Origanum syriacum is now a demanded product nationally and internationally. Air-drying at low temperatures can preserve za’atar quality traits better than other techniques such as oven-drying. The Palestinian za’atar market has the potential to develop and increase its value. However, it is facing many challenges. Another valuable product of za’atar is essential oil. Za’atar essential oil quantity and quality are affected by many factors including geographical location, cultivation, harvesting season, soil, extraction method, temperature, and others. These factors interact with za’atar and with each other; therefore, some factors are more effective than others and further research is needed to determine the optimum condition for producing and obtaining za’atar essential oil. Antimicrobial and antioxidant activities are the main functionalities of za’atar essential oil that are behind its medicinal importance. One hundred and twenty-one compounds have been identified in za’atar essential oil. The most common compounds are thymol, γ–terpinene, carvacrol, and α-pinene. The variation in the composition among za’atar essential oil samples results from the different conditions of the studies during za’atar growth as well as essential oil extraction.The interest in za’atar has increased in recent years due to its economic, cultural, and functional importance. The traditional za’atar mix made from dried  Origanum means “ornament of the mountains”, which comes from the Greek words oros that means mountain or hill, and ganos that means ornament. Since ancient times, Origanum species have been used as medicinal herbs. However, nowadays the importance of Origanum species in culinary practices has outgrown their therapeutic importance. Recently, several species have been used as ornamentals. The genus Origanum was first described by Linnaeus in 1754 [Origanum hybrids, varieties, species, and sub-species in the past 150 years. Seventeen hybrids, 6 sub-species, 38 species, 10 sections, and 3 groups were identified in 1980 by Ietswaart [Origanum species are distributed in the Mediterranean region. Out of the 43 species, 35 species occur solely in the East Mediterranean [Origanum species grow spontaneously in the Mediterranean region and get harvested once or twice per year during the flowering stage from wild population plants [Origanum species can be propagated using seeds, cuttings, layering, or division. The species’ growing habit and variability will determine the best method for its propagation. The species Origanum syriacum is known by different names, such as “za’atar”, Lebanese oregano, Syrian oregano, and Bible hyssop [O. syriacum is a perennial herb with height ranging from 60 to 90 cm, woody creeping roots, and branched woody hairy stems [O. syriacum culinary applications make it one of the most important stable herbs in the Arab region [Origanum secondary metabolites are well studied in both essential oils and polyphenolic compounds terms [O. syriacum essential oil are thymol, carvacrol, sabinene hydrate, γ-terpinene, and p-cymene. Many factors can affect plants’ essential oil, including genotype, geographical location, altitude, harvesting time, vegetative stage, plant part, soil, drying and storage conditions, extraction method, and others [O. syriacum has been used in folk medicine, especially in Arab countries [The word  in 1754 . More thb region . Za’atarb region . Za’atarb region . Origanuds terms . The majountries . Za’atarO. syriacum taxonomy, morphology, and distribution. We have also collected available data regarding za’atar cultivation, processing, and production. Finally, we have provided information about environmental and processing conditions that can influence za’atar essential oil, its functionality, and its composition.In this paper we have included an overview on the za’atar plant Origanum can be generally characterized as several erect sub-shrubby Labiatae, and its stems are medium-sized, it has glandular punctate, and ovate leaves. Origanum sub-terranean parts are mostly woody. Many species of Origanum, especially the species grown in the East Mediterranean region, have woody, very thick roots. The stems in almost all Mediterranean species are woody as well. The length of stems varies among Origanum species but most of them have stems with a length range of 30 to 60 cm. The leaves of Origanum are petiolate in many species, and sessile or sub-sessile in several species. There is a big variation in the shape and size of leaf blades in Origanum. Leaves’ length ranges from 2 to 40 mm, and their width ranges from 2 to 30 mm. The indumentum of leaves is similar to stems; however, the hairs on leaves are usually shorter. Two types of glands exist on the leaves: sessile and stalked glands. These also found on other parts of the Origanum plant. Stems, corollas, bracts, and calyces also have glands on them. Origanum verticillasters are arranged in dense spikes and have few sessile flowers and differentiated bracts. The inflorescences are mostly paniculate, the spikes are usually compact, and the bracts are imbricate. The number of bract pairs in a spike ranges from 2 to 40 with a mean of seven. The shape of bracts is often roundish, ovate, or obovate. Small bracts are similar to leaves in their texture, indumentum, and color, while large bracts are papery, partly purple or a yellowish-green color, and often are not hairy or just slightly hairy. Only two sessile flowers are found on a verticillaster in most Origanum species. The nutlets of Origanum species that have been seen are not different. They are brown and ovoid with 1–1.5 mm length, 0.5 mm width, and a base that is slightly acute to apiculate. Pollen grains of some species have been studied. They were suboblate, hexacoblate, or oblatespheroidal [Origanum species are distributed in the Mediterranean region. Out of the 43 species, 35 species occur solely in the east Mediterranean. Four species can only be found in the western Mediterranean, while three species grow in Libya exclusively [O. vulgare is the only species that grows in a very large area extended from the Azores to Taiwan, while most of the other species occupy small areas. A total of 70% of Origanum groups are endemic to a single island or mountain [Origanum are found when Origanum species co-occur. Usually, hybrids are considered as species initially [Origanum hybridization is common, hybrids are not usually found in large numbers. Hybridization is hypothesized to be the main method for the origin of Origanum species. It may be achieved between two species of Origanum or between an Origanum species and a related genera species [Origanum species grow in mountains and headland areas. They often grow in open or mixed coniferous woods in a partially shaded environment. However, some species, especially those belonging to the Majorana section, are found in lower altitude levels. Origanum species mostly grow on calcareous soils and almost all of them can grow on stony slopes, rocky places, and cliffs [Mainly, lusively . O. vulgmountain . Natural species . The mos species . Most Ord cliffs .Rhus coriaria), and salt [O. syriacum culinary applications make it one of the most important stable herbs in the Arab region [Locally, the term za’atar is used to refer to designated herb mixes, in which traditional ingredients are added to the za’atar herb . Za’atarand salt . This miand salt  in combiand salt , and it and salt . Za’atarand salt . The strand salt . The lowb region . Za’atarb region .Origanum, Thymbra, Thymus, and Satureja. They could be mechanically or manually crumbled but they are not provided in a powder form. Raw broadleaf za’atar products are made of the leaves and/or blossoms of wild or cultivated broadleaf za’atar from the species O. syriacum (by at least 75%) or as a constitute (by 25% maximum) in a mixture of leaves and blossoms of the varieties: Origanum ehrenbergii, Thymbra spicata, Coridothymus capitatus, Thymus syriacus, and Satureia thymbra. Like raw za’atar, the mix could be manually or mechanically crumbled but it is not provided in a powder form. Mixed za’atar products are made of raw za’atar and raw broadleaf za’atar in addition to the husk sumac and sesame seeds. Other ingredients could also be added. Za’atar mix products are classified into three categories: Premium, Extra, and Regular mixed za’atar. Premium mixed za’atar must contain at least 25% broadleaf za’atar mixed with sumac husk and sesame seeds only. A maximum of 6% salt can be added. Extra mixed za’atar contains 20% broadleaf za’atar and raw za’atar mixed with sumac husk and sesame seeds. Grains, nuts, spices, and condiments could be added as well. Like Premium mixed za’atar, only a maximum of 6% salt can be added. Regular mixed za’atar composition is at least 15% broadleaf za’atar and raw za’atar mixed with at least 5% sumac husk and sesame seeds in addition to other ingredients. Regular za’atar mix can contain aromatic grains and herbs, legumes, pomegranate molasses, vegetable oil, wheat bran, sesame seed hull, spices, condiments, and nuts, all of which must meet good manufacturing practices. It is possible to add a maximum of 7% salt and 4% citric acid with an indication of that on the label [According to the Codex Alimentarius Commission Food and Agriculture Organization—World Health Organization, FAO–WHO, 2017 on za’atar mix standardization, there are three types of za’atar products: raw za’atar, raw broadleaf za’atar, and mixed za’atar. Raw za’atar products are composed of the leaves and/or blossoms of the wild and cultivated plant species: he label .Origanum species and sub-species leaves in both processed and semi-processed products, and published it in the ISO 7925 report in 1999. The ISO requirements included: oregano odor and flavor must be aromatic, warm, fragrant, pungent, and bitter, and be free of foreign flavors; oregano products should be free from insects, molds, etc.; extraction matter should not exceed 1% by mass in processed products and 3% in semi-processed products; and oregano plant parts such as stalks should not exceed 3% in the products. Ground oregano must completely pass through a sieve with a 500 μm nominal aperture size. Za’atar must have special flavor and odor without any external flavors and odors that may come from molds, rancidity, or any other substances. Additionally, the color of za’atar mix products should be normal and consistent with the color of such products. All ingredients used for the preparation of za’atar mix products should meet their Codex Alimentarius standards. They should not contain any living insects or spiders, and should be reasonably free from any noticeable molds, dead insects, parts of insects, or rodents, birds, and snail waste. Za’atar mix products must not be in a powder form to guarantee that all the main ingredients of the mix can be seen at a microscopic level or by the naked eye. This will ensure avoiding frauds and impurities concealment. It will also maintain a higher level of essential oil. If the product contained straws, they should not make more than 5% of the mass of the products, and they should not be more than 10 mm in length and 2 mm in diameter. Any non-vegetable origin substance such as soil, dust, sand, etc., or non-food vegetable substance such as wood or dry leaves found in za’atar mix products, should make more than 1% of the mass of the product. Za’atar production practices include seedling propagation, cultivation in the field, weed and pest control, irrigation and fertigation, and finally, harvesting and processing. Za’atar has a very short shelf life that is only 2 days. Therefore, they must be stored away from heat and dry wind in order to keep their freshness . Za’atarO. syriacum. It also reported that air-drying was the best for preserving the