber Fig. a consistQ-factor control via a proper choice of the incidence angle. All numerical calculation in this work has been conducted with the RCWA simulation37. Figure Ef = 0). A strong absorption peak branch is observed for ~ 2 degree < A > 99.995%) occurs at A <  < 1%) for the normal incidence implies that the absorption due to the GMR mode is negligible and the one-port system mimicking concept really works. The detailed analysis on the operation principle of the designed device will be discussed in the next section.The performance of the designed graphene perfect absorber is numerically demonstrated, especially focused on the loss variation adaptive A > 99.99% occurs entclass1pt{minimaQ-factor  as the incident angle approaches zero. So, if the absorption coefficient of the absorbing material becomes smaller, the critical coupling condition, that is, the balance between the leakage rate and the loss rates can be satisfied at a smaller incident angle. To demonstrate this, we investigated the angle dependent absorption performance of the designed device for two different doping levels  of graphene, which is plotted in Fig. Ef = 0.5 eV and mobility Mo = 0.5 m2/Vs, the loss rate of graphene corresponds to ~ 1/40 of the undoped case of the same mobility at Ef increases, which is due to the increased Q-factor of the quasi-BIC mode at the lower incidence angle. It is straightforward that perfect absorption can also be achieved for the increased loss of graphene at the larger incidence angle, which is not shown here. Therefore, even for the unwanted loss variation of graphene, the designed device can achieve perfect absorption via adaptive control of the incidence angle.The excellent feature of the designed perfect absorber is that loss adaptive perfect absorption is achievable via a proper choice of the incidence angle. Especially, perfect absorption can be achieved even if the loss (or the absorption coefficient) of the absorbing material is extremely low. This is attributed to the unique property of the quasi-BIC with an extremely large FF) dependence of reflectance (|R|2) for normal incidence , the Q-factor of GMR1st considerably decreases and thus, it forms a broadband reflector in conjunction with the F-P like background scattering42. As plotted in the lower panel of Fig. 1st near the reflection peak condition  direction with respect to the center of the ridge since the contribution of BIC2nd is dominant. Although GMR1st mode is also excited in this case, the energy stored in it is negligible compared to BIC2nd due to the huge Q-factor difference. So, much stronger field enhancement is attributed to BIC2nd as well.For oblique incidence  and reflection phase , and the wavelength of 2nd). We can see that the locus of the resonance wavelength of BIC2nd is the same as the strong absorption peak branch in Fig. 2nd is responsible for the absorption in our designed device.Now, we closely investigate the interaction between the GMR and the quasi-BIC modes, and the angle dependence of BICQ BIC2nd does not ruin the broadband flat-top reflection due to the GMR1st—the background scattering interaction. It is noteworthy that this kind of interaction between two resonant modes in a single resonator is an unusual phenomenon, which requires triple degeneracy among the two resonant modes and the F-P like background scattering and a proper indirect mutual coupling strength between the two modes as theoretically proved in our previous works43. Unless these conditions are satisfied, which is more usual, a sharp reflection fluctuation known as Fano line shape appears44. Previously, quasi-BIC related Fano resonances are utilized for a narrowband transmission filter at slightly off-normal incidence angle in a 1-D high contrast grating (HGC)28 and a narrowband reflection filter in an asymmetric metasurface29. As seen in Fig. R ~ 0 is observed when BIC1st interacts with the GMR mode at FF = 0.2 and FF = 0.2  and its detailed description is provided in Supplementary information. The interaction between two resonant modes in a two-port asymmetric resonator like the SWG can be modeled as an indirect coupling via the partial reflections at the two port interfaces in the CMT43. From this CMT modeling, we can find the specific indirect coupling condition between the two degenerate resonant modes for perfect reflection or transmission at the resonance. (Supplementary information) This implies that depending on the indirect mutual coupling condition between the quasi-BIC and the GMR modes, perfect transmission as well as perfect reflection can occur at the resonance. Since the indirect coupling stems from the partial