Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 The purpose of this review has been to shed better light on the computational and mathematical techniques used for studying the photosynthetic systems and phenomena of light harvesting complexes. + 1991 word(s) 1991 2020-10-10 04:43:14 |
2 The purpose of this review has been to shed better light on the computational and mathematical techniques used for studying the photosynthetic systems and phenomena of light harvesting complexes. + 1 word(s) 1992 2020-10-13 01:45:37 | |
3 format correct -4 word(s) 1988 2020-10-26 11:17:27 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Badu, S.; Melnik, R.; Singh, S. Applications of Photosynthetic Systems. Encyclopedia. Available online: https://encyclopedia.pub/entry/2530 (accessed on 24 April 2024).
Badu S, Melnik R, Singh S. Applications of Photosynthetic Systems. Encyclopedia. Available at: https://encyclopedia.pub/entry/2530. Accessed April 24, 2024.
Badu, Shyam, Roderick Melnik, Sundeep Singh. "Applications of Photosynthetic Systems" Encyclopedia, https://encyclopedia.pub/entry/2530 (accessed April 24, 2024).
Badu, S., Melnik, R., & Singh, S. (2020, October 13). Applications of Photosynthetic Systems. In Encyclopedia. https://encyclopedia.pub/entry/2530
Badu, Shyam, et al. "Applications of Photosynthetic Systems." Encyclopedia. Web. 13 October, 2020.
Applications of Photosynthetic Systems
Edit

       In biological and life science applications photosynthesis is an important process that involves the absorption and transformation of sunlight into chemical energy. During the photosynthesis process, the light photons are captured by the green chlorophyll pigments in their photosynthetic antennae and further funneled to the reaction center. One of the most
important light harvesting complexes that are highly important in the study of photosynthesis is the membrane-attached Fenna-Matthews-Olson (FMO) complex found in the green sulfur bacteria. In this review, we discuss the mathematical formulations and computational modeling of some of the light harvesting complexes including FMO. The most recent research developments in the photosynthetic light harvesting complexes are thoroughly discussed. The theoretical background related to the spectral density, quantum coherence and density functional theory (DFT) has been elaborated.
Further, details about the transfer and excitation of energy in different sites of the FMO complex along with other vital photosynthetic light harvesting complexes have also been provided. In particular, we will review recent results on spectral density, quantum coherence, quantum entanglement and excitonic energies of different pigments in the light harvesting complexes. We will also discuss the issues pertinent to the highest occupied orbital (HOMO) and lowest unoccupied
orbital (LUMO) energies for all the bacteriochlorophyll utilizing the time-dependent DFT. These results would be helpful in studying the excitonic dynamics of the light harvesting complexes among different applications. Finally, we conclude this review by providing the current and potential applications in environmental science, energy, health and medicine, where such mathematical and computational studies of the photosynthesis and the light harvesting complexes can be readily integrated.

photosynthetic systems light harvesting complexes Fenna-Matthews-Olson (FMO) bacteriochlorophyll (BChl) density functional theory (DFT) molecular dynamics artificial photosynthesis biomimetic and synthetic biology sustainability quantum biology

1. Environmental Science Applications

       Over the past years, significant research efforts have been devoted for the production of energy from biomass to meet the increasing energy demands worldwide and keeping a check on the environmental issues. Microorganisms such as cyanobacteria and microalgae possess a significant potential in the production of biofuels, chemicals, and bio-based products for meeting the global energy crisis [1][2][3][4][5][6][7][8]. Such renewable alternatives would not only limit the reliance on fossil fuel resources but could also serve as a stepping stone for effective transition from a petroleum-based economy to a bio-based economy [3][6]. Notably, the microbial fuel cell represents a promising alternative of electricity generation from the catalysis of microorganisms found in lakes, lagoons, ponds, or even waste water reserves [9][10][11]. Microalgae is one of the examples of the photosynthetic bioorganisms that is used for the production of green bioelectricity utilizing microbial fuel cells. Furthermore, owing to the natural abundance of such living microorganisms, the bioelectricity produced is a highly cost-effective and sustainable alternative for meeting the energy demands of the growing population. However, the large-scale industrial translation of this technology is currently limited owing to several biotechnological, economic and environmental issues. Some of the associated bottlenecks, mainly related to its low stability and efficiency, can be effectively tackled by the synergetic combination of synthetic biology and nanotechnology. For example, the native electrogenic capacity and the working lifetimes of microbiological cells can be augmented utilizing the tunability of nanomaterials. More recently, an overview of the different nanomaterials used to enhance bioelectricity generation through improved photosynthesis, extracellular electron transfer and anode performance have been reviewed in [11]. More details about the photosynthetic microbial fuel cells and their integration with the conventional technology of the microbial fuel cell can be found in [12][13][14][15][16][17]. The photosynthesis can also be used for energy storage, as described in [18][19][20][21][22][23].