aroma, flavor, and color compared to oven- and freeze-drying [O. syriacum, while drying at a higher temperature produced O. syriacum with higher phenols content. It was also reported that shade drying at lower air velocity was the best for preserving alpha-tocopherol content [O. syriacum growing in Lebanon. The resulting data collected during two summers showed that O. syriacum height significantly and positively increased with irrigation frequency level from low to medium (66.3–73.2 cm) and from medium to high (73.2–81.5 cm). Similarly, branching increased with increasing irrigation level, reaching the maximum branching with medium irrigation level, and starting to reduce slowly beyond this level. Accumulation of dry matter as well was negatively affected by increased soil moisture. Therefore, it was suggested that medium irrigation water stress level is required for the prevention of reduced plant branching and dry matter accumulation. An increase of 1.7- and 2.2-fold was observed when increasing the irrigation level from low to medium. However, additional increases beyond medium level did not show more increases. Flower yield was increased by 2-fold in the high irrigation level but the validity of this conclusion is limited due to the high standard deviation of the flower yield data. The levels of thymol and carvacrol in the essential oil of O. syriacum were not statistically different in the different irrigation levels. Drying of O. syriacum was carried out by three different drying technologies: air-drying in a shaded area for 10 days at 25 °C and 45% relative humidity, oven-drying by convection oven at 30 °C for 47 h in 1.2 m/s air velocity and freeze-drying at 0 °C initial temperature for 48 h. The results of the sensory analysis of dried O. syriacum revealed that air-dried O. syriacum had a higher preservation of aroma and flavor than the oven- and freeze-dried O. syriacum. The flavor of air-dried O. syriacum was marked as strong, bitter, pungent, warm, and astringent, while the aroma was marked as camphor-like, strong, and pungent. Freeze-dried O. syriacum flavor and aroma received lower scores with increased undesired earthy and musty aroma. This could have resulted from the presence of sesquiterpenes in freeze-dried O. syriacum. Both oven- and freeze-drying would cause a loss of carvacrol in the essential oil of O. syriacum, leading to the loss of the warm and pungent aroma and flavor. There were significant differences among color scores of air-, oven-, and freeze-dried O. syriacum. According to the study experts, air-drying produced the desirable grayish-green color that is also required by the international standards. Financial analysis showed that the medium irrigation level and air-drying production scenario was not found to be economically feasible due to the high operation and maintenance costs, mainly. However, reducing the product positioning, e.g., by using low-value jars, might make this scenario economically feasible.Limited data about the processing effects on za’atar quality attributes are available. In e-drying . Air-drye-drying . Another content . Every p content  investigp < 0.05) effect of storage on the assays was observed, except in the fresh samples. This could have resulted from the immediate vacuum-packed at −20 °C storage after the treatments. The absence of oxygen together with the low temperature in the storage environment inhibited the enzymatic oxidation of antioxidants in dried herbs. On the other hand, storing fresh samples at −20 °C caused severe chilling injury due to the presence of a high level of moisture and the loss of plants’ integrity. The highest release of antioxidants in fresh samples was observed on day 15 with no further loss observed after that. However, the woody herb thyme was not affected by the chilling injury and no increase in its TP and antioxidants capacity occurred in the fresh thyme sample when stored at −20 °C. All three drying methods were similar in their efficiency and produced typical amounts of dry weight. The higher contents of TP in the dried samples compared to the fresh ones were suggested to be caused by the breaking of cell walls when the brittle dry herbs were milled and homogenized, which increased the release of phenolic compounds. Another suggested reason was the enzymatic degradation of antioxidants in the fresh sample, where the enzymes were active due to the presence of moisture. Air-dried samples had the highest levels of both TP content and antioxidant capacity. In air-drying, herbs lose moisture gradually, which might allow the metabolically active plants to sense this stress and produce phenolic compounds as a defense mechanism. This was proved by the significantly (p < 0.05) higher content of rosmarinic acid in air-dried samples compared to both fresh and other dried samples. Rosemary and thyme were the only herbs that showed significant (p < 0.05) differences in TP content and antioxidant capacity among vacuum oven-dried and freeze-dried samples. The vacuum oven-dried rosemary sample showed significantly higher TP content and FRAP level than freeze-dried rosemary, but no significant ORAC difference was found between them. Thyme showed the highest difference between TP content and antioxidant capacity in the vacuum oven- and freeze-dried samples among all herbs. Intact tissues in woody herbs such as thyme and rosemary act as barriers against phenolic compound release, which reduces their antioxidant capacity. The higher levels of TP content and antioxidant capacity in vacuum oven-dried samples than freeze-dried samples might be due to the reactivation of degradation enzymes in freeze-dried herbs or the release of phenolic compounds by the high heating temperature during vacuum oven-drying. Wakim et al. [O. syriacum from Rkai and Ibrine regions. Solar drying, shade drying, and four drying treatments using forced air artificial dryers with two different temperatures (26 and 45 °C) and two different air speeds (0.1 and 0.2 m/s) were used. For both O. syriacum types, the decrease in chlorophyll content was more noticeable at the high temperature of the solar drying and the dryers at 45 °C. On the other hand, there was not a noticeable loss in chlorophyll content at 26 °C with 0.2 m/s drying, followed by shade-drying, and then 26 °C with 0.1 m/s drying. It was reported that pheophytinization accounted for the loss of chlorophyll. There was a similar rate of thymol and carvacrol loss in both O. syriacum types, and drying at 45 °C caused a lower loss than other drying treatments. The loss of polyphenols was found to be the highest after drying at 26 °C and 0.1 m/s and lowest after solar-drying and drying at 45 °C and 0.2 m/s. This might have resulted from the decomposition of some phenolic compounds by heat. This action produces other structures that increase the level of phenolic compounds after drying at a high temperature. Besides, drying at lower temperatures in shade-drying and drying at 26 °C showed a significant loss in polyphenols due to the prolonged time of drying. Shade-drying was the best method for preserving alpha-tocopherol in both O. syriacum types. A great loss in all tocopherols was caused by drying at a high temperature. Moreover, drying at 0.1 m/s air speed was more advantageous than drying at 0.2 m/s. Higher losses of tocopherols in Ibrine type than Rkai type were observed after drying at 45 °C and 0.2 m/s. Similarly, the tocopherol content loss was also lower in Rkai type after drying at 45 °C and 0.1 m/s. It was suggested that those differences are due to the presence of iron or copper sulfate in Ibrine type, which can speed up tocopherol oxidation. Drying in shade is the most proper method to preserve tocopherols in both types of O. syriacum, because the high temperature that increases the loss of tocopherols is not used in this method. Carotenoid loss rates were higher after drying at the higher temperatures in solar-drying and at 45 °C than drying at 26 °C. The loss of carotenoids was more pronounced in Rkai type. Carotenoids are easily decomposed in the presence of oxygen, light, and copper, and by the effect of temperature. Thus, solar-drying and drying at 45 °C resulted in higher losses of carotenoids than shade-drying and drying at 26 °C. Another reason behind the higher preservation of carotenoids in drying at a lower temperature is the lower oxidation of fat that produces peroxides that can destroy carotenoids. It was difficult to determine a favorable method of drying for the preservation of all the substances in the study.Hossain et al.  investigm et al.  studied O. syriacum) is not just a symbol of Palestine; it has also a great economic value. The economic value of growing and processing za’atar had become more viable in the last decade. The za’atar market has been greatly growing in recent years. Over 6000 dunams are planted with O. syriacum in the northern West Bank, while only 500 dunams were planted in za’atar before 2010. The increasing demand by foreign companies has expanded the cultivated land of this herb. The za’atar market has a good profit; it regains its capital quickly, keeps producing for 7 years, has an average of harvesting every 40 days, and is resistant to pests and diseases. Palestinian za’atar farmers earn about 144 million New Israeli Shekel (NIS) annually. More than 85% of processed za’atar is sold in the local market, and the other 15% goes to the export market. The majority of produced za’atar is fresh-cut za’atar with an estimated 15,000 tons annually. The final marketed product of za’atar ranges from 20 to 29% (average 24%) compared with the freshly harvested biomass. Commercial production of za’atar is new in Palestine; it represented only 3% of the total exported herbs in 2013, but the production is growing and it more than doubled in both value and volume after two years, reaching 763 tons of dried za’atar and 329 tons of fresh za’atar in December 2016, according to the Palestinian Ministry of Agriculture. However, there is an export demand for other types of za’atar that are not known locally, but there are no research centers that can work on the hybridization and development of such kinds of za’atar. Palestinian O. syriacum is not labeled by its scientific name; it is usually labeled as oregano or its Arabic name, za’atar. The end market of Palestinian za’atar is still dominated by about 42 cooperatives, hundreds of women’s groups, small-scale farmers, and about 16 processing industries. These processers are mainly located in Nablus and Jenin where most za’atar harvesting is carried out. A total of 200 workers produce za’atar and other kinds of herbs in these processers. A total of 70% of za’atar production in Palestine is done by commercial manufactures, while the other 30% is produced at homes and consumed locally. Some of the manufacturers buy fresh za’atar from farmers in big volumes during the peak of the season to reduce the costs. In Palestine, za’atar is commonly consumed in a dried form either alone or in za’atar mixes. Palestinians and people in regional countries prefer za’atar mixes for their strong, unique flavor. Only a small amount of za’atar from Jordan and Turkey is imported to Palestine each year, while Palestine exports za’atar to many countries including Jordan, Canada, Gulf countries, EU, and USA countries. About 70% of exported za’atar is in the dried form and most of it is exported in bulk to Jordan. Only some private-labeled packaged za’atar products are exported to Europe and the US. The Palestinian za’atar market is not big enough to reinforce an active industry. Therefore, za’atar producers and processors should concentrate on the export market to make a high-quality volume. To achieve this, local producers and processors will need to invest in developing export