reflections at the surfaces of the SWG, the coupling condition is strongly dependent on FF. In our optimal design, the proper coupling condition between BIC2nd and GMR1st modes for perfect reflection is satisfied at FF = 0.55, 1st and GMR1st modes at FF = 0.2 and 2nd and GMR1st modes.For a clear comparison, two reflectance (reflection phase) spectra for 2nd and GMR1st modes appears to remain roughly up to Q-factor of BIC2nd mode, resulting in the reflectance dip development. Note that the indirect coupling strength is determined by the decay rates of the two modes as well as the reflections at the surfaces of the SWG43. So, the operation range of Q-factor should be limited. However, this is not the fundamental limit. Our present design is for undoped graphene of a certain condition . For graphene of a larger loss due to the difference material quality, the device can be redesigned to have a larger optimal incidence angle, and then, the operation range of In our present design, the proper coupling condition between BIC46. Therefore, it can be stated that the designed structure behaves like a virtual one-port resonant system, mimicking the system composed of a single-mode resonator and an external mirror. In our proposed perfect absorber structure, BIC2nd works as a lossy mode while GMR1st works as an internal mirror in conjunction with the background scattering as aforementioned.It is also noteworthy that the reflection characteristics of our designed structure without graphene is similar to the phase shifter based on an ideal asymmetric Fabry–Perot cavity with a perfectly reflecting bottom mirrorQ-factor of BIC2nd, shows Q-factor (or lower leakage rate); the smaller incidence angle, the higher Q-factor. This is because a smaller incidence angle induces a weaker structural asymmetry and consequently, a less distortion of the symmetry-protected BIC. For the quantitative analysis of the angle dependent Q-factor of BIC2nd, we extracted the leakage rate of BIC2nd by fitting the CMT model to the reflection phase spectrum calculated with the RCWA. According to the CMT, the reflection phase in a lossless one-port system with a single resonance is given byo and γleak are a resonant frequency and a leakage  rate, respectively38. The Q-factor of BIC2nd is calculated by QBIC = o/2γleak, which is plotted in Fig. QBIC ~ 702 at the optimal angle of QBIC increases toward infinity as QBIC is inversely proportional to the square of the asymmetry parameter  rates, respectively6. Perfect absorption can be reached when the critical coupling condition (γleak = γloss) is satisfied at the resonance (o).The optimal incidence angle selection for perfect absorption satisfying the critical coupling condition is analyzed with the CMT. According to the CMT, absorption efficiency in a lossy one-port system with a single resonance is given byγleak is obtained via fitting the CMT model (1) to the reflection phase spectrum calculated with the RCWA as mentioned in the previous section, we can also extract γloss by fitting the CMT model (2) to the absorption spectra , it is confirmed that the critical coupling occurs at Ef = 0.4 eV and 0.5 eV, the optimal incidence angles for the critical couplings are 2nd resonance.Once MT model  to the aQ-factor for loss variation, which is based on the quasi-BIC and the GMR modes in a SWG. In the device design, the one-port resonant system mimicking concept was adopted. The device structure is quite simple and easy to fabricate; no external mirror is required, and monolayer graphene is placed on the ridge of the SWG. The proposed perfect absorber scheme can be used for any kind of ultrathin absorbing media including various 2-D materials.In conclusion, we have numerically demonstrated a graphene perfect absorber with a function of adaptive control of 37 and the coupled mode theory (CMT) fitting for a lossy and lossless one-port resonant system38. In the RCWA simulation, more than 300 harmonics were applied to guarantee accuracy around the resonant wavelength. In all our calculations, the complex permittivity of graphene (g) was calculated using Kubo formulation based on the local random phase approximation for various Ef39, assuming graphene thickness of 0.34 nm, Fermi velocity of 106 m/s, and mobility of 0.5 m2/Vs.To numerically investigate and analyze the reflection and absorption properties in the proposed perfect absorber, we used two-dimensional RCWA Supplementary Information.


