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Chemical Equations03:10

Chemical Equations

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Chemical equations represent the identities and relative quantities of substances involved in a chemical reaction. The substances undergoing reaction are called reactants, and their formulas are placed on the left side of the equation. The substances generated by the reaction are called products, and their formulas are placed on the right side of the equation. Plus signs (+) separate individual reactant and product formulas, and an arrow (→) separates the reactant and product (left and...
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A balanced chemical equation provides the information of chemical formulas of the reactants and products involved in the chemical change. A reaction’s stoichiometry helps predict how much of the reactant is needed to produce the desired amount of product, or in some cases, how much product will be formed from a specific amount of the reactant.
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All chemical reactions begin with a reactant, the general term for one or more substances entering the reaction. Sodium and chloride ions, for example, are the reactants in the production of table salt. One or more substances produced by a chemical reaction are called the product. Chemical reactions follow the law of conservation of mass, which means that matter cannot be created nor destroyed in a chemical reaction. The components of the reactants—the number of atoms and the...
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The status of a reversible reaction is conveniently assessed by evaluating its reaction quotient (Q). For a reversible reaction described by m A + n B ⇌ x C + y D, the reaction quotient is derived directly from the stoichiometry of the balanced equation as
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Chemical reactions often occur in a stepwise fashion, involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs.
For instance, the decomposition of ozone appears to follow a mechanism with two steps:
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Updated: Sep 7, 2025

Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks
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Chemical Reaction Networks' Programming for Solving Equations.

Ziwei Shang1, Changjun Zhou2, Qiang Zhang1

  • 1Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian 116622, China.

Current Issues in Molecular Biology
|June 20, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel DNA-based method for solving complex nonlinear equations using chemical reaction networks (CRNs). This advancement expands the capabilities of biomolecular computing for solving previously intractable mathematical problems.

Keywords:
biological molecular calculationschemical dynamicschemical reaction networksmolecular programming

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Area of Science:

  • Biomolecular Computing
  • Synthetic Biology
  • Computational Chemistry

Background:

  • Chemical Reaction Networks (CRNs) using DNA substrates demonstrate computational capabilities.
  • Solving complex computational problems requires advanced designs for basic calculation modules and reaction steps in biomolecular computing.

Purpose of the Study:

  • To present a novel method for solving nonlinear equations using DNA-based CRNs.
  • To expand the scope of solvable equations in DNA computing, including exponential, logarithmic, and trigonometric functions.

Main Methods:

  • Utilized a gateless structure basic calculation module for CRNs.
  • Designed discrete and analog algorithms to solve nonlinear equations.
  • Employed transformation methods, Taylor expansion, and Newton iteration for equation solving.
  • Improved and optimized the CRN++ programming language's basic calculation module.

Main Results:

  • Successfully solved nonlinear equations previously unsolvable by DNA-based CRNs.
  • Demonstrated the feasibility of solving exponential, logarithmic, and simple triangle equations.
  • Verified the computational method through simulations and examples.
  • Analyzed and optimized errors within the CRN++ basic module over time.

Conclusions:

  • The developed method effectively solves a wider range of nonlinear equations using DNA-based CRNs.
  • Improvements to the CRN++ programming language enhance the reliability and accuracy of biomolecular computations.
  • This work advances the potential of DNA computing for complex mathematical problem-solving.