How to choose references for journal papers

Choosing appropriate references is a crucial and often neglected skill. Yet it is important for honesty, publishing in higher impact journals, and sharing your work. While many guides exist on this, most are written to a very basic audience, so here I describe referencing for a graduate-student, with guiding principles

Honesty: Academia depends on acknowledging prior work to clarify your own contributions. Omission of references for claims can quickly cross the line into plagiarism. You don’t want your paper retracted or a 5-year ban from journals, cite the most similar prior work! Credit other authors!

Persuasion: References provide confidence in the paper’s assumptions, claims, purported literature gaps, and validity of the methods chosen. Thus, references should comprehensively support controversial claims, claims of novelty, and validation sections.

Utility: References are used by the editors to select reviewers. Other authors will get notifications (e.g. automated on google scholar) about papers that cite their work. Some journals want to see citations to their own journal, which while self-serving, does indicate that the subject is of a relevant field. Citations also increase the visibility of other papers in search engines. The publication years of citations indicates how thoroughly the authors looked at the literature in identifying gaps. Therefore, it is more useful to cite the newest works of many active authors in the field! Making lists of key authors and papers to cite is recommended (and should include those from suggested reviewers!).

Source: SMBC

Original/Primary sources: Most statements should cite the originator of an idea, such as an original theorem, the invention of an analytical technique, the invention of a technology, the first instance of a non-dimensional number, etc. Too often, writers reference reviews, aka “secondary sources,” leaving it a scavenger hunt for the reader to understand a claim. Finding original sources is easy on google scholar: search by date (custom range) and select early years until only one a few papers shows up. Check their reference sections to ensure there is nothing earlier. Other helpful search cues include using quotations “” around key terms, and using “intitle:” to search for words in the titles of papers.

Acceptable references: Ideally, peer-reviewed journal papers make up most references. Government or policy reports are good for statements where a body as made comparisons (e.g. between technologies, identifying relative health risks, etc). Patents and presentations are especially relevant when citing the origin of technologies. Textbooks and book chapters may be good references for equation sections, especially when they explain the concepts well.

Self-referencing: Because self-referencing can be motivated by helping one’s own citation stats, doing so must be done precisely to maintain integrity. Such references should be reserved for discussing the most prior relevant work, especially in the introduction where major contributions are introduced. This referencing is also relevant when describing the very latest work, which can also help address the problem that search engines often hide minimally cited work, which suppresses new papers. Generally, more than 10-15% of references being self-references is considered excessive.

Avoiding Bias: Common referencing biases include citing work from the same country or demographics, citing only work that agrees with the author on topics without community consensus, bias towards positive results, and bias towards famous authors.

Further reading: The above discussion focused on selecting reference, neglecting referencing basics like how to cite, where to place citations, selecting the most relevant reference, etc. See links below for more:

https://www.researchgate.net/publication/296695162_Enhance_the_Value_of_a_Research_Paper_Choosing_the_Right_References_and_Writing_them_Accurately

How to choose reviewers for your manuscripts

Most researchers fail to choose good reviewers who can provide prompt, well-informed, and thorough evaluations of your work. I’ve listed below some suggestions for reviewer selection based on my experience as a manuscript submitter, reviewer, and serving as an editor.

DO’s

Suggested reviewers should:

  • be from multiple closely related fields to provide diverse perspectives

  • have published on related topics in the last 3-5 years

  • have published in the chosen journal, or lower IF but related ones, often.

  • be a sufficient expert on the topic. e.g. no more junior than a student doing a PhD on the topic. You can include some more junior folk or those in industry, but the norm is for most suggested reviewers to have their doctorate already. Young assistant Profs tend to be great options.

  • be authors of relevant work that you cite sufficiently in the manuscript

  • Include a large number of options (e.g. 6+, as most usually decline).

  • Include researchers who list the topic as a key area on their google scholar’s (example)

  • have awards for “Excellence in Review” in said journal or related ones. (example). ACS, ASME, and MDPI are good about these recognitions.

DON’T’s

Don’t suggest reviewers who:

  • are from your current institution

  • have published with you in the last 3* years (*years may vary, but exceptions can be made for niche topics. Rules may vary by journal)

  • are all from the same country

  • lack sufficient expertise or current work on your specific topic

  • are retired or otherwise no longer as research active

  • be too likely to agree with you without thinking critically

  • Are so famous that they likely are too inundated with reviews to take an interest in your manuscript. For such scholars, odds are better if it’s a high IF journal or you know they have current mentees with Thesis on the topic. Even as an assistant Prof I get several review requests per week, the senior folk are flooded with requests!

Other don’t’s:

  • don’t submit manuscripts that are highly disparaging, dismissive, etc of other authors- the reviews may be harsh if those authors do review!