The remote epitaxy of GaN epilayers on GaN/sapphire templates was studied by using different graphene interlayer types. Monolayer, bilayer, double-stack of monolayer, and triple-stack of monolayer graphenes were transferred onto GaN/sapphire templates using a wet transfer technique. The quality of the graphene interlayers was examined by Raman spectroscopy. The impact of the interlayer type on GaN nucleation was analyzed by scanning electron microscopy. The graphene interface and structural quality of GaN epilayers were studied by transmission electron microscopy and X-ray diffraction, respectively. The influence of the graphene interlayer type is discussed in terms of the differences between remote epitaxy and van der Waals epitaxy. The successful exfoliation of GaN membrane is demonstrated. In recent years, a novel approach to the growth of III-nitrides has emerged, based on 2D materials, such as graphene, as interlayers between the substrate and the epitaxial layer ,2,3. ComThe critical step in this approach is the graphene layer transfer. Thicker graphene interlayers allow for easier exfoliation of the grown epilayer, since the separation of films tends to occur within graphene layers ,16 due tGenerally, the transfer of the graphene layer onto the target substrate is conducted in either a wet or a dry manner. The main disadvantages of dry transfer are the appearance of cracks, due to the interaction with hard surfaces, and a relatively high material cost . Cracks 3) were used as Ga and N precursors, respectively. The epitaxy process was monitored by an in situ laser reflectometry system operating at 650 nm. Transfer-ready poly(methyl methacrylate)-coated (PMMA-coated) graphene films from two vendors were used to cover the GaN/sapphire templates. Graphene monolayers were obtained from Graphenea Inc. , while the bilayer graphene was acquired from ACS Material, LLC . After the transfer, samples were annealed in an oven with a controlled environment.The GaN layers in the studied samples were grown using a low-pressure metalorganic vapor phase epitaxy (MOVPE) in a flip-top close-coupled showerhead 3 × 2” reactor . Trimethylgallium (TMGa) and ammonia . The surface morphology was studied by scanning electron microscopy . The surface roughness was evaluated by atomic force microscopy . The freely distributed WSxM software was used to analyze AFM data . The GaNThe initial GaN/sapphire template was prepared by the standard MOVPE growth of the GaN layer on a 2-inch c-plane sapphire substrate , the full width at half maximum (FWHM) of a 2D peak, and the position of the 2D peak make it possible to determine the number of graphene layers with a relatively good degree of accuracy [2D/IG was 2.5, while the position and FWHM of the 2D peak were 2682 cm−1 and 38 cm−1, respectively, all consistent with the single graphene layer [2D/IG decreased to 0.8, and the 2D peak broadened to 48 cm−1, indicating two graphene layers in the film [−1, and the G peak slightly shifted to 1583 cm−1 in the bilayer graphene. In contrast, the 2D peak shifted to 2687 cm−1, and an additional D’ peak emerged on the shoulder of the G peak in the double-stack graphene. The broadening and the shift of the 2D peak are caused by its splitting into different subpeaks, which is explained by the evolution of the electronic bands in graphene with an increasing number of layers [2D/IG in the triple-stack graphene was reduced to 0.3, which is actually below the expected value of 0.6 [The number and quality of graphene layers on the GaN/sapphire template were verified by Raman spectroscopy. The Raman spectra for all the studied types of graphene interlayer are presented in 500 cm−1 ,27. The accuracy . For thene layer . For botthe film . Howeverf layers ,30. The e of 0.6 , and impTo reveal the impact of the graphene interlayer type on the formation of the initial GaN seeds, the growth of the GaN nucleation layer on the graphene-covered templates was carried out for 5 min at 700 °C without an extra recrystallization process. The selected growth conditions were based on our previous study on the remote epitaxy of GaN .The initial formation of GaN islands is demonstrated in the SEM images in The epitaxial orientation of the GaN seeds is determined by the electrostatic interaction with the GaN template below the graphene layer . Seeds wTo study the difference between bilayer and double-stack graphene interlayers in more detail, the thick GaN layers of 2.5 µm were grown on both interlayer types. The optimized multi-step MOVPE protocol was used to perform nucleation at 700 °C and high-temperature growth at 1075 °C 6 and NiCl2 solution. The combination of stresses in electroplated nickel and weak bonding to the interlayer resulted in the start of epilayer exfoliation (For reliable exfoliation of thin GaN films, metal films deposited on the epilayer surface were