capabilities. Moving from exporting bulk raw za’atar to packaged branded products will significantly increase the Palestinian export value. Unfortunately, many challenges are facing the Palestinian za’atar market’s growth. It was found that Palestinian za’atar is re-exported from Israel to important markets as Israeli za’atar. Additionally, the cultivation of za’atar in Palestine is still difficult since its native areas are under occupation. Another challenge is the presence of competitor suppliers such as Jordan, Turkey, Lebanon, and Syria. These suppliers can compete on price, quality, and consistency of supply. Palestinian growers face difficulty in providing products with consistent quality, supply, and price. Manufacturers prefer other sources to buy raw materials, especially sumac and sesame, where they buy it from Turkey, Ethiopia, and Egypt. Other problems in Palestinian za’atar processing and production include: farmers are unorganized, the use of unsafe fertilizers, lack of equipment, lack of safety and standards certifications, some essential ingredients’ availability, quality and high cost, and very little production and processing of organic za’atar. Many factors need to be improved to solve these problems, including agriculture and propagation practices, research, processing and preservation technologies, quality control, marketing, legalization, and others [Palestinian za’atar , while the positive correlation between essential oil yield and organic matter, nitrogen, and potassium was low and insignificant. Gas chromatography-mass spectrometry (GC-MS) results show that soil pH and composition affected the essential oil contents. Both soil pH and P2O5 content were significantly negatively correlated with carvacrol, thymoquinone, and p-cymene, and they were significantly positively correlated with thymol, while thymol was significantly negatively correlated with nitrogen, K2O, and organic matter content [O. syriacum essential oil with high thymol content. On the other hand, nursery, potting, professional agricultural mixtures, sterilized inoculated, sterilized non-inoculated, and non-sterilized inoculated soils produced O. syriacum essential oil high in both thymol and carvacrol. Water, organic matter, and mineral rate improve the essential oil yield. Moreover, arbuscular mycorrhizal fungi (AMF) enhances the water and nutrient intake and plant growth, which improves essential oil yield as well. It was noted that AMF promoted the carvacrol and reduced the thymol levels in O. syriacum essential oil [Soil pH and composition have an impact on both ffect it ,23. Thertial oil .O. syriacum essential oil yield before and during extracting [Besides the effect of the environmental factors on za’atar essential oil, extracting and identification methods can also have an impact on za’atar essential oil yield and composition. Hydro-distillation produced higher essential oil yield compared to supercritical-fluid-extraction (SFE) in a study . One stutracting . Static tracting . Anothertracting . It was tracting .O. syriacum essential oil yield included the plant part in which essential oil was extracted [O. syriacum essential oil yield and composition [Other factors that were reported to influence xtracted , the dryxtracted , and thextracted , while uposition .Origanum genus comes from its antioxidant, antimicrobial, antifungal, antispasmodic, antimutagenic, anti-inflammatory, and analgesic properties. It has been used as an ethnomedicine for thousands of years. Origanum has been used as carminative, stimulant, tonic, and diaphoretic. Turkish folk medicine has used Origanum for gastrointestinal problems as an antiparasitic, antihelminthic, and expectorant. It is suggested that the synthesis and release of inflammatory mediators are influenced by the carvacrol in Origanum essential oil. Thus, it makes it useful in treating gastric ulcers. Folk medicine also uses Origanum in the treatment of cough, colic, irregular menstrual cycle, and toothache. It has also a promising potential in preventing diabetes complications [Origanum and its different roles in the treatment of various health problems including respiratory, gastric, and urinary tract disorders, dermatological affections, viral infections, and cancer [Origanum can be used as a disinfectant and flavoring agent for soups, perfumes, and food products [Origanum species that have been used for their medicinal properties include O. syriacum, O. vulgare, O. dictamnus, and O. majorana [O. syriacum has been used in folk medicine, especially in Arab countries. It has an antiseptic activity, and it is helpful in stomach and intestinal pain relief, heart disease, cough, cold, wounds, toothache, and anxiety [O. syriacum effects in his worldwide popular book “The Canon of Medicine”. He said: “it is a good analgesic for joint pain, chewing the leaves relieves both gum and toothache. When rubbed upon chest it relieves bronchitis, it has a beneficial effect on the liver and stomach and a strong anthelmintic effect”. Additionally, the doctor, pharmacist, and astronomist Dawud ibn ‘Umar al-Anṭākī (1534–1592 AD) talked about O. syriacum in one of his books. He said that it is “an antidote for many poisons, a carminative, for detoxification of the organism, as a blood thinner, for loss of appetite, as an anthelmintic and food preservative.” [O. syriacum in folk medicine are different according to the country. For example, it is used for treating stomach pain in Jordan, while in Turkey it is used for cold symptoms mainly [The medical importance of the ications . Many std cancer . Besidesproducts . Origanumajorana . O. syri anxiety . The famvative.” . The uses mainly .Origanum essential oil and its components. These activities have been mainly classified as antibacterial and antifungal activities. It is believed that phenols are the most powerful antimicrobial compounds in the essential oil. The next most powerful antimicrobial compounds are alcohols, followed by ketones, ethers, and then hydrocarbons [O. syriacum has an antibacterial property against both Gram-positive and Gram-negative bacteria, which make it useful for both bacterial infectious diseases and food preservation. Essential oils’ hydrophobic nature allows them to be embedded in the membranes of the cell and the mitochondria, break them, and throw out their contents. Some conditions such as low pH, temperature, and oxygen levels can improve its antibacterial activity. Similarly, antifungal activity is also an important property of O. syriacum essential oils. It plays a role in preserving food and treating infectious diseases, as well as plant pathogenic fungi that can cause significant losses for farmers [O. syriacum essential oil at different degrees. Variable concentrations and concentration units were used by the studies. O. syriacum essential oil’s antimicrobial effect is mostly concentration-dependent. It has interesting inhibitory effects that are comparable to synthesized antimicrobial effects. It was also reported in a study that O. syriacum essential oil could improve the effect of some antimicrobials [O. syriacum essential oil was effective against antimicrobial-resistant bacterial strains in two studies [O. syriacum essential oil [O. syriacum essential oil. It was reported that the essential oils with the richest γ-terpinene and α-terpinene levels have the highest antibacterial activity in a study [O. syriacum essential oil was found to exhibit higher antimicrobial activity than wild O. syriacum essential oil in a study [O. syriacum.An abundant number of studies have reported the antimicrobial activities of ocarbons . The ant farmers . Many microbials . O. syri studies ,41. Sometial oil ,26,32. D a study . Cultiva a study . Table 5Origanum plants have been considered effective scavengers of the human body’s metabolic pathway free radicals [O. syriacum. Antioxidant activity protects cells from harmful free radicals and reactive oxygen species (ROS). The antioxidant activity also improves endothelial function, stimulates DNA repair, and has anti-inflammatory action. Many studies indicated that phenolic compounds and flavonoids in essential oils are responsible for the antioxidant activity. It was also found that O. syriacum essential oil exhibits an antiparasitic activity that might be due to its phenolic compounds, such as thymol and carvacrol, flavonoids, and terpenoids [O. syriacum essential oil showed antioxidant activity in a wide range of assays. Similar to the antimicrobial activity, variable concentrations and concentration units were used by the studies. One study tested the antioxidant capacity of O. syriacum essential oil compounds as well [O. syriacum essential oil was concentration-dependent [O. syriacum essential oil exhibited higher antioxidant activity than fresh O. syriacum essential oil [O. syriacum.Antioxidant dietary supplies from radicals . A largerpenoids . Assessirpenoids . O. syri as well . Three sependent ,19,45. Atial oil . It was O. syriacum oral administration on blood was found in an animal study [Several interesting activities of za’atar essential oil were found, including tocolytic , anti-inal study , which m


Molecularly imprinted polymers (MIPs) are obtained by initiating the polymerization of functional monomers surrounding a template molecule in the presence of crosslinkers and porogens. The best adsorption performance can be achieved by optimizing the polymerization conditions, but this process is time consuming and labor-intensive. Theoretical calculation based on calculation simulations and intermolecular forces is an effective method to solve this problem because it is convenient, versatile, environmentally friendly, and inexpensive. In this article, computational simulation modeling methods are introduced, and the theoretical optimization methods of various molecular simulation calculation software for preparing molecularly imprinted polymers are proposed. The progress in research on and application of molecularly imprinted polymers prepared by computational simulations and computational software in the past two decades are reviewed. Computer molecular simulation methods, including molecular mechanics, molecular dynamics and quantum mechanics, are universally applicable for the MIP-based materials. Furthermore, the new role of computational simulation in the future development of molecular imprinting technology is explored. Molecularly imprinted polymers (MIPs) are porous materials with specific recognition capacity towards the template molecule, which are obtained by self-assembly of template molecules and functional monomers in a porogen, and then polymerization is initiated in the presence of a cross-linking agent. The process of preparing MIPs is outlined in Computational simulation has rapidly developed in recent years. It uses computer technology as a carrier and combines the theoretical basis of quantum mechanics and statistical mechanics as a tool-based cross-discipline. Molecular simulation calculation employs computer technology to simulate changes in the static structure and dynamic motion of molecules by calculating and comparing the relationship between the form and energy of the interaction between molecules to effectively explain the mechanism of action at the molecular level. The method is simple to operate and not restricted by the space environment, and the calculation is accurate and efficient. At present, many reports on the application of computational simulation in molecular imprinting technology have been published ,24,25,26The methods used in the theoretical calculation and simulation of various MIP designs are molecular mechanics (MM), molecular dynamics (MD), and quantum mechanics (QM). The computational cost of MM optimization is considerably lower than that of QM, and thus it is