       The effects of different kinds of light sources on the production of biomass and pigments have been studied in the photosynthetic bacteria waste water treatment in [24]. The applications, opportunities and challenges of using microalgae group Chlorophyta for various energy and environmental applications have been reviewed in [25], highlighting some critical aspects such as the applicability of Chlorophyta in industrial and domestic waste water treatment, and removal of contaminating nutrients. Recent research advances in the waste water treatment utilizing the freshwater monocultures of filamentous algae have been reviewed and critically analyzed in [26], mainly focusing on microalgae and polyculture systems. Research gaps in translating this technology to large-scale system design, including species selection criteria, the effect of nutrient type and loading conditions, inorganic carbon supply, algae–bacteria interactions and parameters, viz., pond depth, mixing and harvesting regimes were identified along with providing a future road map for maximizing productivity and waste water treatment efficiency [27]. Furthermore, the green algae (Chlorella Kessleri) is one of the most common light harvesting complexes found in the water which can be used to measure the purity of water utilizing rigorous study of photosynthesis phenomena in them. This can be done by measuring the concentration of oxygen produced by photosynthesis in water containing green algae [28][29][30].

       The detailed understanding and analysis of quantum coherence and spectral density in the light harvesting complexes would also be helpful in the understanding of processes pertinent to the solar and photovoltaic cells [31][32][33][34][35][36][37]. Recently, different theoretical models used for describing energy absorption and transmission in solar cells and photosynthetic systems, including the FMO complex, have been critically analyzed in [38]. This study highlights that the use of sinks, traps or any artificial relaxation process in the standard theoretical models of solar energy conversion, which is developed for studying the energy transfer to the reaction center in photosynthetic systems may contradict to the second law of thermodynamics. These findings could invalidate several existing models used for studying solar energy conversion and raise significant concerns regarding some of the earlier drawn conclusions. A possible solution to address this issue has been put forward in [38] by providing a thermodynamically-consistent version of the model that explicitly describes parts of the reaction center and employs a Hamiltonian transfer to describe the energy absorption and transmission instead of a decay rate or sink term. Owing to the difficulties to probe molecular self-assembling and packing structures at the atomic level by experimental techniques, theoretical simulations are becoming a useful tool in our better understanding of the structure–property relationship of the electronic processes for organic solar cells [39][40][41][42][43][44]. Recent advances in the theoretical simulations for organic solar cells ranging from the molecular dynamics simulated packing structures to the electronic processes computed by quantum-chemical, in combination with kinetic Monte Carlo, simulations have been reviewed in [39]. The future perspective and challenges associated with the prediction of electrical characteristics and photoelectric conversion efficiencies of organic solar cells from molecular structures utilizing theoretical simulations have also been highlighted in [39].

2. Biomimetic Applications

       Artificial photosynthesis is envisioned as a promising technique for harvesting solar energy through water splitting and CO2 reduction to generate high-energy chemical fuels [45][46][47][48][49]. Although the field of artificial photosynthesis is still in its infancy phase of research, recent advances in synthetic biology have provided a significant boost to this interdisciplinary research field. The main goal of artificial photosynthesis is to assemble molecular systems into larger-scale constructs for replicating the natural processes of photosynthesis which is a quite challenging and complex task in itself [49]. Today, artificial photosynthesis is largely focused on understanding and mimicking the ultimate functionality of the natural photosynthetic phenomena for producing energy-rich fuel using cheap and environmentally friendly biomimetic compounds [47][49]. Thus, the essential components of an artificial photosynthetic device would be: (i) a light harvester (e.g., semiconductor) for converting solar photons to excited states, generation of charge-separation and regulation of the flow of collected excitation energy to the reaction sites, (ii) a reduction active reaction site and an oxidation active reaction site, where conversion of excited states to redox potential occurs, (iii) molecular catalysts (i.e., transition metal complexes) to assist water splitting and CO2 reduction system, and (iv) linkages of different molecular and nano- and macro-scale components of artificial photosynthetic elements [47][48][50].