used to generate the necessary force. The key processes are schematically presented in oliation f. Note tAfter the exfoliation, the presence of graphene was checked for both the GaN membrane and the remaining template. As revealed by Raman spectroscopy e, grapheGaN epilayers were grown on GaN/sapphire templates via graphene interlayers. The approach of multiple overlapping stacks of monolayer graphene was utilized to minimize the possibility of growth through holes. To evaluate the impact of interlayers on further growth, different interlayer types were studied: monolayer, bilayer, double-stack of monolayer, and triple-stack of monolayer graphene. Raman measurements revealed a small quality difference between the bilayer and the double-stack graphene, and indicated a higher than expected number of layers in triple-stack graphene. Studies of initial GaN nucleation split the interlayer influence into two groups: low density of aligned islands was observed on monolayer and bilayer graphene, and the high density of randomly oriented islands was observed on stacked graphene interlayers. The different nucleation mechanisms indicated remote and vdW epitaxy, respectively. Further growth of the thick GaN epilayer on the bilayer and double-stack graphene resulted in a high-quality and only partially coalesced GaN epilayer, respectively. Thus, the main focus should be on the graphene transfer: while multiple transfers allow the covering of holes and major defects, the single transfer process leads to a higher quality of resulting epilayer. The weak interaction between the epilayer and the underlying template allowed successful exfoliation of GaN membrane.


The 3- and 6-turn MI biosensors exhibited similar characteristics where the MI ratio peaked at a similar value. Our results suggest that the MI ratio can be increased by increasing the sensing area size and film thickness rather than the number of turns. We showed that an optimal film thickness to sensing area size ratio is required to obtain a high MI ratio. Our findings will be useful for designing highly sensitive MI biosensors capable of detecting low biomagnetic signals.Thin-film magneto-impedance (MI) biosensors have attracted significant attention due to their high sensitivity and easy miniaturization. However, further improvement is required to detect weak biomagnetic signals. Here, we report a meander thin-film biosensor preparation to investigate the fabrication parameters influencing the MI effect. Specifically, we hypothesized that an optimal film thickness and sensing area size ratio could be achieved to obtain a maximum MI ratio. A meander multilayer MI biosensor based on a NiFe/Cu/NiFe thin-film was designed and fabricated into 3-, 6-, and 9-turn models with film thicknesses of 3 µm and 6 µm. The 9-turn biosensor resembled the largest sensing area, while the 3- and 6-turn biosensors were designed with identical sensing areas. The results indicated that the NiFe film thickness of 6 µm with a sensing area size of 14.4 mm Magnetic sensors have received significant attention in electrical and biomedical research over the past few decades ,2,3,4. T20Ni80) permollay (Py) soft magnetic material has shown a significant contribution to the construction of MI biosensors. This material demonstrates large permeability, low magnetostriction, and no crystalline anisotropy [N film [Biosensor film thickness significantly affects MI performance. The thickness must be optimized to attain the maximum MI response with regard to magnetic material selection. Recently, the iron–nickle  process, including-beam evaporation and photoetching electroplating and other technical steps. The MI response of these sandwich meander-shaped MI biosensors was studied in different structural conditions. The results indicated that both the sensing area size and thickness had a significant influence on the MI response. We further analyzed and discussed the relationship between the number of turns, thickness, and the sensing area size of the meander lines.f defines the AC frequency, and σ and μ indicate the NiFe conductivity and permeability, respectively. In practice, the δ defines the biosensor cross-section. When the biosensor is subjected to the external magnetic field and the AC flows through it, the employed field modifies the permeability of the biosensor material, resulting in an MI effect [MI effect depends considerably on the permeability that is controlled by adjusting the biosensor geometry. Geometry includes shapes such as meander line shape, thickness, and the number of turns. Here, we optimized these structural parameters to achieve a highly sensitive MI