orders of magnitude faster than the latter. However, the accuracy of MM results is limited by simplified calculation models, which allow the reduction in calculation costs. The QM approach can better solve the problem of choosing the appropriate initial direction of interacting molecules because it is more accurate than the other methods. However, the computational complexity of the QM approach exponentially increases as the number of molecules involved in the calculation system increases. The MD method can effectively address this problem. When simulating the dynamic process of the interaction between molecules, changes in the molecule itself are often not considered, thereby making the calculation of the simulation method more efficient. Therefore, the MD method is most widely used when numerous molecules are involved in designing MIPs, such as in optimizing the ratio of template, monomer, and cross-linking agent. The application of MM, MD, and QM methods in MIP simulation is given in The MM method treats molecules as a collection of atoms held together by elasticity or resonance force. It uses energy functions, such as internal energy terms, including bond length, bond angle, and dihedral angle changes, to calculate changes in the molecular internal energy caused by changes in molecular structure. Combined with nonbonding energy (electrostatic interaction), these potential energy functions are called potential functions, and their parameters can be obtained by fitting quantum chemistry calculation results or experimental data. The MM method can optimize the molecular static structure of thousands of atomic systems; perform molecular structure optimization, system dynamics, and thermodynamic calculations; and select the smallest energy and the most stable molecular conformation in the space structure. However, this method ignores the movement of electrons and cannot simulate the state of electron movement in chemical reactions, thereby lowering the accuracy of the calculation ,85,86.Common force fields used in MIP calculation simulation by MM method are OPLS3, CHARMM, MMFF94, AMBER MM and MMFF94X. Compared with other commonly used small molecule force fields, the OPLS3 supplies reference data and related parameter types which exceed one order of magnitude. Therefore, this force field achieves a high level of accuracy in the performance benchmark for assessing conformational propensity and solvation of small molecules. It is mainly suitable for liquid systems, such as peptides, proteins, nucleic acids, and organic solvents. In addition, it employs lots of reference data and related parameter types; this also limits its use in the simulation of small molecule systems. The CHARMM force field is mainly used for the simulation of biological macromolecules, including energy minimization, molecular dynamics and Monte Carlo simulation. The simulation process provides information about molecular structure, interaction, energy, etc. The MMFF94 force field provides good accuracy in a series of organic and pharmaceutical molecular simulation calculations. The core parameterization is provided by high-quality quantum computing without a large amount of experimental data for testing molecular systems. It performs well in optimizing geometry, bond length, angle, as well electrostatic and hydrogen bonding effects. The AMBER force field also has significant and extensive applications in the field of simulation and calculation of biological macromolecules. Its advantage lies in the calculation of biological macromolecules, but the calculation results of small molecule systems are often unsatisfactory.MD methods can clarify the macroscopic properties of particles in dynamic motion. In 1957, Alder and Wainwright developed the MD technology. They computationally simulated the behavior of hard balls in boxes at different temperatures and densities. This method aims to establish a particle system via Newtonian mechanics and statistical mechanics, calculate the speed and position of molecules, obtain the state of motion of molecules, and integrate the dynamics and thermodynamic properties of systems. It is based on molecular mechanics and considers the influence of external environment, such as temperature and pressure, to calculate the molecular structures  and thermodynamic parameters of molecules in motion. The calculation result is close to the real state. The application of MD in molecular imprinting is illustrated in The Tripos force field in the MD method has been proven to produce molecular geometry close to the crystal structure for different molecular selections. This force field has good calculation results in both protein and organic molecular simulations. The COMPASS force field is the first molecular force field based on ab initio calculations, which can accurately predict the molecular structure, conformation, vibration, and thermodynamic properties of isolated and condensed molecules. The COMPASS force field is also the first molecular force field that unifies the organic molecular system and the inorganic molecular system that were previously treated separately. It can simulate organic and inorganic small molecules, macromolecules, some metal ions, metal oxides and metals. The GROMOS force field guarantees the accuracy of the parameters through a series of quantum chemical calculations and existing databases. Most importantly, this force field fully considers the symmetry of the molecular structure to make the simulation more perfect.Many reports on the application of computational simulation in molecular imprinting technology have been published. Most of them used QM-based calculation methods. The primary QM simulation calculation methods are ab initio calculation methods, semiempirical calculation methods, and density functional theory (DFT) methods.The ab initio calculation method is based on the Hartree–Fock method. This method uses some of the most basic physical constants, such as the speed of light and Planck’s constant, as known parameters, and it adopts mathematical methods to calculate molecular physics and chemistry without introducing empirical parameters. In this method, the SDCI method is applied to both the single excited and double excited states of molecules. Other methods, such as CISD(T) and MCSCF, consider different variables. The ab initio calculation method is not limited to the structure of small molecules as it can also calculate the static and dynamic properties of macromolecular systems, including intramolecular and intermolecular interactions ,88. The The semiempirical method introduces some experimentally measured parameters on the basis of the ab initio calculation method, simplifies the Hartree–Fock method, and reduces the amount of experimental calculation. This method can calculate and simulate the electronic structure and properties of real biological systems, such as enzymes and proteins. Other calculation methods are available: AM1, PM3, EHMO, CNDO, and NDDO. Among these methods, AM1 can predict the existence of hydrogen bonds between molecules by calculating the activation energy of particles. However, when it is used to calculate thermodynamic properties, such as the enthalpy of particles, large errors are committed. PM3 usually has a small error, and it is used in molecular simulations and theoretical calculations . HoweverThe DFT method is based on the Hohenberg–Kohn principle. It uses the electron density function in molecular simulation. The computational complexity of this method is small, and it can calculate molecular bond energy , predictThe calculation methods of theoretical molecular simulation used in molecular imprinting technology largely adopt the QM method. However, the QM method also has shortcomings. This method can only qualitatively predict the type of interaction between molecules but cannot accurately describe the energy changes of complex mixtures. Therefore, the previous research using this method for theoretical simulation has mostly applied to the qualitative description of molecular systems ,98. The The application of theoretical calculations in designing MIPs is primarily achieved by theoretical simulations and selection of appropriate functional monomers, template molecules, crosslinkers, and their ratios. The binding energy  between the template molecule and the functional monomer can be simulated and calculated provided that the binding energy between the template molecule and the functional monomer is high, indicating that the corresponding MIPs have excellent selectivity and adsorption performance. In addition, the ratio of the molecular and monomer system is closely related to the imprint factor of MIPs. In general, this ratio is calculated and optimized by performing the computational simulation in a vacuum environment to obtain the Eqaution (1) for the binding energy between the template molecule and the functional monomer.ΔESolvent is the energy difference between a template molecule and a functional monomer in solution and in a vacuum environment. A weak influence of the solution on noncovalent interactions during molecular fingerprint polymerization results in a small energy difference value, suggesting that the solvent is the best polymerization solvent for obtaining molecular fingerprint polymers [In most cases, vacuum simulation calculations often differ from the actual situation as they consider the effects of spatial media, including the addition of solvents, to make the simulation calculation highly consistent with experimental results. The solvent  affects the energy of the system during the synthesis of MIPs. The results of molecular modeling can be made closer to real situation and the reliability of the results can be increased by conducting the simulation of a molecular fingerprint polymer in a solvent medium. The binding energy is calculated by Equation (2):polymers ,100.The primary factor in MIP imprinting polymerization is the strong bonding force between the template and the functional monomer. Therefore, choosing the right functional monomer is a key factor in designing MIPs. An MIP can be reasonably designed by applying the DFT method in selecting the monomer with the best interaction with 2-isopropoxyphenol; it can be combined with the PM3.5 method to optimize the template-to-monomer ratio . QuantumThe strongest interaction site can be further located by obtaining the electrostatic potential map on the surface of the template molecule via the DFT method . Figure n) complex system with the smallest energy value. It obtained the theoretical parameters of intermolecular interactions and provided a reliable theoretical basis for the interaction between the template and the monomer. Similar molecular simulations of combining DFT and MD methods had been used in furazolidone [The key to the selectivity and enrichment ability of MIPs lies in the formation of a stable complex between the template and the functional monomer. Therefore, choosing the right functional monomer is an important factor in designing MIPs. The DFT method had been employed to study intermolecular interactions between harmane and functional monomer . Firstlyzolidone  and kojizolidone  imprintezolidone . Before The DFT calculation method had also been used to explore the influence of different porogens on the binding energy of nicotinamide to monomer methacrylic acid . TemplatBaggiani  applied 2 as a solvent into the model. The theoretically designed itaconic acid MIP exhibited a high affinity and selectivity to acetamide.An imprinted polymer membrane that can selectively adsorb atrazine in an aqueous medium can be developed  using thMolecular simulation methods are also used in designing and synthesizing dummy template MIPs. Feng  adopted Molecular simulation calculation can be also performed