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# Date Archive: 2020 April

## Chemical Solutions: Step-by-Step Chemistry Series

Last week, we kicked off a four-part series on Wolfram|Alpha's step-by-step chemistry offerings with chemical reactions. Future posts will cover chemical structure and bonding along with quantum chemistry. We continue this week with chemical solutions, another foundational component of all chemistry classes.

From the blood in your veins to the oceans covering the planet, solutions are everywhere! Understanding their chemical properties is essential to sustaining life, creating new materials and treating illness. As such, disciplines ranging from biology to material science to the health professions all must be comfortable doing solution-related computations.

To master such calculations, the step-by-step results provide stepwise guides that can be viewed one step at a time or all at once. Read on for example problems covering solute concentration, solution preparation, pKa and colligative properties.

## 非線形偏微分方程式への有限要素法の適用

Mathematica 12 has powerful functionality for solving partial differential equations (PDEs) both symbolically and numerically. This article focuses on, among other things, the finite element method (FEM)–based solver for nonlinear PDEs that has been newly implemented in Version 12. After briefly reviewing basic syntax of the Wolfram Language for PDEs, including how to designate Dirichlet and Neumann boundary conditions, we will delineate how Mathematica 12 finds the solution of a given nonlinear problem with FEM. We then show some examples in physics and chemistry, such as the Gray–Scott model and the time-dependent Navier–Stokes equation. More information can be found in the Wolfram Language tutorial “Finite Element Programming,” on which most of this article is based.

## 1. はじめに

Wolfram Research社の旗艦製品であるMathematicaは，5,000 を超える組み込み関数を有するWolfram Languageを駆動する．数理モデリング，解析の基本となる常・偏微分方程式の分野においては，これらをシンボリックに，あるいは数値的に解くための強力なソルバを搭載している．最近は有限要素法(FEM) を利用した数値的求解機能が大幅に強化され，偏微分方程式(PDE)を任意の領域上で解いたり，固有値・固有関数を求めたりすることが可能となった．ここでは，最新のバージョン12における非線形偏微分方程式のFEMによる求解を中心に，現実的な問題に応用する上での流れを例とともに紹介する．なお，有限要素法を用いて非線形PDEを解くワークフローの詳細，コードはすべて公開されている．MathematicaのWolframドキュメント内で，チュートリアル“FiniteElementProgramming”を参照いただきたい．

Current Events & History

## Tackling a Pandemic: A Computer-Based Maths Approach

How did the Department of Health and Social Care (DHSC) come up with their multi-phase response to tackle COVID-19? In this post, I investigate how the UK government's original plan against the coronavirus aligns with the four-step computational thinking process. Teachers are welcome to use this post as a free resource.

Please note: where possible, I have taken data from before the DHSC's plan was published.

## The Computational Thinking Process

What is the computational thinking process? Simply put, it is a sequence of four steps that you can take in order to solve a problem. The aim is not just to obtain a solution, but to ensure that the right choices were made, the right tools were used and the right outcomes were achieved along the way. The steps are as follows: you define explicitly the problem you wish to solve, abstract it to a computational form, compute an answer, then interpret the result:

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## Chemistry Step-by-Step Solutions: Chemical Reactions

If you’re studying chemistry or are in a discipline requiring chemistry prerequisite courses, then you know how expensive the required textbooks can be. To combat this, the chemical education community has developed open educational resources to provide free chemistry textbooks. However, although free textbooks keep cash in your wallet, they don’t include solution guides for all the homework problems.

Luckily, the Step-by-Step Solutions feature of Wolfram|Alpha has got your back! Whether you’re studying remotely or collaborating via video conferencing, Wolfram|Alpha helps you learn and apply the problem-solving frameworks for chemical word problems. The step-by-step solutions provide stepwise solution guides that can be viewed one step at a time or all at once. The guides not only hone efficient problem solving, but also facilitate digging deeper into concepts that might still be murky.

## Advancing Coding Skills, Teamwork & Computational Thinking at the Wolfram Emerging Leaders Program

Computational thinking is an increasingly relevant and important skill to develop. The ability to break down problems into their component parts, and to piece together a solution quickly and accurately, is important for a variety of careers and pursuits in the 21st century. Even more important, perhaps, is that this skill enables you to express ideas clearly enough so that even a computer can understand them.
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## Finally We May Have a Path to the Fundamental Theory of Physics… and It’s Beautiful

I Never Expected This It’s unexpected, surprising—and for me incredibly exciting. To be fair, at some level I’ve been working towards this for nearly 50 years. But it’s just in the last few months that it’s finally come together. And it’s much more wonderful, and beautiful, than I’d ever imagined. In many ways it’s the […]

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## Computational Explorations of the Coronavirus on Wolfram Community

When the world is in distress, Wolfram users turn to computation! Even in the midst of this global pandemic, Wolfram staff, friends and colleagues continue to show the power of computational curiosity. We’ve provided a centralized COVID-19 data and resources page, with ways to get free licenses for Wolfram technology through August, livestreamed multiparadigm explorations into the science and data behind the virus, computational explorations from Wolfram users and more. This resource will be continually updated, so make sure to check back often!

Our community of staff and users have been incredibly active, creating their own innovative resources and exploring available data from many different angles. Wolfram Community gathers talented and experienced data scientists, biologists, chemists, supply chain experts, epidemiologists, mathematicians, physicists and more. In recent weeks, we’ve seen a flurry of activity and exploration, a willingness to share ideas and information, and mutual encouragement from industry professionals and high-school students alike.