biosensor. The MI effect of a magnetic material is usually expressed as the relative change of impedance given by Equation (2) and is expressed in Zmin [The MI effect describes the electrical impedance change in magnetic materials when subjected to an external magnetic field. In this study, nickel–iron (NiFe) was used as magnetic material, and copper (Cu) served as a conductive material for biosensor construction. MI effect variation mainly depends on the skin effect, which is the penetration of the electromagnetic field within the Cu conductive material or Cu surface when an alternating current (AC) flows through it . The penI effect . Hence,  in Zmin . It is tZmin is the minimum impedance during biosensor measurements when the magnetic field strength magnetically saturates the material. In this work, the impedance is measured when the magnetic field is off, i.e., Zmin = Z (eH = 0). When the value of Z is at its maximum, the MI is at its maximum. This occurs when the magnetic field intensity “eH” saturates the NiFe material, resulting in maximum permeability and minimum skin depth. Hence, we used a permanent magnet to generate a constant and strong magnetic field to maintain high permeability.MI response and its relationship to the magnetic field and sensor geometry. The maximum MI response occurs when Z(H) exhibits a maximum change as anisotropy affects it. The maximum MI response can be achieved by longitudinal anisotropy, which occurs when the MI biosensor is placed parallel to the applied external magnetic field and the current flow. Transverse anisotropy arises when the MI biosensor is perpendicularly positioned to the applied external magnetic field and the current flow. For the longitudinal anisotropy configuration, at eH = 0, the transverse permeability is maximum. For transverse anisotropy, the transverse permeability is at its maximum at Hk, which is given by Equation (3) [K indicates the anisotropy constant, and sM defines saturation magnetization. The maximum MI response is achieved when Hk is at its minimum.A critical factor in biosensor design is the tion (3) :(3)Hk=2KA magneto-impedance biosensor was designed and constructed using NiFe soft magnetic material. It was designed and patterned into a meander structure with a length of 5 mm and with various line widths and a gap of 60 µm between each line . Three c2O3) as an insulation layer, and 300 nm chromium/gold (Cr/Au) to be used for potential biosensor functionalization. The NiFe magnetic layer was processed to the length of 5000 μm in all configurations, a width of 160 μm in the 6- and 9-turns configurations, a width of 320 µm in the 3-turn configuration, and a thickness of 3 and 6 μm in all of the MI biosensors. The Cu conductive layer had a similar length of 5000 µm, a width of 120 µm, and a thickness of 4 µm.A meander thin-film MI biosensor was constructed with double magnetic layers based on two different thicknesses to investigate the effect of MI when it is based on thickness variation and to determine an optimal thickness to sensing area size ratio to achieve maximum MI response. 2O3/Cr/Au films, as shown in 2O3 film served as an insulation layer and was inserted between the sensing element and the immuno-platform.The overall MI biosensor design consisted of Cr/Cu/NiFe/Cu/NiFe/Al2O3 that was 300 nm thick was then deposited by means of electron-beam evaporation followed by an etching process to bare the Cu electrode  [A critical parameter in MI biosensor fabrication and measurement is the external magnetic field used to define the anisotropy during fabrication and to magnetize the magnetic sensing element during testing. A constant magnetic field Htion (3) . The layHe, as shown in ® ZVL vector network analyzer with two contact terminals. The AC flowed through the MI biosensors with a sweep frequency range of 1–40 MHz and a constant current amplitude of 10 mA, as shown in Z(H) curves and was defined by Equation (4) [The magnetic domain is defined along the meander length and width and is perpendicular to the meander plane. It resembles the longitudinal, transverse, and perpendicular MI response, as shown in tion (4) :(4)MI%=1Z(H) is the magneto-impedance when the longitudinal magnetic field eH is ON, and Z(H0) is the magneto-impedance when the magnetic field is OFF. The Z(H) is obtained by the equation for impedance, Equation (5) [tion (5) :(5)Z=R+jZ describes the impedance, R denotes the resistance, the real part of the impedance, and L represents the inductance, the imaginary part of the impedance.Z). The relative change in Z indicates the magnitude of the MI response, which is denoted as the MI ratio, and it is calculated