in designing chiral enantioselective imprinted polymers. Sobiech  preparedTheoretical simulation can also provide a theoretical basis for the identification mechanism of MIPs. The formation process of experimentally proposed magnetic molecularly imprinted polypyrrole at the molecular level can be understood via the DFT method to obtain the thermodynamic properties of the prepolymerized template and the monomer complex in the presence of water. On the basis of the negative values of ΔG and ΔH, this results in the complexation of the monomer with praziquantel in aqueous solution spontaneously forming stable complexes. Moreover, the results of molecular geometric conformation simulation showed that four hydrogen bonds and one π–π stacking interaction are established between praziquantel and pyrrole, which explains the formation of praziquantel and pyrrole prepolymer complex at the molecular level . ThroughN-(4-isopropylphenyl)-N′-butyleneurea MIP to phenylurea herbicides [The selective mechanism of ciprofloxacin-imprinted membrane was also further explained through molecular simulations . The binrbicides . This merbicides  and the rbicides  at the mYang  performeComputer molecular modeling technology has been applied to the screening and optimization of molecules in many materials, and it is also a feasible method for preliminary exploration of MIP. Computer simulation reduces the time and reagent-related costs required to obtain the appropriate MIP adsorbent, and significantly reduces the consumption of organic solvents. In addition, it can explain the specific recognition mechanism of imprinted materials at the molecular level. For all the above reasons, the use of computer molecular simulation to design MIP adsorbents in analytical practice not only conforms to the principles of green analytical chemistry, but also explains the nature of MIPs binding to target molecules from the intermolecular forces. The QM method, compared with other methods, can ensure more accurate simulation results in the MIP system dominated by non-bonding interaction, because the smallest structural unit electron was studied and the quantum effect was considered in the method. Therefore, the QM method is also the most widely used in MIP simulation operations. However, in the simulation of macromolecules and polyatomic systems, this method is very time-consuming and even prone to errors. MM and MD are classical mechanics methods. Their smallest structural unit is no longer an electron but an atom. Therefore, the simulation operation complexity of the imprinting system is greatly reduced, and the operation speed is faster. MM method directly utilizes the potential function to study the problem, without considering the kinetic energy and the corresponding structure of the atom. However, the MD method focuses on the movement of atoms in the MIP system and establishes the relationship between temperature and time, which can simulate the imprinting system more realistically, and the simulation results are more representative. In general, the DFT procedure in the QM method was recommended in the MIPs design and mechanism interpretation simulation calculation. However, this also means that the computational complexity of this method increases dramatically for large molecules and systems with a large number of molecules. MD method may be the best solution at this situation, simulated annealing process in particular, which can complete the lowest energy conformation search in a very short time. At present, an increasing number of research have been using multiple calculation methods to achieve complementary advantages when designing and optimizing the experimental parameters of MIPs preparation, so as to ensure more efficient and accurate simulation results. In addition, simulation is also the direction of current efforts. A more realistic simulation environment can make the calculation results accurate and reliable.


Fast growing scientific topics have famously been key harbingers of the new frontiers of science, yet, large-scale analyses of their genesis and impact are rare. We investigated one possible factor connected with a topic’s extraordinary growth: scientific prizes. Our longitudinal analysis of nearly all recognized prizes worldwide and over 11,000 scientific topics from 19 disciplines indicates that topics associated with a scientific prize experience extraordinary growth in productivity, impact, and new entrants. Relative to matched non-prizewinning topics, prizewinning topics produce 40% more papers and 33% more citations, retain 55% more scientists, and gain 37 and 47% more new entrants and star scientists, respectively, in the first five-to-ten years after the prize. Funding do not account for a prizewinning topic’s growth. Rather, growth is positively related to the degree to which the prize is discipline-specific, conferred for recent research, or has prize money. These findings reveal new dynamics behind scientific innovation and investment. Scientific revolutions have famously inspired scientists and innovation but large-scale analyses of scientific revolutions in modern science are rare. Here, the authors investigate one possible factor connected with a topic’s extraordinary growth—scientific prizes. Classical studies of extraordinary growth focus on the specifics of illustrative cases, such as the Copernican revolution and its associated changes in astronomical topics’ productivity and impact on scientific thinking4. Newly-available, large-scale data on nearly all scientific topics enables the study of periods of extraordinary growth from a statistical perspective. Here we investigate generalizable factors associated with the onset and magnitude of the extraordinary growth of scientific topics using a large and diverse sample of scientific topics7.The extraordinary growth of a scientific topic occurs when there is a period of unexpected and abnormally large growth in a topic’s impact or size9. Scientific prizes were originally restricted to certain scientific disciplines and topics, but they have proliferated and are now awarded in nearly all disciplines9. Prize research has primarily studied how awards change prizewinners’ careers16 by recognizing18, celebrating19, and changing perceptions of a scholar’s work21. For example, case studies of Howard Hughes Medical Investigators and John Bates Clark and Fields medalists have shown that prizewinners’ papers published before their prize is conferred gain citations significantly faster than expected22 after the prize and that winning one prize increases the probability of the same scholar winning future prizes9.We investigated the statistical dynamics around a possible correlate of the onset of a scientific topic’s extraordinary growth: a topic’s association with a scientific prize24. On the other hand, scholars have claimed that prizes signal that the best work associated with a topic has been done, which would lessen rather than an expand interest in a topic25. An impression reinforced by the fact that prizewinners tend to move onto new topics after winning a prize12 and the papers by matched contenders for the prize are concommitently cited less than expected12.It is uncertain whether the link between prizes and unexpected growth for a single prizewinner’s work extends to changes in the growth of an entire topic, and current theoretical arguments and empirical work are nascent. On the one hand, scholars have argued that the increased interest in a prizewinning scientist’s work may likewise increase interest in the topic associated with a prize9 and longitudinal data on over 10,000 scientific topics.As a first step toward understanding the possible links between prizes and a topic’s extraordinary growth, we investigated whether prizes are statistically associated with the onset of a period of abnormal growth in a topic’s productivity, impact, and the migration of scientists into and out of the topic. Our analysis uses new data on hundreds of recognized scientific prizes worldwide16. To validate the Wikipedia data, we manually cross-checked it with prize-related data on dedicated webpages and in print media. Figure From various sources, we collected data on 405 scientific prizes conferred 2900 times between 1970 and 2007 with respect to 11,539 scientific topics in 19 disciplines. Scientific prize data was collected from Wikipedia pages on prizes and scientists. The prizes in our sample include awards like the Wolf Prize and Turing Prize, as well as hundreds of other prizes recognized on Wikipedia’s “scientific prizes” page26. As a validity check, MAG uses statistical sampling to verify the face validity of the classification of papers to topics28 (see SI. Sec.1 for details).Scientific topic data comes from Microsoft Academic Graph (MAG). MAG covers over 172 million publications by 209 million authors in 48,000 journals from 1800 to 2017. It uses crowdsourcing, AI, and NLP to generate meaningful and plausible classifications of scientific topics in ways that integrate human expert observations and empirical replicability. MAG defines the universe of scientific topics using Wikipedia article pages that are classified as being on “scientific topics”; these pages are created and updated by scientists and users through crowdsourcing. MAG then uses NLP and AI to assign research publications to topics by associating a paper’s text (not just keywords) with the linguistic content of Wikipedia’s scientific topics pages29. Following prior prize research13, we used DID to test for non-causal statistical relationships between prizewinning and a topic’s extraordinary growth. Also, following the literature, we combined DID with Dynamic Optical Matching (DOM)33. DOM is a longitudinal case control matching procedure that identifies a matched group of non-prizewinning topics. To test whether a prizewinning topic’s growth after the prize is awarded is significantly greater than expected, i.e., “extraordinary,” we used a difference-in-differences (DID) regression design. DID regression tests for the effects of randomly assigned treatments as well as non-causal tests of statistical significance, in which one group experiences an event that the other group does not experience33, we identified five non-prizewinning topics that had growth patterns statistically equivalent to prizewinning topics before the prize year on six growth criteria. Three growth criteria broadly represented a topic’s impact: (a) productivity, (b) number of citations, and (c) number citations of the topic’s leading scientists. Three criteria represent the movement of scientists into and out of a topic: (a) number of incumbent scientists, (b) number of new entrants, and (c) number of star scientists from outside the topic38. To ensure that prizewinning topics and their matched topics have yearly parallel growth before the prize year, prizewinning and matched topics had to be from the same discipline and had to have statistically indistinguishable growth patterns on all six measures, each year, for 10 years before the prize40.Using DOM41. “Citations” measures a topic’s yearly number of citations and captures a topic’s impact42. Citation growth was measured on an absolute and per capita basis. “Impact of Topic’s Leading Scientists” measures the mean total citations of the upper 5% of scientists working on a topic and captures the impact of a topic’s intellectual leaders. To measure a topic’s size36, we created the variable “#Incumbents,” which measures a topic’s yearly number of continuing scientists, and the variable “#Entrants,” which measures the yearly number of scientists who publish for the first time on a topic. “#Disciplinary Stars” measures the number of scientists working on a topic that are among the 5% most cited scientists in the topic’s discipline43. The last three variables ensure that matched topics and prizewinning topics have equivalently eminent scientists and likely prizewinners44. Supplementary Figure p-values > 0.2).