  • Fail to cite reviewers whose work is foundational to your topic. One should especially cite work that was the origin for ideas, and the most recent work

  • don’t forget that English-native reviewers will be more likely to be harsh towards work written by non-native speakers


Other comments:

Trouble finding appropriate reviewers is a major challenge for many papers, causing delays, and often, desk rejections by the editor when insufficient reviewers are found. There are also ways to find out if some folk in your field are particularly bad reviewers, by looking at their stats when you serve as guest editor for a journal. For example, some folk may have a very high rate of accepting reviews and not doing them, or simply having very high rejection rates. Notably, it can be okay to suggest acquaintances as reviewers, as researchers tend to meet the most relevant folk. Labs should keep running lists of potential reviewers for topics they work on- share your suggestions with your lab!

What is the most efficient desalination technology?

While seawater desalination is a renewable water source, it can’t be truly renewable without minimized energy needs. This means desalination needs two things: to be extremely energy efficient, and to be highly compatible with renewables. This begs the question: what are the most energy efficient desalination technologies? And second, how can these technologies be integrated with renewable power?

For energy efficiency, reverse osmosis desalination, which uses high pressure membranes that only pass pure water, is by far the most efficient using electrical energy[1]. The electrical energy powers pumps (often above 90% efficient), and the pressurized flow must overcome the osmotic pressure to surpass the thermodynamic minimum energy limit [2]. Therefore, the most efficient technology revolves around minimizing pumping energy. Obviously pump efficiency is key, but as these are already very efficient, the main approaches come into play in reducing wasted or excess pressure. The wasted energy forms come from three areas, in descending order: 1) excess pressure above the osmotic pressure [2,3,4], 2) pressure required to overcome membrane permeability [5,6], 3) concentration boundary layers, aka concentration polarization[4], and 4) pressure losses through membrane modules and pipes [3].

For the first main loss of energy, pumping pressure, the aim has been to follow the osmotic curve as closely as possible [2]. Multistaging pumps to step along the curve is promising, but the stepwise reductions means that to fully eliminate this energy loss, infinite pumps (with infinite cost) are required. Furthermore, efficient pumps that can handle high pressure inlets are rare and difficult to manufacture. In contrast, batch systems, which vary over time, can very closely follow these osmotic pressure curves, largely eliminating this wasted energy [3]. However, the membrane modules have finite recovery that limits this reduction, and causes batch systems to have an energy tradeoff between membrane recovery per pass and pumping recirculation energy [3]. Still, these systems have shown excellent promise, predicting 25% improvements in efficiency vs single stage systems [2]. While batch technologies are new, semibatch systems have achieved the lowest seawater desalination energy needs yet, at about 2 kWh/m3. Our preliminary results show batch systems could reach down to 1.4 kWh/m3 [3] for seawater. Furthermore, osmotically assisted batch processes could achieve such excess pressure improvements, and thus high efficiencies, for much higher salinities [3,6,7,8,9].

For the second energy loss category, ultrapermeable membranes have been studied extensively to reduce the energy required [10]. The most permeable membranes developed can increase permeability multiple orders of magnitude. However, today commercial thin-film-composite membranes achieving permeabilities above 2 L/m2hrbar, returns are diminished as concentration effects take over [6].

The next critical efficiency concern is concentration boundary layers. New spacer designs have been proposed that can reduce this effect by 2-5x, with a tradeoff in some pressure drop. Optimizing these designs with fouling and pressure concerns remains an important step in further progress on reverse osmosis.

The fourth and final main category of pressure drops is hydraulic pressure drops through pipes [10]. Simple engineering and larger pipe diameters can help with larger pipes, and better membrane spacers and module inlet designs may assist further. Pressure drops related to hydraulic components including pumps and energy recovery devices remain larger and more important.

Overall, high efficiency has been demonstrated with sources of losses working separately, but high-quality engineering bringing all of these together can still provide impressive benefits. For seawater at 50% water recovery, these means demonstrating systems operating below 2 kWh/m3, and eventually approaching the 1.09 kWh/m3 limit.

 

[1]    J. H. Lienhard V, G. P. Thiel, D. M. Warsinger, and L. D. Banchik, Low Carbon Desalination: Status and Research, Development, and Demonstration Needs. Abdul Latif Jameel World Water and Food Security Lab, MIT, 2016. (link)

[2]    D. M. Warsinger1, E. W. Tow1, K. Nayar, and J. H. Lienhard V, “Energy efficiency of batch and semi-batch (CCRO) reverse osmosis desalination,” Water Research, vol. 106, pp. 272-282, 2016.  https://doi.org/10.1016/j.watres.2016.09.029   (preprint)

[3]      S. Cordoba, A. Das, D. Warsinger, Desalination, Double-acting piston batch reverse osmosis configuration for best-in-class efficiency and low downtime, vol. 506, pp. 114959, 2021   https://doi.org/10.1016/j.desal.2021.114959

[4]     A. Das, D. Warsinger, Batch Counterflow Reverse Osmosis, Desalination, vol. 507, pp. 115008, 2021  https://doi.org/10.1016/j.desal.2021.115008