from the Z(H) curves when the external magnetic field is applied. GraphPad Prism 7.0 software and Microsoft Excel were used to perform statistical analysis and to create plots. Optimization of the sensing area size and thickness was performed using the MI response values obtained from the biosensor. This represents the electrical impedance changes of the sensing element measured when the magnetic field was ON and OFF. The 3-, 6- and 9-turn MI biosensors were used for testing, and five measurements for each biosensor type were conducted. Average MI ratio values were derived and compared between the three biosensor types using a one-way ANOVA test. Relative standard deviation (RSD) was calculated using Microsoft Excel. The resultant sensing area size from the biosensor turns, and the different film thicknesses were compared. The optimal sensing area size and thickness was chosen based on the largest MI response and the biosensor with the least amount of variation. A bar chart was generated, and p-values ≤ 0.05 were considered statistically significant.We used Microsoft Excel to convert the real and imaginary phase data into impedance  denotes the MI response when the magnetic field eH was ON; the permanent magnet was placed at a 4 cm distance away from the MI biosensor, and Z(H0) was OFF when the permanent magnet was removed. The results indicated that the impedance change peaked at 14.2 MHz and maximized when subjected to the applied external magnetic field at 7.1 Oe. The maximum MI effect was found at 7.1 Oe when the permanent magnet was placed 4 cm away from the MI biosensor. The MI ratio was calculated based on Equation (4), where Here, the increase in the MI ratio can be partially attributed to the number of turns made by the meander line. The number of turns (9 turns) acts as a magnetic flux, where the magnetic flux of the adjacent sandwich NiFe film interacts with each other by the mutual inductance of the magnetic chain. Due to this mutual-inductance effect, the more turns that are made, the greater the change in the inductance ratio in the meander structure is. Hence, a more extensive change ratio can be obtained by Equation (4), leading to a greater MI response. Moreover, the skin effect, which is the tendency of the alternating current to become distributed within the Cu conductive layer such that the current density is larger on the surface of the Cu layer and decreases exponentially with greater depths in the Cu material (skin depth), has been attributed to the MI response increase. Here, the skin depth matches the NiFe/Cu/NiFe material thickness, whereas the NiFe is 6 µm thick, achieving a 70% increase. Furthermore, the sandwich structure geometry has contributed to MI enhancement in the areas where the large permeability magneto-inductive effect dominates the skin effect, allowing it to overcome the skin depth, resulting in large impedance changes. To achieve a higher MI response, we optimized structural parameters such as film thickness, the number of turns, and sandwich layout.In this work, the MI response peaked at 238% and 168% at 14.2 MHz under 7.1 Oe in the 9-turn sample with 6 µm and 3 µm film thicknesses. This peak value is much larger than the maximum MI ratio reported by Yang et al.,where more turns (10-turns) were employed, and the peak field of 7.1 Oe is much lower than their reported peak, 17 Oe . UsuallyeH”, of 0–20 Oe. The maximum impedance change was at 14.2 MHz under 7.1 Oe, as the permanent magnet was placed 4 cm apart from the MI biosensor. The 6-turn MI biosensor is identical to the 9-turn MI biosensor, with the exception of the number of turns used to investigate the turn impact on the MI response based on 3 µm and 6 µm film thicknesses. The same measurement setup and conditions were used: 1–40 MHz and an external magnetic field, “It is worth noting that the number of turns taken by the film is essential to the design of an MI biosensor when trying to achieve a higher MI response. We found that the MI ratio in the 6- and 9-turn models increased as the number of turns increased at the proper thickness. For the 6-µm film thickness, the MI ratio of 238% (9-turns) was higher than the MI ratio of 157% (6-turns) by 81%. It should be noted that an increase of three turns increased the MI ratio by 81%. Similarly, for the 3 µm film thickness, the MI ratio increased by 60%, from 108% to 168%, in the 6- and 9-turn configurations. Hence, the 9-turn meander line with a 6-µm film thickness could be the ideal parameters for MI biosensor design to achieve a higher MI response. As discussed above, the increase in the MI ratio can mainly be attributed to the large magnetic flux