“Productivity” measures a topic’s yearly number of publications and relates to a topic’s output, resources, and publication normst against the average growth rate of the matched topics at time t. We refer to this difference in growth as Δt, formally expressed as:To test for a statistical relationship between prizes and extraordinary growth, we compared the post-prize growth in prizewinning topics at time Yt is the prizewinning topic’s growth at time t and t’s range is −10 to +10. A Δt = 0.0 indicates no difference in the growth of the prizewinning and matched groups. Time t represents actual time in years . Extraordinary growth occurs when Δt is statistically and significantly different from zero. We analyze the growth dynamics associated with a topic’s first prize and consider a prize to be correlated with the onset of extraordinary growth if growth starts shortly after the prize year. The SI reports confirmatory robustness checks for alternative measures of Δt  is a binary variable equal to one or zero for prizewinning and matched topics, respectively. The estimated β1s all have insignificant p-values greater than 0.05, indicating that prizewinning and matched topics have no statistically significant growth differences before the prizewinning event on all six measures of growth. Post (β2) is a binary variable equal to one for the 10-year period after the prize year and equal to zero before the prize year. Prizewinning*post (β3) is the interaction term. β2 and β3 are significant for all six growth measures , demonstrating that prizewinning topics grow unexpectedly larger after the prize is awarded relative to matched topics.Prizewinning is strongly and positively related to and extraordinary growth. Relative to matched topics, prizewinning topics have unexpected and significant increases in growth on all six measures of growth. Table p-values < 0.0001). At 10 years after the prize, the growth gap increases to 25–55% depending on the growth measure .Figure In comparing the overall impact of prizewinning topics to matched topics, we observe large and consistent growth differences. Prizewinning topics display strong post-prize extraordinary growth in productivity and citation impact. At 10 years after the prize, prizewinning topics are 39.8% more productive in terms of the number of publications 1. We created a master list of the topics that new entrants into prizewinning and matched topic groups had published before the prize year. We used Shannon Entropy to quantify the topic diversity of the lists (see SI). The findings suggest that extraordinary growth positively correlates with paradigmatic diversification. As the 10 value of 1.5, the prizewinning topic group’s paradigmatic diversity is 11.6% greater than the matched topic group  and their five matched topics separately. After the prize, 60% of the prizewinning topics show growth larger than that of their specific five matched topics . This finding indicates that the results are not driven by outlier topics and are generalizable . Supplementary Figure p-values > 0.05), reinforcing our main finding—prizewinning is associated with the onset of a topic’s sustained period of unexpected and extraordinary growth.Our main findings compare differences in post-prize growth for prizewinning and matched topic groups. Here, we examined the growth of each prizewinning topics . We also created a three-category money variable defined as (a) no money, (b) money below the median, and (c) money above the median .Discipline-specific prizes often have greater perceived within-discipline status than do general prizes. For instance, the Fields Medal in math is generally viewed as more prestigious than the general-science National Medal of Science Prize53. For example, the MacArthur Prize website acknowledges that the fellowship “…is not a reward for past accomplishment, but rather an investment in a person’s originality, insight, and potential.” To code a prize for its association with recent or past research, we counted the interevent time in years between a prize year and the first year a prizewinner worked on the prizewinning topic. We then created a distribution of inter-event times across all prizes.Though prizes can be given for recent or past research, most are generally awarded for contemporary work, not longstanding research; otherwise, many prizes would exclude younger scholarst-1, t-2, and t-3 years to account for autoregressive effects of To examine the link between prize characteristics and magnitude of extraordinary growth, we regressed the 10 for our six growth variables. Prize characteristics significantly predict the magnitude of Δ10 in 17 out of 18 cases. The 17 positive tests are statistically significant and sometimes substantively large. The only null relationship out of the 18 tests indicates that prize money does not predict changes in the citation impact of a topic’s leading scientists.Figure 10 generalizes when controlling for confounds. Figure 10. For example, conditional on the topic being a prizewinner, a single standard deviation increase in recency is associated with a 13.8% increase in Δ10 of new scientists and a 14.6% increase in Δ10 of citations. Moneyed or field-specific prizes predict an increase in Δ10 of 1.9% or 5.3% in citation growth, respectively. These findings indicate that prizes are associated with extraordinary growth in a topic and that the magnitude of extraordinary growth is strongly predicted by a prize’s features. Supplementary Tables 54.The significant relationship between prize characteristics and ΔThe rapid, unexpected growth of scientific topics have long held a reputation in science because of their connection to unexpected shifts in research efforts, technology developments, and individual scientific careers. Yet, most work has focused on intricate analyses of specific cases rather than on the statistical dynamics of extraordinarly growth. We conducted a large-scale, science-wide analysis of one factor that may be associated with the onset and magnitude of growth: scientific prizes. We found that scientific prizes predict unexpectedly large changes in the growth of a research topic.Relative to matched, non-prizewinning topics with equivalent historical growth, disciplinary status, and demography, prizewinning topics are significantly more productive, higher impact, and attractive to incumbent, rookie, and star scientists. At 5-to-10 years after the prize year, prizewinning topics are over 30% more productive and are associated with significantly higher citation impact on average on a per capita basis. Also, we found that prize characteristics predict the magnitude of a topic’s unexpected and extraordinary growth. The magnitude of growth is greatest when the topic of research associated with the prize is recent, the prize is a discipline-specific rather than general science award, and the award is monied. Surprisingly, we found no evidence that funding is related to the extraordinary growth of prizewinning topics. These findings have implications for the study of the mechanisms behind the extraordinary growth of prizewinning scientific topics.55. Kuhn argued that conservative investment and risk-taking are interconnected in scientific advances. Consistent with Kuhn, we found that prizewinning topics retain a base of incumbents who perhaps reinvest in the topic with a conservative orientation that takes current ideas further, while at the same time the new entrants attracted to prizewinning topics bring with them new viewpoints that promote a risk-taking orientation for experimentation.While our work is among the first to look at how prizewinning relates to the growth of ideas rather than the careers of individual scientists, the mechanisms by which prizewinning plays a role in the abnormal growth of topics remains an important avenue of future research. We focused on the statistical links between prizes and the onset of extraordinary growth, which can provide a basis for examining mechanisms. Our findings relate to what Thomas Kuhn called the “essential tension between tradition and innovation”61.The new points of view that entrants bring to the prizewinning topic may also be connected to Kuhn’s notion of paradigm shifts. Paradigm shifts have been identified in a few detailed case studies and focus on a topic’s revolutionary growth in size and impact. For example, Kuhn references work on the Copernican revolution that indicated that the earth-centric view of the solar system was replaced with sun-centric view of the solar system over a more than 100-year period. Our work suggests that a possible early source of a paradigm shift maybe the onset of a topic’s unexpected growth, which involves an influx of new scientists whose research expertize and diverse demographics provide the potential building blocks of new paradigms, a notion compatible with the teams, social network, and organizational literatures that have shown that new entrants with diverse backgrounds can transform thinking and stimulate innovation62. In this theoretical argument, Zuckerman argued that prizes may act as signals to scientists that a prizewinning topic offers comparatively strong prospects for professional growth, or conversely, prizes signal the end of a period of growth by suggesting that a topic’s potential opportunities for professional recognition have run their course, leading scientists to move away from the prizewinning topic25.Our findings also relate to Zuckerman’s prizes-as-signals argumentExamining our findings in light of these crisscrossing arguments suggests conditional support for the claim that a prizewinning topic’s intellectual and professional attractiveness become more rather than less positive after the prize’s conferment. First, we found that the prize characteristics of money, disciplinary-specialization, and recency are positively related to the onset and magnitude of extraordinary growth. Second, we found that rookie and star scientists begin working on prizewinning topics in unexpectedly high numbers after the prize’s award. Nevertheless, a firm conclusion may have to wait for new data or emerging natural experiments that could shed more definitive light on these causal arguments and their contingencies.63. For example, special funding was dedicated boost rates of interdisciplinary research65. Regardless of the stated objectives of funding, Myers (2020) found that funding weakly induces scientists to change their research direction47. Consistent with Myers’ work, we found that available data on prizewinning and non-prizewinning topics do not differ in NIH grants received before the prize’s conferral, and funding remains flat for prizewinning topics after the prize, indicating that funding levels do not explain the association between prizes and a topic’s extraordinary growth. While this result is consistent with other research showing that funding does not materially change research agendas already in process47, the finding does rely only on NIH funding, which is a large and leading source of funding, but does not necessarily generalize to all types of funding or funding practices. Nevertheless, with the number of topics growing each year59 while funding levels have remain relatively flat suggests that the link between funding and extraordinary growth may be an especially important target for future research pursuits.Funding stands out as a possible driver of the growth of topics because funding decisions intentionally involve peer and expert reviews designed to steer researchers and resources to topics predicted to be promising research areas62. To date, the answer to this question