       The artificial photosynthesis is a good source of production of chemical energy that can be used to reduce the amount of carbon dioxide present in the environment [51][52][53][54][55][56][57][58][59][60][61]. The use of artificial fertilizers has been increased in the past few decades for boosting food productivity for satisfying the needs of the growing population [62][63]. The increased consumption also brings production of the byproducts of the natural processes occurring on a daily basis that can be utilized in the production of sustainable and green energy utilizing artificial photosynthesis. Several computational techniques are also available in the literature for studying artificial photosynthesis [64][65][66][67]. In addition, the use of the small molecules to trigger the photosynthesis reaction has been recently studied in [68][69][70][71][72][73].

3. Health and Applications in Medicine

       An exciting application of nano-sized self-assemblies of the chlorosomes found in the green sulfur as a contrast agent for medical imaging for visualizing different structures and pathologies within the human body has been demonstrated in [74][75][76][77]. The feasibility and potential of such studies can be attributed to the fact that light harvesting antennas like chlorosomes have a special structure through which they can absorb light even from the region with very low intensity of light source. The previtamin D3 from 7-dehydrochlorostel level can also be determined in human skin by studying photosynthesis in them through exposure to sunlight [78][79]. The photosynthetic bacteria are also a good source of vitamin B12 and have been used in some of the important medical applications, including the treatment of anemia, neuritis and eye problems [80]. Other applications of photosynthetic bacteria include the production of coenzyme Q10 that is used for treating heart disease, brain vascular injury and anemia [80]. These bacteria can also be used to produce the porphyrin and ribonucleic acids (RNA) that again can potentially be used in treating several diseases and deficiencies in the human body [80].

4. Enhancing the Quantum Efficiency of Excitonic Energy Transfer and Ultrafast Processes in Light Harvesting Complexes

       Valuable lessons can be learned from the operating principle of photosynthesis that is a highly optimized process whose primary steps involve transport of energy while operating near theoretical quantum limits of efficiency [81]. In recent years, there have been significant research efforts that have been motivated by the hypothesis that nature may use quantum coherences to direct energy transfer [81]. There has been a resurgence of interest in quantum biology owing to the advances in experimental and computational techniques to accurately capture the quantum phenomena in biological systems at smaller length and timescales [82]. Notably, quantum effects in biology have been extensively studied in the FMO complex and small photosynthetic light harvesting antennas of bacteria and plants. Apart from our better understanding of quantum effects in these biological systems, these studies also pave the way for the rational design of optimal molecular photonic structures to achieve efficient transport of excitons [83]. Such analysis would be quite useful in designing organic semiconductors that provide an attractive alternative for the sustainable production of materials and devices in some of the emerging applications, such as consumer electronics, solar energy capture, photocatalysis, quantum computing, communication and sensing [83][84]. Clearly, a lot of work has to be done in this direction to test the proposed hypothesis, address raised controversies and discover many more functional quantum behavior [81]. Recall, e.g., earlier reported results claiming that the dynamic long-lived electronic quantum coherence in the FMO BChl complex explain its extreme efficiency that allows them to sample vast areas of phase space for finding the most efficient path. However, more recent evidence indicates that the observed long-lived coherences originate from impulsively excited vibrations and are too fast for electronic coherences to play a significant role in the exciton transfer between pigments [85]. Even more recently, the effect of underdamped intramolecular vibrational modes on enhancing excitation energy transfer has been investigated in [86], using the approach based on the numerically exact hierarchy equation of motion. This study reported that the weakly coupled underdamped vibrational mode fuels a faster excitation energy transfer, elucidating that long-lived vibrations can, in principle, enhance energy transfer, without involving long-lived electronic coherence [86]. Thus, more studies are needed in this intrinsically interdisciplinary research field, not only to improve our understanding of the mechanisms behind the fundamental photosynthetic process of nature, but also to transfer these ideas into the next-generation artificial light-harvesting materials.