produced by the 9-turn configuration compared to the 6-turn configuration, as the magnetic flux is proportional to the number of turns. This may differ if the size of the meander line is altered; hence, further investigation is required. Moreover, the 6-turn MI biosensor displayed an MI response that was higher than the MI response reported by Wang et al. using the same biosensor conditions .The 3-turn MI biosensor exhibited similar characteristics to the 6- and 9-turn MI biosensors, with the exception of the number of turns and the width of the meander line. The width of the meander line was 160 µm wider than the 60- and 9-turn configurations. The measurements were conducted using the same setup and conditions as above.The 3- and 6-turn MI biosensors were expected to provide different MI ratios because when there are more turns, the MI ratio is higher, especially when compared to the configuration results of the 6-turn and 9-turn models. This discrepancy could be attributed to the meander line geometry of the 3-turn MI biosensor possess. Hence, further investigation is required to understand whether the MI ratio increase was mainly dependent on the number of turns taken by the meander line or the width of the turns (more details in the following sections). Still, the maximum MI ratio, 155%, in the 3-turn MI biosensor was comparable to reported MI ratios ,47,49.2 in the 9-turn configuration and 9.6 mm2 in the 6- and 3-turn configurations. The 9-turn MI biosensor contained the largest sensing area size, whereas the 6- and 3-turn MI biosensors exhibited a similar sensing area size despite the differences in the number of line turns because the line width in the 3-turn biosensor is doubled. Sensing area size variation was employed to investigate its influence on the MI effect and to determine the ratio of the optimal sensing area size to the number of turns required to enhance the MI response. Moreover, the intention was also to investigate whether the MI ratio is greatly affected by the sensing area size or the number of turns, as partially shown in the previous sections.An optimal ratio of the film sensing area size and the number of turns is critical to the design of highly sensitive MI biosensors. Here, three sensing area sizes were designed: 5 mm × 2.88 mm, 5 mm × 1.92 mm, and 5 mm × 1.92 mm. The sensing area size was determined by the number of turns taken by the meander line  and the line width, which was 160 µm wide in the 9- and 6-turn configurations and was 320 µm wide in the 3-turn MI biosensors. The resultant sensing area sizes were 14.4 mm2 sensing area yielded the maximum MI ratio, as the biosensor comprises nine turns. The 6- and 3-turn MI biosensors exhibited almost similar MI ratios, as they possess a similar sensing area size of 9.6 mm2. The maximum MI ratios based on the sensing area sizes, 14.4 mm2, 9.6 mm2 and 9.6 mm2, were 238%, 157%, and 155%, representing the 9-, 6- and 3-turn MI biosensors, respectively. Thus, the relationship between the number of turns and the MI ratio is not proportional. We noted a linear relationship between the MI ratio and the film sensing area size; the MI ratio increased as the film sensing area size increased.2) improved compared to the permeability of the 9.6 mm2 film sensing area. This could be attributed to the reduction in the eddy current loss controlled by the shape and the size of the film sensing area rather than the number of turns. It is worth noting that the eddy current loss in the 14.4 mm2 sensing area shape is much less than it is in the 9.6 mm2 sensing area biosensors. This explains why the permeability retains its value at 14.2 MHz, achieving a high MI response. Based on these results, a 14.4 mm2 sensing area size comprising a 160 µm and 5 mm meander line width and length, 9-turns, and 6 µm film thickness are the preferred parameters for designing highly sensitive MI biosensors. These findings are congruent with the MI ratio increase reported by Arribas et al., where they linked the increase in the MI ratio to the permeability changes based on different film sensing areas sizes despite using a single magnetic layer sensor [The MI response variation could be attributed to the permeability of the magnetic films affected by the meander line size. At 14.2 MHz, the permeability of the film sensing area , 9.6 mm2 (6-turns), and 9.6 mm2 (3-turns) with 3-µm and 6-µm film thicknesses . Using one-way ANOVA compassion, the %MI was not significantly different between the 3- and 6-turns MI biosensor types (p = 0.06075). Nonetheless, the 9-turn MI biosensor (6 µm thick) was significantly different and displayed the largest MI ratio compared to