has remained beyond the reach of empirical work, including in this work, as the answer depends on many factors such as the multiple ways in which an idea’s quality can be defined and measured. What has been determined is that prizes are awarded on average to worthy work. For example, the official statement by the International Congress of Mathematicians, which include the Field’s Medal, noted that on average prizes are not intended to select the best work, just work that is worthy: “We must bear in mind how clearly hindsight shows that past recipients of the Field’s medal were only a selection from a much larger group of mathematicians whose impact on mathematics was at least as great as that of the chosen” (ICM 1994)12.A central question in the scientific prize literature since its inception has been whether prizes “select” the highest quality research9 found that the number of prizes worldwide have proliferated, which presumably offers more opportunity to celebrate scientists and ideas, however, as prizes have proliferated, prizes have become increasingly concentrated within a relatively small network of elite scientists and their mentees. Further, the most successful mentees study topics that differ from their mentor’s topics of study, suggesting that skills associated with conducting prizewinning work can be mentored and applied to new research areas16. Future research may therefore examine ways in which prizewinning tacit knowledge and research skills can be diffused more broadly across scientists and topics, and how vacancy chains within the prize network may open and close.If one accepts the ICM’s approach to prizes, newly identified linkages among prizewinners and prizes raise related questions about prizes and meritocracy. Ma et al. 18. Focusing on research areas where women’s participation is large and there are many prizes, such as biomedicine, women are winning prizes a rates closer to their representation in the field but the prizes they win have lower prestige and less money than the prizes won by their male counterparts18. Those trends coupled with the finding that a prize’s prestige and money predict the magnitude of extraordinary growth a prize can have on a topic suggests that future research should investigate how prize committee nomation and decision procedures are linked to diversity, a process already taking place among some prize committees66.Another area of prize meritocracy focuses on representation. New research indicates that women are winning prizes more inline with their participation rates in science but continue to be but statistically less likely to win research prizes than their male peersRelatedly, the question of prize meritocracy in science depends on the availability of data that can connect scientists, topics of study, and impact. Here we used the relatively new Microsoft Academic Graph (MAG) data, which uses expert human opinion and algorthims to identify differences in ideas and topics. The relatively new benefits of the MAG data is that it has explicit reproducbile procedures that can be evaluated for bias. Nevertheless, science is an ever changing entity. Year to year, new fields emerge and the semantic meaning of terms change over time and at different rates across different communities of practice, which means MAG provides a defensible snapshot of scientific topics, but not necessarily an immutable one.In this way, our work contributes to knowledge about changes in scientific thinking, the mobility of scientists between topics, and investment funding that together broaden understanding of how the frontiers of science develop.29. Borjas and Doran12 studied how Field Medal prizewinners’ career change relative to non-prizewinners. In their case, like ours, prizes were not assumed to be randomly assigned to topic. Hence, they used matching, where matching is done between the prizewinner and a set of “contenders” non-prizewinners whose historical scholarly performance would have made them contenders for the prize. To justify matches between prizewinners and non-prizewinners, Borjas and Doran stated, “In short, while it is tempting to claim that the 52 Fields Medal recipients are in a class by themselves and that there are no losing contenders with equivalent or better early achievements, this view does not correspond with what mathematicians themselves have written12.” For example, The International Congress of Mathematicians67, which awards the Fields Medal, the Nevanlinna Prize, the Gauss Prize, and the Chern Medal during the congress’s opening ceremony has officially stated: “We must bear in mind how clearly hindsight shows that past recipients of the Fields Medal were only a selection from a much larger group of mathematicians whose impact on mathematics was at least as great as that of the chosen” (ICM 1994)12. The arbitrariness in the number, timing, and field distribution of Fields Medal recipients means that a similarly great group of “contenders” should exist that can be contrasted with the winners in a difference-in-differences strategy to determine how winning the medal influences productivity and research choices.” Similarly, the DID regression used in our analysis is specified as follows:Zi,t is one of our six outcome variables for topic i at time t. Prizewinningi is a dummy variable quantifying whether the topic 68. If the topic belongs to the matched group, the prizewinning year of the related prizewinning topic will be used as the reference point. To study whether a growth pattern before and after a topic is associated with a topic’s prizewinning event, we combine difference-in-difference regression with matching. This approach has been used frequently in studies of prizes and in other areas where observation data is not randomly assigned and where experimental random assignment may be impossible due to factors such as harm to subjects33 to a time-series data to simultaneously maximize the closeness and balance characteristics of accurate matching69. To study the relationship between between prizewinning and a topic’s growth pattern, we measured a topic’s growth for a 10-year period prior to the prizewinning event and 10 years after the prizewinning event for a total of 21 years of study per topic. In our periodization, time zero designates the prizewinning event year. The 10-year period prior to time zero was used to find five matched, non-prizewinning topics in the same discipline that grew in a statistically indistinguishable way from the prizewinning topic’s pre-prize growth on six growth measures: (a) productivity, (b) citation, (c) topic’s lead scientist impact, (d) #incumbent scientists, (e) #entrants, and (f) #disciplinary stars. The 10-year period after the prizewinning event was used to measure differences in the growth of the prizewinng topic and its matched, non-prizewinning topics. Our MAG data begins in 1960 and ends in 2017, which permitted us to study prizes and topic growth between 1970 and 2007. Our sample includes 12, 041 prizewinning of which a total of 11,539 topics (>95%) prizewinning topics could be statistically matched to 5 non-prizewinning topic using DOM. If a topic is associated with multiple prizes over time, we studied growth from the first prizewinning event. Limiting the analysis to topics win one prize during the 10-year post-prize period produced same results as the full sample.To select the matched non-prizewinning topics, we used a Dynamic Optimal Matching method, which applies the Optimal Matching Method32. To achieve this, for each prizewinning topic 70t* represents the first prizewinning year for topic First, we selected a matched topic candidate poolSecond, to ensure the balance between the matched and prizewinning topics for the entire system, we select 5 matching topics from the candidate pool to be the topic’s peer group. In this process, we (1) minimized the distances between the matched and prizewinning topics in terms of n and for any time t before the prizewinning event, where the differences between the prizewinning topic 32. We found the best-optimized matching possible where (1) the distance between the prizewinning topics and the matched topics is minimized; at the same time, (2) the difference between the matched and prizewinning groups is not statistically significant for any Specifically, we make sure that the differences between the prizewinning and matched topic groups are small enough for each matching category Here Further information on research design is available in the Supplementary InformationReporting Summary


Small additions of nanofiber materials make it possible to change the properties of polymers. However, the uniformity of the additive distribution and the strength of its bond with the polymer matrix are determined by the surface of the nanofibers. Silanes, in particular, allow you to customize the surface for better interaction with the matrix. The aim of our work is to study an approach to silanization of nanofibers of aluminum oxide to obtain a perfect interface between the additive and the matrix. The presence of target silanes on the surface of nanofibers was shown by XPS methods. The presence of functional groups on the surface of nanofibers was also shown by the methods of simultaneous thermal analysis, and the stoichiometry of functional groups with respect to the initial hydroxyl groups was studied. The number of functional groups precipitated from silanes is close to the number of the initial hydroxyl groups, which indicates a high uniformity of the coating in the proposed method of silanization. The presented technology for silanizing alumina nanofibers is an important approach to the subsequent use of this additive in various polymer matrices. Nanomaterials are characterized by the fact that their properties are determined not so much by their internal structure as by the structure of their surface . It is cDuring the compounding of polymers with nanomaterials, the latter are introduced into the polymer matrix and distributed over it. Depending on the nanoparticle’s surface properties, it can both bind and order polymer chains around itself  and, on Since the middle of the twentieth century, a method of surface modification has been known owing to the hydrolyzable organosilicon compounds’ interaction with a hydrophilic surface . This meOne of the interesting nanostructured components are alumina nanofibers obtained by the technology of melting aluminum oxidation . AluminaModern methods of surface functionalization are very diverse and are based on the chemical interaction of a primer with surface groups . In addiDepending on the surface functionalization procedure, nanoparticles exhibit completely different properties. During silanization, the process of hydrolysis of silanes on the surface can occur in the presence of an aqueous adsorbate and moist air. This can lead to the appearance of silica aggregates around the nanofibers, which will loosen the interface between the additive and the matrix. It is important to ensure a strong bond between the nanoparticle and the polymer matrix and to prevent any inclusions in the interface. For silanes, this can be realized in the case when the hydrolysis of alkoxide groups occurs strictly on the surface of the nanoparticle. Then, the functional group interacting with the polymer matrix will be directly attached to the surface of the nanofibers. The aim of our work is to study an approach to silanization of nanoparticles in which functional groups bind only to the surface of nanofibers, and hydrolyzed silanes do not create extraneous aggregates on the surface. This article describes the approaches and method for treating alumina nanofibers with silanes in order to control the interaction interface between the polymer and the additive.Alumina nanofibers were obtained