[5]    D. M. Warsinger, E. W. Tow, L. A. Maswadeh, G. Connors, J. Swaminathan, and John H. Lienhard, “Inorganic fouling mitigation by salinity cycling in batch reverse osmosis,” Water Research, vol. 137, pp. 384-394, 2018. https://doi.org/10.1016/j.watres.2018.01.060

[6]   D. M. Warsinger, J. Swaminathan, and J. H. Lienhard V, “Ultrapermeable membranes for batch desalination: maximum desalination energy efficiency, and system cost,” IDA 2017 World Congress on Water Reuse and Desalination, São Paulo, Brazil, October 15-20, 2017. (preprint)

[7]   S. P. Córdoba, A. Das, D. M. Warsinger, Improved Batch Reverse Osmosis Configuration For Better Energy Efficiency, IDA 2019 World Congress World Congress on Water Reuse and Desalination, Dubai, UAE, October 20-24, 2019.

[8]   J. Swaminathan, E. W. Tow, D. M. Warsinger, and J. H. Lienhard V, “Effect of practical losses on optimal design of batch RO systems,” IDA 2017 World Congress on Water Reuse and Desalination, São Paulo, Brazil, October 15-20, 2017. (preprint)

[9]  D. M. Warsinger, E. W. Tow, R. McGovern, G. Thiel, and J. H. Lienhard V. Batch Pressure-Driven Membrane Separation with Closed-Flow Loop and Reservoir. Full Patent US ,US10166510B, 2 previously No. 15/350,064 November 2016 (link)

[10] Rao, Akshay K., Owen R Li, Luke Wrede, Stephen M. Coan, George Elias, Sandra Cordoba, Michael Roggenberg, Luciano Castillo, and D.M. Warsinger. 2021. “A Framework for Blue Energy Enabled Energy Storage in Reverse Osmosis Processes.” Desalination, vol 511, pp 115088. https://doi.org/10.1016/j.desal.2021.115088

PhD students: The most and least productive people on the planet

A commentary drafted as a PhD student myself, by Dr. David Warsinger

There are few groups with such a disparity between poor productivity habits, but great potential, than PhD students. Typical PhD students, in their last few months before their defense, produce more publishable scientific results and write more content for papers than the rest of their PhD combined. In MIT’s mechanical engineering department, it’s not uncommon for students to produce only 1 or 2 first author papers in their first four year of graduate school, while finishing 3 or even 5 as their final year wraps up. While I was a student, I made my own approximate of how myself and peers spent their time in lab in the first year;

Capture.PNG

So what is the source of this pandemic of unproductivity? If scientific progress is the bedrock for human progress, and the majority of it is produced by the PhD’s themselves, should this wasted potential make us panic?

A significant piece of this waste is evident from the typical lab environment. You take young people with often no work experience, plop them in front of a computer with internet, remove any daily oversight, surround them with interesting socialable peers, give them no clear deadlines besides “graduate eventually”, leave them with undefined goals, and surround them with the infinite distractions of coursework and university activities. This is made worse by the diametrically opposite demands of science compared to the coursework from childhood through grad school, which regiments assignments with precise deadlines, rules, and evaluation criteria. Add to the mix the modern Professor, an advisor with a million other responsibilities than advising, and you have a recipe for a lost-time cake. Graduate students are tasked with tackling the hardest brainest problems science has to offer, and often aren’t given the foggiest clue how to go about doing so. There aren’t courses on “how to science,” instruction manuals on spending time well, or widely available mentors tasked with teaching such (the other students get to graduate once they finally figure it out!). This student isolation is worsened by a common lone-wolf expectation culture for PI’s, who are often discouraged from collaborating so they get “the credit” and tenure. So there are rarely available peer researchers at hand who can tell them quick solutions to solve common problems. There are exceptions of course, who find ways to be productive. Indeed, those students competitive for top academic jobs realize what is possible, and can coauthor 30 or more papers or patents during their PhD while completing their degree early (like my inspirational friend Nenad).

So, how do we solve this problem? There are too many ideas to list, but a first approach should be tackling each of the contributing problems.  The severe knowledge gaps on researching and self-productivity can be addressed, perhaps with heavy reading or coursework. The silo’ed environment can be reduced, perhaps by increasing collaboration, exposure to researchers with similar projects, and a dramatic change in the culture of collaboration at the student and university level. Productivity should be evaluated with processes and software, and analyzed by students and their mentors. Student expectations need to be very clear, and role models made apparent.

While I wrote most of this as a student myself, as a PI now I try to cultivate a list of books, required written training material, clear student guideline documents, and a highly collaborative lab environment. Despite these challenges, graduate students today are the cornerstone of most research progress- imagine a world where we had them operating productively!

Some days are slower than others. Much slower…  (from PhD Comics)

Some days are slower than others. Much slower… (from PhD Comics)