References

  1. Badu, S.; Melnik, R. Fundamental molecular complexes of photosynthesis and their biomedical applications. Proceedings and Extended Abstracts. Proceedings and Extended Abstracts. In Proceedings of the IWBBIO 2017 International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2017, Granada, Spain, 26–28 April 2017; pp. 94–96.
  2. Croce, R.; van Grondelle, R.; van Amerongen, H.; van Stokkum, I. Light Harvesting in Photosynthesis; CRC Press: Boca Raton, FL, USA, 2018.
  3. Halder, P.; Azad, A. Recent trends and challenges of algal biofuel conversion technologies. In Advanced Biofuels; Elsevier: Amsterdam, The Netherlands, 2019; pp. 167–179.
  4. Syrpas, M.; Venskutonis, P.R. Algae for the production of bio-based products. In Biobased Products and Industries; Elsevier: Amsterdam, The Netherlands, 2020; pp. 203–243.
  5. Kumar, M.; Sun, Y.; Rathour, R.; Pandey, A.; Thakur, I.S.; Tsang, D.C. Algae as potential feedstock for the production of biofuels and value-added products: Opportunities and challenges. Sci. Total. Environ. 2020, 716, 137116. Appl. Sci. 2020, xx, 5 26 of 29
  6. Veeramuthu, A.; Ngamcharussrivichai, C. Potential of microalgal biodiesel: Challenges and applications. In Renewable Energy; IntechOpen: London, UK, 2020.
  7. Hitchcock, A.; Hunter, C.N.; Canniffe, D.P. Progress and challenges in engineering cyanobacteria as chassis for light-driven biotechnology. Microb. Biotechnol. 2020, 13, 363–367.
  8. Khan, A.Z.; Bilal, M.; Mehmood, S.; Sharma, A.; Iqbal, H. State-of-the-Art Genetic Modalities to Engineer Cyanobacteria for Sustainable Biosynthesis of Biofuel and Fine-Chemicals to Meet Bio–Economy Challenges. Life 2019, 9, 54.
  9. Zhang, Y.; Liu, M.; Zhou, M.; Yang, H.; Liang, L.; Gu, T. Microbial fuel cell hybrid systems for wastewater treatment and bioenergy production: Synergistic effects, mechanisms and challenges. Renew. Sustain. Energy Rev. 2019, 103, 13–29.
  10. Gul,M.M.;Ahmad,K.S.Bioelectrochemicalsystems: Sustainablebio-energypowerhouses.Biosens.Bioelectron. 2019, 142, 111576.
  11. Mouhib,M.;Antonucci,A.;Reggente,M.;Amirjani,A.;Gillen,A.J.;Boghossian,A.A.Enhancingbioelectricity generation in microbial fuel cells and biophotovoltaics using nanomaterials. Nano Res. 2019, 12, 2184–2199.
  12. ElMekawy, A.; Hegab, H.M.; Vanbroekhoven, K.; Pant, D. Techno-productive potential of photosynthetic microbial fuel cells through different configurations. Renew. Sustain. Energy Rev. 2014, 39, 617–627.
  13. Qi, X.; Ren, Y.; Liang, P.; Wang, X. New insights in photosynthetic microbial fuel cell using anoxygenic phototrophic bacteria. Bioresour. Technol. 2018, 258, 310–317.
  14. Xu, H.; Wang, L.; Wen, Q.; Chen, Y.; Qi, L.; Huang, J.; Tang, Z. A 3D porous NCNT sponge anode modified withchitosanandPolyanilineforhigh-performancemicrobialfuelcell. Bioelectrochemistry2019,129,144–153.
  15. Milano, F.; Punzi, A.; Ragni, R.; Trotta, M.; Farinola, G.M. Photonics and optoelectronics with bacteria: Making materials from photosynthetic microorganisms. Adv. Funct. Mater. 2019, 29, 1805521.
  16. Di Lauro, M.; la Gatta, S.; Bortolotti, C.A.; Beni, V.; Parkula, V.; Drakopoulou, S.; Giordani, M.; Berto, M.; Milano, F.; Cramer, T.; et al. A Bacterial Photosynthetic Enzymatic Unit Modulating Organic Transistors with Light. Adv. Electron. Mater. 2020, 6, 1900888.