the 6- and 3-turn MI biosensors. Moreover, the 9-turn MI biosensor (3 µm thick) also showed a larger MI ratio than the 3- and 6-turn MI biosensors. The 3- and 6-turn MI biosensors showed similar trend variation in the MI ratio, which may be related to the similar sensing area size variations. Based on the calculated RSD values, the 9-turn MI biosensor (14.4 mm2 sensing area size) in 6 µm film thickness preserved its magnetic properties and showed excellent reproducibility with an RSD of 2.12%, indicating good precision compared to the RSD of 3.22% of the same sensor with a 3 µm film thickness. In the 6- and 3-turn MI biosensors (9.6 mm2 sensing area), the RSD increased to 3.14% and 3.10% for the 6 µm film thickness and to 4.12% and 4.04% for the 3 µm film thickness. Both the 6- and 3-turn MI biosensors displayed almost similar RSD, as they exhibited similar MI ratios. Therefore, excellent reproducibility is retained in the 9-turn biosensors.2) excellent stability was attributed to the appropriate ratio of the film thickness (6 µm) and the sensing area size (14.4 mm2), resulting in the stability and excellent superparamagnetism of the NiFe film. Here, the NiFe film thickness directly impacts the skin effect, where the permeability increases as the penetration depth decreases. The penetration depth matched the material thickness at 14.2 MHz, producing significant impedance variations. The excellent reported precision of the 9-turn MI biosensor supports the reliability of measurement results, making it a suitable biosensor for medical applications compared to other reported low MI biosensor responses. For example, MI biosensors have been reported to detect the cancer biomarker alpha-fetoprotein (AFP) with an MI ratio of 55% to 70% [MI biosensor geometry plays a vital role in magnetic signal detection. This work optimized structural parameters to achieve highly sensitive biosensors based on biosensor sensing area size, thickness, and the number of turn variations. Based on these findings, the 9-turn MI biosensor could be suitable for biomagnetic detection applications. The 9-turn MI biosensor’s (14.4 mm% to 70% ,50, the % to 70% , the pro% to 70% , and pro% to 70% .2, which resembled a 9-turn MI biosensor, is the optimum ratio yielding the maximum MI ratio. We found that the 3- and 6-turn MI biosensors shared a common characteristic: the MI ratio peaked at an almost similar value at the 3-µm and 6 µm film thicknesses. Thus, the relationship between the number of turns and the MI ratio is not proportional. We noted a linear relationship between the MI ratio and the film sensing area size; the MI ratio increased as the film sensing area size increased. It is worth noting that the magnetic peak field increased with the increase of the sensing area size and thickness, and the MI ratio in the 3-, 6- and 9-turn biosensors reached the maximum at the same magnetic field intensity indicating good stability and reproducibility. Excellent stability and reproductivity were retained in the 9-turn MI biosensors, as indicated by the low RSD of 2.12%, making its structural parameters ideal for biosensor design. These findings provide valuable information for the design of highly sensitive MI biosensors to detect weak biomagnetic signals in medical applications. However, other parameters, such as Cu conductive layer thickness, its line dimension, and the gap between each meander line, may also impact the MI response and should be investigated in future studies.We have investigated structural parameters of biosensors that are able to influence the MI effect. We fabricated an MI biosensors-based sandwich NiFe/Cu/NiFe film with a meander configuration by means MEMS technology into 3-, 6-, and 9-turn configurations with different film thicknesses prepared using electroplating technology. The structural parameters, including film thickness, sensing area size, and the number of turns, and how they influence the MI effect, have been thoroughly investigated. We speculated an ideal NiFe film thickness and sensing area size ratio to obtain the maximum MI ratio. We predicted that the MI ratio significantly depends on the sensing area size rather than the number of turns by designing 3- and 6-turn models with equal sensing area sizes to investigate this hypothesis. The MI ratio results showed a variation trend from increasing to decreasing with the increase of the film sensing area size and the thickness rather than the number of turns. The maximum MI ratio obtained by the 9-turn layout was 80% larger than the 3- and 6-turn structures at 14.2 MHz and 7.1 Oe. The NiFe film thickness of 6 µm with a sensing area size of 14.4 mm