from ENAW-1199 aluminum using the molten aluminum oxidation technology , similarThe selection of silanization modes made it possible to develop an optimal procedure for the treatment of alumina nanofibers with silanes. For each silanziation, 10 g of alumina nanofibers was taken and dried at a temperature of 140 °C in a ShS-40-02 SPU drying oven for about 8 h in order to remove all adsorbed water from the surface, and at the same time to preserve hydroxyl groups in the surface structure. Then, the nanofibers were dispersed in toluene using an overhead stirrer based on the SGR-1 YHCHEM reactor with a stirring speed of 1000 rpm within 90 min. Next, the suspension was heated to 80 °C with stirring at 600 rpm within 40 min. The selected silanes were added to the obtaining dispersion in the amount of 5 g. Thus, in the obtained dispersion, the only place where silane can be hydrolyzed is the surface of alumina nanofibers according to the scheme . The silHeating is used to accelerate the silane’s diffusion in the medium and the speed of its binding to the surface of nanofibers. After thermal stabilization of the alumina nanofibers’ dispersion in toluene, the required silane is added with stirring. After stirring the mixture for an hour, it is cooled, rinsed with toluene, and decanted. Toluene residues are removed by drying at a temperature of 120–140 °C in a drying oven within 8 h.Simultaneous thermal analysis was used to determine functional groups on the surface of alumina nanofibers by weight loss and the characteristic heat flow to which this process leads. Samples were analyzed on a NETZCH Jupiter 449 . Samples in the form of a powder were placed in a Pt crucible on a differential sensor with an identical Pt crucible as a reference, and then heated in a thermostabilized oven at a rate of 10 °C/min in air flow of 100 sccm. The sensor was also blown with a protective argon flow of 100 sccm.−9 mBar. The spectra were excited by monochromatic Al Kα irradiation (1486.6 eV) of an X-ray tube. The C 1s, O 1s, Al 2p, and Si 2p spectra were fitted with Gaussian–Lorentzian peak profiles after subtraction of a Shirley-type background utilizing the CasaXPS software .package. The samples were not exposed to preliminary annealing by testing at 200 °C. This could disrupt the functional groups under study.X-ray photoelectron spectra were measured with a SPECS instrument equipped with a PHOIBOS 150 MCD 9 hemispherical analyzer at an electron take-off angle of 90° with the pass energy of 10 eV for high-resolution spectra and 20 eV for survey spectra. The pressure in an analytical chamber was in the range of 102O3 structure , silicon and oxygen are contained in equal amounts, which is in good agreement with the reported data. The proportion of silicon in the sample is 2.5 % and that of nitrogen is 2.3 %; therefore, with some conventions, we can take their ratio as 1:1, i.e., corresponding to the stoichiometry of the functional group. The proportion of silicon in relation to carbon (26.0%) in the sample, that is, the silicon–carbon ratio, is 1:10, which, however, differs from the silicon/carbon ratio in the butyl-amine functional group, which is equal to 1:4. Excess carbon in the samples studied by the XPS method is most often due to adsorbed CO2 and other organic pollutants. Usually, they are disposed of by annealing at a temperature of 200–300 °C, but in our case, this would lead to the destruction of functional groups. Finally, the close ratio of the atomic fractions of oxygen (45.2%) and aluminum (23.9%) should be noted, as the bulk of the sample consists of Al2O3; their ratio in the sample should be 3:2 or 1.5:1, however, it is easy to see in the sample that their ratio is 1.9:1. The excess oxygen in the sample is also associated with the air adsorbate, which is composed of H2O and CO2.The surface’s functional groups of alumina nanofibers were determined by the XPS method . In the 6H11O2Si≡) and beyond, we do not have such a bright identifier as nitrogen. The silicon proportion in the sample is 1.4%; the ratio of this element with carbon (29.0%) is 1:21. This excess of carbon relative to the stoichiometric ratio should also be attributed to various carbonaceous contaminants. Oxygen in the sample is more related to the constituent element of alumina nanofibers than by the presence in the functional group of the ratio of the atomic fractions of oxygen (48.8%) and aluminum (20.8%); in the sample, their ratio is 2.35:1 and excess oxygen cannot be attributed in any way to its contribution from the epoxypropyl functional group. The excess oxygen in the sample is also associated with the air adsorbate, which is composed of H2O and CO2.In the alumina nanofibers’ samples coated with epoxypropyl functional groups, such elements as carbon, oxygen, silicon, and aluminum are identified. In the epoxypropyl functional group (C7H11O2Si≡), such elements as carbon, oxygen, silicon, and aluminum are identified. The silicon proportion in the sample is 1.5%; the ratio of this element with carbon (32.5%) is 1:22. Here, too, the excess of carbon relative to the stoichiometric ratio should be explained by various carbon-containing adsorbate. Oxygen in the sample is more related to the constituent element of alumina nanofibers than by the availability in the functional group of the ratio of the atomic fractions of oxygen (46.5%) and aluminum (19.5%); in the sample, their ratio is 2.38:1 and excess oxygen is also associated with air adsorbate, which consists predominantly of H2O and CO2.In alumina nanofibers’ samples coated with methacrylic functional groups (C2H3Si≡), we also identify such elements as carbon, oxygen, silicon, and aluminum. The silicon proportion in the sample is 2.7%; the ratio of this element with carbon (20.0%) is 1:7.3. Oxygen in the sample is more related to the constituent element of alumina nanofibers than by the presence in the functional group of the ratio of the atomic fractions of oxygen (51.8%) and aluminum (25.5%); in the sample, their ratio is 2:1. In this sample, we also have a deviation from the stoichiometric proportion between the elements due to the presence of air adsorbate.Finally, in alumina nanofibers’ samples coated with vinyl functional groups  that its amount strongly differs from stoichiometry (the number of OH groups is estimated at about 8–14%) and does not correspond to the data of simultaneous thermal analysis. Most likely, there is a significant influence of the background, and because of its contribution, we observe a quantitative discrepancy. Functional groups can be characterized as chemisorbed molecules, and their number, proportional to the specific surface of nanofibers, is comparable to the amount of air adsorbate. Nevertheless, we see a similarity in the values of silicon and nitrogen for the samples of alumina nanofibers functionalized with amino groups, which allows us to conclude that the target functional group is contained on the surface of the nanofibers. Generally, the presence of silicon lines in the spectra indicates that the silanization of alumina nanofibers was successful.A uniform study of samples by the method of simultaneous thermal analysis will allow a uniform description of all the main processes . When heThe sample with vinyl functional groups has the least amount of water, the evaporation of which ends at about 116 °C. This is because the vinyl functional group is the least polar of the entire sample. The vinyl group’s stability is characterized by an exothermic peak of the heat flux at 332 °C, which is associated with its oxidation. The methacrylic functional group is freed from the adsorbate at a temperature of about 143 °C, and its combustion is characterized by an exothermic peak of the heat flux at 301 °C. The epoxy functional group is freed from the adsorbate at a temperature of about 130 °C, and its combustion is characterized by an exothermic peak of the heat flux at 248 °C. The lowest combustion temperature is due to the instability of the epoxy functional group above 200 °C. Finally, the butylamine functional group is freed from the adsorbate at a temperature of about 131 °C, and its combustion is characterized by an exothermic peak in heat flux at 288 °C. These are the samples that are characterized by the largest proportion of adsorbate; this can be explained by the amine centers’ polarity.OHω = 1.61% from the data of raw alumina nanofibers’ thermal analysis. The equality in the amounts of hydroxyl and functional groups leads to the equality of their proportions, which can be expressed through the mass fraction of hydroxyl groups:If we assume that a silane is added to each hydroxyl group, then the number of functional groups will be equal to the number of hydroxyl groups on the surface of alumina nanofibers. We obtain the mass fraction of hydroxyl groups OHM is the molecular weight of the hydroxyl group, and MAl2O3 is the molecular weight of aluminum oxide. If, during thermal analysis, hydroxyl groups completely evaporate, then during the oxidation of functional groups, silicon remains on the surface of nanofibers and, taking this into account, the mass fraction of the removed part of the functional groups is determined by the ratio below:Here, the letter RM denotes the molecular weight of the functional group removed in the process of simultaneous thermal analysis, whereas SiM denotes the molecular weight of silicon.Here, the letter Data calculated from stoichiometric ratios are summarized in From the presented comparison, it can be seen that treatment with VTMS and GlyMS leads to the formation of functional groups on the surface of alumina nanofibers in an amount close to stoichiometric. There are fewer methacrylic functional groups in the silanized nanofiber sample than is suggested by stoichiometry. This can be explained by the instability of these functional groups. There are much more butylamine functional groups in the sample than is suggested by stoichiometry. The excess of butylamine groups is most likely associated with the aminosilanes’ dimerization .The interaction of organosilanes with the surface of alumina nanofibers by hydrolysis on hydroxyl groups was shown in this article. The silanes’ selection allows us to state that most of these primers effectively modify the surface, which can be used for their introduction into various polymers, both non-polar using VTMS and polar with various variants of interaction with the polymer matrix.An interesting fact is the stoichiometric closeness of the number of hydroxyl and functional groups. This indicates that the bond of silanes with the surface of alumina nanofibers occurs during the hydrolysis of only one alkoxysilane group, whereas the rest, apparently, are oxidized after the silanization process. Although it is quite possible that there are microstates in which a silane combines simultaneously with two or three hydroxyl groups, they are still realized much less frequently owing to the electrostatic repulsion of hydroxyl groups from each other. Thus, the silane molecule combines with only one hydroxyl group for purely topological reasons.It has also been shown that the silanization process is applicable to metal oxide nanomaterials such as alumina nanofibers. An important step in this procedure is the preliminary drying of the nanofibers. As a large specific surface area of the material accumulates a large amount of air adsorbate, it will necessarily lead to the hydrolysis of silanes and the loosened binding of their functional groups to the surface of alumina nanofibers.Thus, the article presents an efficient technique for silanizing alumina nanofibers with various organosilanes to improve their interface with target polymers. The improvement is achieved by the uniformity of coating the alumina nanofibers with functional groups . The sto