  17. Sun, J.; Yang, P.; Li, N.; Zhao, M.; Zhang, X.; Zhang, Y.; Yuan, Y.; Lu, X.; Lu, X. Extraction of photosynthetic electron from mixed photosynthetic consortium of bacteria and algae towards sustainable bioelectrical energy harvesting. Electrochim. Acta 2020, 336, 135710.
  18. McKendry, P. Energy production from biomass (part 1): Overview of biomass. Bioresour. Technol. 2002, 83, 37–46.
  19. Cruz, J.A.; Avenson, T.J.; Kanazawa, A.; Takizawa, K.; Edwards, G.E.; Kramer, D.M. Plasticity in light reactions of photosynthesis for energy production and photoprotection. J. Exp. Bot. 2005, 56, 395–406.
  20. Walker, B.J.; Kramer, D.M.; Fisher, N.; Fu, X. Flexibility in the Energy Balancing Network of Photosynthesis Enables Safe Operation under Changing Environmental Conditions. Plants 2020, 9, 301.
  21. Dimitriev, O.; Yoshida, T.; Sun, H. Principles of solar energy storage. Energy Storage 2020, 2, e96.
  22. Ravi, S.K.; Rawding, P.; Elshahawy, A.M.; Huang, K.; Sun, W.; Zhao, F.; Wang, J.; Jones, M.R.; Tan, S.C. Photosynthetic apparatus of Rhodobacter sphaeroides exhibits prolonged charge storage. Nat. Commun. 2019, 10, 1–10.
  23. Liu, Y.; Ge, Z.; Sun, Z.; Zhang, Y.; Dong, C.; Zhang, M.; Li, Z.; Chen, Y. A high-performance energy storage system from sphagnum uptake waste LIBs with negative greenhouse-gas emission. Nano Energy 2020, 67, 104216.
  24. Zhou, Q.; Zhang, P.; Zhang, G. Biomass and pigments production in photosynthetic bacteria wastewater treatment: Effects of light sources. Bioresour. Technol. 2015, 179, 505–509.
  25. Abinandan, S.; Shanthakumar, S. Challenges and opportunities in application of microalgae (Chlorophyta) for wastewater treatment: A review. Renew. Sustain. Energy Rev. 2015, 52, 123–132.
  26. Liu, J.; Pemberton, B.; Lewis, J.; Scales, P.J.; Martin, G.J. Wastewater treatment using filamentous algae— A review. Bioresour. Technol. 2019, p. 122556.
  27. Umar, L.; Alexander, F.A.; Wiest, J. Application of algae-biosensor for environmental monitoring. In Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy, 25–29 August, 2015; pp. 7099–7102.
  28. Wati, A.; Rusva, R.; Umar, L. Effect of LED Wavelengths and Light-Dark Cycle on Photosynthetic Production of Chlorella Kessleri for Algae-Based Biosensor Optimization. In Journal of Physics: Conference Series; IOP Publishing: Bristol, UK, 2019; Volume 1351, p. 012003.
  29. Appl. Sci. 2020, xx, 5 27 of 29
  30. Umar, L.; Hamzah, Y.; Setiadi, R.N. Biosensor signal improvement using current mirror topology for dissolved oxygen measurement. Meas. Sci. Technol. 2019, 30, 065102.
  31. Xu, M.; Melnik, R.V.; Borup, U. Modeling anti-islanding protection devices for photovoltaic systems. Renew. Energy 2004, 29, 2195–2216.
  32. Alharbi, F.H.; Kais, S. Theoretical limits of photovoltaics efficiency and possible improvements by intuitive approaches learned from photosynthesis and quantum coherence. Renew. Sustain. Energy Rev. 2015, 43, 1073–1089.
  33. Brédas,J.L.;Sargent,E.H.;Scholes,G.D.Photovoltaicconceptsinspiredbycoherenceeffectsinphotosynthetic systems. Nat. Mater. 2017, 16, 35–44.
  34. Romero, E.; Novoderezhkin, V.I.; van Grondelle, R. Quantum design of photosynthesis for bio-inspired solar-energy conversion. Nature 2017, 543, 355–365.
  35. Dong, Y.; Cha,H.; Zhang, J.; Pastor,E.; Tuladhar,P.S.; McCulloch,I.; Durrant,J.R.; Bakulin, A.A. Thebinding energy and dynamics of charge-transfer states in organic photovoltaics with low driving force for charge separation. J. Chem. Phys. 2019, 150, 104704.
  36. Gasparini, N.; Salleo, A.; McCulloch, I.; Baran, D. The role of the third component in ternary organic solar cells. Nat. Rev. Mater. 2019, 4, 229–242.
  37. Segev, G.; Beeman, J.W.; Greenblatt, J.B.; Sharp, I.D. Hybrid photoelectrochemical and photovoltaic cells for simultaneous production of chemical fuels and electrical power. Nat. Mater. 2018, 17, 1115–1121.
  38. Gelbwaser-Klimovsky, D.; Aspuru-Guzik, A. On thermodynamic inconsistencies in several photosynthetic and solar cell models and how to fix them. Chem. Sci. 2017, 8, 1008–1014.
  39. Han, G.; Yi, Y.; Shuai, Z. From molecular packing structures to electronic processes: theoretical simulations for organic solar cells. Adv. Energy Mater. 2018, 8, 1702743.
  40. Zhao, Z.W.; Pan, Q.Q.; Geng, Y.; Wu, S.X.; Zhang, M.; Zhao, L.; Su, Z.M. A theorectical design of performant chlorinated benzothiadiazole-based polymers as donor for organic photovoltaic devices. Org. Electron. 2018, 61, 46–55.
  41. Nelson, T.R.; White, A.J.; Bjorgaard, J.A.; Sifain, A.E.; Zhang, Y.; Nebgen, B.; Fernandez-Alberti, S.; Mozyrsky, D.; Roitberg, A.E.; Tretiak, S. Non-adiabatic Excited-State Molecular Dynamics: Theory and Applications for Modeling Photophysics in Extended Molecular Materials. Chem. Rev. 2020, 120, 2215–2287.
  42. Schröder, F.A.; Turban, D.H.; Musser, A.J.; Hine, N.D.; Chin, A.W. Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation. Nat. Commun. 2019, 10, 1–10.
  43. Zhao, Z.W.; Pan, Q.Q.; Geng, Y.; Wu, Y.; Zhao, L.; Zhang, M.; Su, Z.M. Theoretical Insight into Multiple Charge-Transfer Mechanisms at the P3HT/Nonfullerenes Interface in Organic Solar Cells. ACS Sustain. Chem. Eng. 2019, 7, 19699–19707.
  44. Marmolejo-Valencia, A.F.; Mata-Pinzón, Z.; Dominguez, L.; Amador-Bedolla, C. Atomistic simulations of bulk heterojunctions to evaluate the structural and packing properties of new predicted donors in OPVs. Phys. Chem. Chem. Phys. 2019, 21, 20315–20326.
  45. Bonke, S.A.; Wiechen, M.; MacFarlane, D.R.; Spiccia, L. Renewable fuels from concentrated solar power: Towards practical artificial photosynthesis. Energy Environ. Sci. 2015, 8, 2791–2796.
  46. Fukuzumi, S. Artificial photosynthesis for production of hydrogen peroxide and its fuel cells. Biochim. Biophys. Acta (BBA)-Bioenerg. 2016, 1857, 604–611.
  47. Gamba, I. Biomimetic Approach to CO2 Reduction. Bioinorg. Chem. Appl. 2018, 2379141.
  48. Zhou,H.;Li,P.;Liu,J.;Chen,Z.;Liu,L.;Dontsova,D.;Yan,R.;Fan,T.;Zhang,D.;Ye,J. Biomimeticpolymeric semiconductor based hybrid nanosystems for artificial photosynthesis towards solar fuels generation via CO2 reduction. Nano Energy 2016, 25, 128–135.
  49. Quader, M.; Ahmed, S. Bioenergy with carbon capture and storage (BECCS): Future prospects of carbon-negative technologies. In Clean Energy for Sustainable Development; Elsevier: Amsterdam, The Netherlands, 2017; pp. 91–140.
  50. Barber, J. Photosynthetic energy conversion: Natural and artificial. Chem. Soc. Rev. 2009, 38, 185–196.
  51. Kay, A.; Graetzel, M. Artificial photosynthesis. 1. Photosensitization of titania solar cells with chlorophyll derivatives and related natural porphyrins. J. Phys. Chem. 1993, 97, 6272–6277.
  52. Berardi, S.; Drouet, S.; Francas, L.; Gimbert-Suriñach, C.; Guttentag, M.; Richmond, C.; Stoll, T.; Llobet, A. Molecular artificial photosynthesis. Chem. Soc. Rev. 2014, 43, 7501–7519.
  53. Fukuzumi, S.; Ohkubo, K.; Suenobu, T. Long-Lived Charge Separation and Applications in Artificial Photosynthesis. Acc. Chem. Res. 2014, 47, 1455–1464.
  54. Kim, D.; Sakimoto, K.K.; Hong, D.; Yang, P. Artificial Photosynthesis for Sustainable Fuel and Chemical Production. Angew. Chem. Int. Ed. 2015, 54, 3259–3266.
  55. Faunce,T.;Styring,S.;Wasielewski,M.R.;Brudvig,G.W.;Rutherford,A.W.;Messinger,J.;Lee,A.F.;Hill,C.L.; Degroot, H.; Fontecave, M.; et al. Artificial photosynthesis as a frontier technology for energy sustainability. Energy Environ. Sci. 2013, 6, 1074–1076.
  56. Mora, S.J.; Odella, E.; Moore, G.F.; Gust, D.; Moore, T.A.; Moore, A.L. Proton-Coupled Electron Transfer in Artificial Photosynthetic Systems. Accounts Chem. Res. 2018, 51, 445–453.
  57. Odella, E.; Mora, S.J.; Wadsworth, B.L.; Huynh, M.T.; Goings, J.J.; Liddell, P.A.; Groy, T.L.; Gervaldo, M.; Sereno, L.E.; Gust, D.; et al. Controlling proton-coupled electron transfer in bioinspired artificial photosynthetic relays. J. Am. Chem. Soc. 2018, 140, 15450–15460.
  58. Brown, K.A.; King, P.W. Coupling biology to synthetic nanomaterials for semi-artificial photosynthesis. Photosynth. Res. 2019, pp. 1–11.
  59. Berhanu, S.; Ueda, T.; Kuruma, Y. Artificial photosynthetic cell producing energy for protein synthesis. Nat. Commun. 2019, 10, 1–10.
  60. Lee, K.Y.; Park, S.J.; Lee, K.A.; Kim, S.H.; Kim, H.; Meroz, Y.; Mahadevan, L.; Jung, K.H.; Ahn, T.K.; Parker, K.K.; et al. Photosynthetic artificial organelles sustain and control ATP-dependent reactions in a protocellular system. Nat. Biotechnol. 2018, 36, 530–535.
  61. Lee, Y.V.; Tian, B. Learning from Solar Energy Conversion: Biointerfaces for Artificial Photosynthesis and Biological Modulation. Nano Lett. 2019, 19, 2189–2197.
  62. Bruce,A.;Faunce,T.Sustainablefuel,food,fertilizerandecosystemsthroughaglobalartificialphotosynthetic system: Overcoming anticompetitive barriers. Interface Focus 2015, 5, 20150011.
  63. Long, S.P.; Zhu, X.G.; Naidu, S.L.; Ort, D.R. Can improvement in photosynthesis increase crop yields? Plant Cell Environ. 2006, 29, 315–330.
  64. Borg, O.A.; Godinho, S.S.; Lundqvist, M.J.; Lunell, S.; Persson, P. Computational study of the lowest triplet state of ruthenium polypyridyl complexes used in artificial photosynthesis. J. Phys. Chem. A 2008, 112, 4470–4476.
  65. Barber, J.; Tran, P.D. From natural to artificial photosynthesis. J. R. Soc. Interface 2013, 10, 20120984.
  66. Asahi, R.; Jinnouchi, R. Atomistic modeling of photoelectric cells for artificial photosynthesis. Multiscale Simul. Electrochem. Devices 2020, 107.
  67. Aitchison, C.M.; Andrei, V.; Antón-García, D.; Apfel, U.P.; Badiani, V.; Beller, M.; Bocarsly, A.B.; Bonnet, S.; Brueggeller, P.; Caputo, C.A.; et al. Synthetic approaches to artificial photosynthesis: General discussion. Faraday Discuss. 2019, 215, 242–281.
  68. Darensbourg, M.Y.; Llobet, A. Preface for Small Molecule Activation: From Biological Principles to Energy Applications. Part 3: Small Molecules Related to (Artificial) Photosynthesis. Inorg. Chem. 2016, 55, 371–377.
  69. Guiglion, P.; Berardo, E.; Butchosa, C.; Wobbe, M.C.C.; Zwijnenburg, M.A. Modelling materials for solar fuel synthesisbyartificialphotosynthesis;predictingtheoptical,electronicandredoxpropertiesofphotocatalysts. J. Phys. Condens. Matter 2016, 28, 074001.
  70. Pann,J.;Roithmeyer,H.;Viertl,W.;Pehn,R.;Bendig,M.;Dutzler,J.;Kriesche,B.;Brüggeller,P. Phosphinesin artificial photosynthesis: Considering different aspects such as chromophores, water reduction catalysts (WRCs), water oxidation catalysts (WOCs), and dyads. Sustain. Energy Fuels 2019, 3, 2926–2953.
  71. Guiglion,P.;Monti,A.;Zwijnenburg,M.A. Validatingadensityfunctionaltheoryapproachforpredictingthe redox potentials associated with charge carriers and excitons in polymeric photocatalysts. J.Phys. Chem.C 2017, 121, 1498–1506.
  72. Shtarev, D.S.; Shtareva, A.V.; Ryabchuk, V.K.; Rudakova, A.V.; Serpone, N. Considerations of Trends in Heterogeneous Photocatalysis. Correlations between conduction and valence band energies with bandgap energies of various photocatalysts. ChemCatChem 2019, 11, 3534–3541.
  73. Wilbraham, L.; Sprick, R.S.; Jelfs, K.E.; Zwijnenburg, M.A. Mapping binary copolymer property space with neural networks. Chem. Sci. 2019, 10, 4973–4984.
  74. Zheng, G. Porphyrin Nanotechnology: Discovery, Clinical Translation and Beyond. In Proceedings of the 2016 Asia Communications and Photonics Conference (ACP); IEEE: Piscataway, NJ, USA, 2016, pp. 1–3.
  75. Ng, K.K.; Takada, M.; Harmatys, K.; Chen, J.; Zheng, G. Chlorosome-Inspired Synthesis of Templated Metallochlorin-Lipid Nanoassemblies for Biomedical Applications. ACS Nano 2016, 10, 4092–4101.
  76. Shao, S.; Rajendiran, V.; Lovell, J.F. Metalloporphyrin nanoparticles: Coordinating diverse theranostic functions. Coord. Chem. Rev. 2019, 379, 99–120.
  77. Mironov, A.F.; Zhdanova, K.A.; Natal’ya, A.B. Nanosized vehicles for delivery of photosensitizers in photodynamic diagnosis and therapy of cancer. Russ. Chem. Rev. 2018, 87, 859.
  78. MacLaughlin, J.A.; Anderson, R.R.; Holick, M.F. Spectral character of sunlight modulates photosynthesis of previtamin D3 and its photoisomers in human skin. Science 1982, 216, 1001–1003.
  79. Veronikis, A.J.; Cevik, M.B.; Allen, R.H.; Shirvani, A.; Sun, A.; Persons, K.S.; Holick, M.F. Evaluation of a Ultraviolet B Light Emitting Diode (LED) for Producing Vitamin D3 in Human Skin. Anticancer Res. 2020, 40, 719–722.
  80. Badu, S.; Melnik, R. NMR properties of Fenna–Matthews–Olson light harvesting complex: Photosynthesis and its biomedical applications. In Proceedings of the 2017 IEEE First, Ukraine Conference on Electrical and Computer Engineering (UKRCON), Kyiv, Ukraine, 29 May–2 June 2017; IEEE: Piscataway, NJ, USA, 2017; pp. 318–321.
  81. Lambert, N.; Chen, Y.N.; Cheng, Y.C.; Li, C.M.; Chen, G.Y.; Nori, F. Quantum biology. Nat. Phys. 2013, 9, 10–18.
  82. Cupellini, L.; Bondanza, M.; Nottoli, M.; Mennucci, B. Successes & challenges in the atomistic modeling of light-harvesting and its photoregulation. Biochim. Biophys. Acta (BBA)-Bioenerg. 2020, 1861, 148049.
  83. Lishchuk, A.; Vasilev, C.; Johnson, M.P.; Hunter, C.N.; Törmä, P.; Leggett, G.J. Turning the challenge of quantumbiologyonitshead: Biologicalcontrolofquantumopticalsystems.FaradayDiscuss.2019,216,57–71.
  84. Forn-Díaz, P.; Lamata, L.; Rico, E.; Kono, J.; Solano, E. Ultrastrong coupling regimes of light-matter interaction. Rev. Mod. Phys. 2019, 91, 025005.
  85. Wientjes, E.; Lambrev, P. Ultrafast processes in photosynthetic light-harvesting. Photosynth. Res. 2020, 144, 123–125.
  86. Duan,H.G.;Nalbach,P.;Miller,R.D.;Thorwart,M. Intramolecularvibrationsenhancethequantumefficiency of excitonic energy transfer. Photosynth. Res. 2020, pp. 1–9.
More
Information
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : , ,
View Times: 2.3K
Revisions: 3 times (View History)
Update Date: 26 Oct 2020
1000/1000